Upper Klamath Basin Landsat Image for May 25, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 16, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for April 7, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for October 29, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 23, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for September 21, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 25, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for November 8, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for September 27, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for August 4, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for October 7, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 9, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for May 6, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for April 30, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 1, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 17, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Landsat: a global land imaging program

USGS Publications Warehouse

Byrnes, Raymond A.

2012-01-01

Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs across four decades. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. In practice, NASA develops remote-sensing instruments and spacecraft, launches satellites, and validates their performance. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground-data reception, archiving, product generation, and distribution. The result of this program is a visible, long-term record of natural and human-induced changes on the global landscape.

Upper Klamath Basin Landsat Image for June 24, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-7 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 10, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-7 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Landsat: A Global Land-Imaging Project

USGS Publications Warehouse

Headley, Rachel

2010-01-01

Across nearly four decades since 1972, Landsat satellites continuously have acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space; consequently, NASA develops remote-sensing instruments and spacecraft, then launches and validates the satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground-data reception, archiving, product generation, and distribution. The result of this program is a visible, long-term record of natural and human-induced changes on the global landscape.

Landsat: A global land-imaging mission

USGS Publications Warehouse

,

2012-01-01

Across four decades since 1972, Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. NASA develops remote-sensing instruments and spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and distribution. The result of this program is a long-term record of natural and human induced changes on the global landscape.

Upper Klamath Basin Landsat Image for May 30, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for April 28, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 11, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Using Landsat satellite data to support pesticide exposure assessment in California

USGS Publications Warehouse

Maxwell, Susan K.; Airola, Matthew; Nuckols, John R.

2010-01-01

We found the combination of Landsat 5 and 7 image data would clearly benefit pesticide exposure assessment in this region by 1) providing information on crop field conditions at or near the time when pesticides are applied, and 2) providing information for validating the CDWR map. The Landsat image time-series was useful for identifying idle, single-, and multi-cropped fields. Landsat data will be limited during the winter months due to cloud cover, and for years prior to the Landsat 7 launch (1999) when only one satellite was operational at any given time. We suggest additional research to determine the feasibility of integrating CDWR land use maps and Landsat data to derive crop maps in locations and time periods where maps are not available, which will allow for substantial improvements to chemical exposure estimation.

Techniques for Producing Coastal Land Water Masks from Landsat and Other Multispectral Satellite Data

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hall, Callie

2005-01-01

Coastal erosion and land loss continue to threaten many areas in the United States. Landsat data has been used to monitor regional coastal change since the 1970s. Many techniques can be used to produce coastal land water masks, including image classification and density slicing of individual bands or of band ratios. Band ratios used in land water detection include several variations of the Normalized Difference Water Index (NDWI). This poster discusses a study that compares land water masks computed from unsupervised Landsat image classification with masks from density-sliced band ratios and from the Landsat TM band 5. The greater New Orleans area is employed in this study, due to its abundance of coastal habitats and its vulnerability to coastal land loss. Image classification produced the best results based on visual comparison to higher resolution satellite and aerial image displays. However, density sliced NDWI imagery from either near infrared (NIR) and blue bands or from NIR and green bands also produced more effective land water masks than imagery from the density-sliced Landsat TM band 5. NDWI based on NIR and green bands is noteworthy because it allows land water masks to be generated from multispectral satellite sensors without a blue band (e.g., ASTER and Landsat MSS). NDWI techniques also have potential for producing land water masks from coarser scaled satellite data, such as MODIS.

Techniques for Producing Coastal Land Water Masks from Landsat and Other Multispectral Satellite Data

NASA Technical Reports Server (NTRS)

Spruce, Joe; Hall, Callie

2005-01-01

Coastal erosion and land loss continue to threaten many areas in the United States. Landsat data has been used to monitor regional coastal change since the 1970's. Many techniques can be used to produce coastal land water masks, including image classification and density slicing of individual bands or of band ratios. Band ratios used in land water detection include several variations of the Normalized Difference Water Index (NDWI). This poster discusses a study that compares land water masks computed from unsupervised Landsat image classification with masks from density-sliced band ratios and from the Landsat TM band 5. The greater New Orleans area is imployed in this study, due to its abundance of coastal habitats and ist vulnerability to coastal land loss. Image classification produced the best results based on visual comparison to higher resolution satellite and aerial image displays. However, density-sliced NDWI imagery from either near infrared (NIR) and blue bands or from NIR and green bands also produced more effective land water masks than imagery from the density-sliced Landsat TM band 5. NDWI based on NIR and green bands is noteworthy because it allows land water masks to be generated form multispectral satellite sensors without a blue band (e.g., ASTER and Landsat MSS). NDWI techniques also have potential for producing land water masks from coarser scaled satellite data, such as MODIS.

Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites.

PubMed

Yan, Wai Yeung; Mahendrarajah, Prathees; Shaker, Ahmed; Faisal, Kamil; Luong, Robin; Al-Ahmad, Mohamed

2014-12-01

This studypresents a remote sensing application of using time series Landsat satellite images for monitoring the Trail Road and Nepean municipal solid waste (MSW) disposal sites in Ottawa, Ontario, Canada. Currently, the Trail Road landfill is in operation; however, during the 1960s and 1980s, the city relied heavily on the Nepean landfill. More than 400 Landsat satellite images were acquired from the US Geological Survey (USGS) data archive between 1984 and 2011. Atmospheric correction was conducted on the Landsat images in order to derive the landfill sites' land surface temperature (LST). The findings unveil that the average LST of the landfill was always higher than the immediate surrounding vegetation and air temperature by 4 to 10 °C and 5 to 11.5 °C, respectively. During the summer, higher differences of LST between the landfill and its immediate surrounding vegetation were apparent, while minima were mostly found in fall. Furthermore, there was no significant temperature difference between the Nepean landfill (closed) and the Trail Road landfill (active) from 1984 to 2007. Nevertheless, the LST of the Trail Road landfill was much higher than the Nepean by 15 to 20 °C after 2007. This is mainly due to the construction and dumping activities (which were found to be active within the past few years) associated with the expansion of the Trail Road landfill. The study demonstrates that the use of the Landsat data archive can provide additional and viable information for the aid of MSW disposal site monitoring.

Utilization of LANDSAT images in cartography

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Alburquerque, P. C. G.

1981-01-01

The use of multispectral imagery obtained from LANDSAT for mapping purposes is discussed with emphasis on geometric rectification, image resolution, and systematic topographic mapping. A method is given for constructing 1:250,000 scale maps. The limitations for satellite cartography are examined.

Thirty Years of Vegetation Change in the Coastal Santa Cruz Mountains of Northern California Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2015-01-01

Results from Landsat satellite image times series analysis since 1983 of this study area showed gradual, statistically significant increases in the normalized difference vegetation index (NDVI) in more than 90% of the (predominantly second-growth) evergreen forest locations sampled.

Satellite Image Atlas of Glaciers of the World

USGS Publications Warehouse

Williams, Richard S.; Ferrigno, Jane G.

2005-01-01

In 1978, the USGS began the preparation of the 11-chapter USGS Professional Paper 1386, 'Satellite Image Atlas of Glaciers of the World'. Between 1979 and 1981, optimum satellite images were distributed to a team of 70 scientists, representing 25 nations and 45 institutions, who agreed to author sections of the Professional Paper concerning either a geographic area (chapters B-K) or a glaciological topic (included in Chapter A). The scientists used Landsat 1, 2, and 3 multispectral scanner (MSS) images and Landsat 2 and 3 return beam vidicon (RBV) images to inventory the areal occurrence of glacier ice on our planet within the boundaries of the spacecrafts' coverage (between about 82? north and south latitudes). Some later contributors also used Landsat 4 and 5 MSS and Thematic Mapper, Landsat 7 Enhanced Thematic Mapper-Plus (ETM+), and other satellite images. In addition to analyzing images of a specific geographic area, each author was asked to summarize up-to-date information about the glaciers within each area and compare their present-day areal distribution with reliable historical information (from published maps, reports, and photographs) about their past extent. Because of the limitations of Landsat images for delineating or monitoring small glaciers in some geographic areas (the result of inadequate spatial resolution, lack of suitable seasonal coverage, or absence of coverage), some information on the areal distribution of small glaciers was derived from ancillary sources, including other satellite images. Completion of the atlas will provide an accurate regional inventory of the areal extent of glaciers on our planet during a relatively narrow time interval (1972-1981).

Data fusion of Landsat TM and IRS images in forest classification

Treesearch

Guangxing Wang; Markus Holopainen; Eero Lukkarinen

2000-01-01

Data fusion of Landsat TM images and Indian Remote Sensing satellite panchromatic image (IRS-1C PAN) was studied and compared to the use of TM or IRS image only. The aim was to combine the high spatial resolution of IRS-1C PAN to the high spectral resolution of Landsat TM images using a data fusion algorithm. The ground truth of the study was based on a sample of 1,020...

Earthshots: Satellite images of environmental change – Chernobyl, Ukraine

USGS Publications Warehouse

,

2013-01-01

The Landsat 5 image from April 29, 1986, was the first satellite image of the accident. The data from Landsat were used to help confirm that an explosion had happened at Chernobyl and that the plant had been shut down.

Seagrass mapping in Greek territorial waters using Landsat-8 satellite images

NASA Astrophysics Data System (ADS)

Topouzelis, Konstantinos; Makri, Despina; Stoupas, Nikolaos; Papakonstantinou, Apostolos; Katsanevakis, Stelios

2018-05-01

Seagrass meadows are among the most valuable coastal ecosystems on earth due to their structural and functional roles in the coastal environment. This study demonstrates remote sensing's capacity to produce seagrass distribution maps on a regional scale. The seagrass coverage maps provided here describe and quantify for the first time the extent and the spatial distribution of seagrass meadows in Greek waters. This information is needed for identifying priority conservation sites and to help coastal ecosystem managers and stakeholders to develop conservation strategies and design a resilient network of protected marine areas. The results were based on an object-based image analysis of 50 Landsat-8 satellite images. The time window of image acquisition was between June 2013 and July 2015. In total, the seagrass coverage in Greek waters was estimated at 2619 km2. The largest coverages of individual seagrass meadows were found around Lemnos Island (124 km2), Corfu Island (46 km2), and East Peloponnese (47 km2). The accuracy assessment of the detected areas was based on 62 Natura 2000 sites, for which habitat maps were available. The mean total accuracy for all 62 sites was estimated at 76.3%.

Options for using Landsat and RapidEye satellite images aiming the water productivity assessments in mixed agro-ecosystems

NASA Astrophysics Data System (ADS)

de C. Teixeira, Antônio H.; Leivas, Janice F.; Bayma-Silva, Gustavo

2016-10-01

For water productivity (WP) assessments, the SAFER (Surface Algorithm for Evapotranspiration Retrieving) algorithm for evapotranspiration (ET) and the Monteith's light use efficiency (LUE) model for biomass production (BIO), were applied to Landsat and RapidEye satellite images, in the Brazilian semiarid region, inside the dry season of 2011, in a mixture of irrigated and rainfed agro-ecosystems. Firstly, with the Landsat image, the methodology from which the surface temperature (T0) is derived as a residue in the radiation balance was tested. Low differences were detected, being Landsat ET with the thermal band averaged 0.9 +/- 1.5 mm d-1, while without it the mean value was 0.8 +/- 1.5 mm d-1. The corresponding Landsat BIO values were respectively 28 +/- 59 and 28 +/- 58 kg ha-1 d-1, resulting in mean WP of 1.3 +/- 1.3 kg m-3, in both cases. After having confidence on the residual methodology for retrieving T0 it was applied to the RapidEye image, resulting in average pixel values for ET, BIO and WP of 0.6 +/- 1.5 mm d-1, 26 +/- 58 kg ha-1 d-1 and 0.9 +/- 1.3 kg m-3, representing 75%, 93% and 69% of the Landsat ones obtained without the thermal band. In addition, the Surface Resistance Algorithm (SUREAL) was used to classify the agro-ecosystems into irrigated crops and natural vegetation by using the RapidEye image. The incremental values for ET, BIO and WP in 2011 were 2.0 +/- 1.3 mm d-1, 88 +/- 87 kg ha d-1 and 2.5 +/- 0.6 kg m-3, respectively, as a result of the replacement of the natural species by crops.

Accuracy comparison in mapping water bodies using Landsat images and Google Earth Images

NASA Astrophysics Data System (ADS)

Zhou, Z.; Zhou, X.

2016-12-01

A lot of research has been done for the extraction of water bodies with multiple satellite images. The Water Indexes with the use of multi-spectral images are the mostly used methods for the water bodies' extraction. In order to extract area of water bodies from satellite images, accuracy may depend on the spatial resolution of images and relative size of the water bodies. To quantify the impact of spatial resolution and size (major and minor lengths) of the water bodies on the accuracy of water area extraction, we use Georgetown Lake, Montana and coalbed methane (CBM) water retention ponds in the Montana Powder River Basin as test sites to evaluate the impact of spatial resolution and the size of water bodies on water area extraction. Data sources used include Landsat images and Google Earth images covering both large water bodies and small ponds. Firstly we used water indices to extract water coverage from Landsat images for both large lake and small ponds. Secondly we used a newly developed visible-index method to extract water coverage from Google Earth images covering both large lake and small ponds. Thirdly, we used the image fusion method in which the Google Earth Images are fused with multi-spectral Landsat images to obtain multi-spectral images of the same high spatial resolution as the Google earth images. The actual area of the lake and ponds are measured using GPS surveys. Results will be compared and the optimal method will be selected for water body extraction.

RECENT DEVELOPMENTS IN THE U. S. GEOLOGICAL SURVEY'S LANDSAT IMAGE MAPPING PROGRAM.

USGS Publications Warehouse

Brownworth, Frederick S.; Rohde, Wayne G.

1986-01-01

At the 1984 ASPRS-ACSM Convention in Washington, D. C. a paper on 'The Emerging U. S. Geological Survey Image Mapping Program' was presented that discussed recent satellite image mapping advancements and published products. Since then Landsat image mapping has become an integral part of the National Mapping Program. The Survey currently produces about 20 Landsat multispectral scanner (MSS) and Thematic Mapper (TM) image map products annually at 1:250,000 and 1:100,000 scales, respectively. These Landsat image maps provide users with a regional or synoptic view of an area. The resultant geographical presentation of the terrain and cultural features will help planners and managers make better decisions regarding the use of our national resources.

A translational registration system for LANDSAT image segments

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Erthal, G. J.; Velasco, F. R. D.; Mascarenhas, N. D. D.

1983-01-01

The use of satellite images obtained from various dates is essential for crop forecast systems. In order to make possible a multitemporal analysis, it is necessary that images belonging to each acquisition have pixel-wise correspondence. A system developed to obtain, register and record image segments from LANDSAT images in computer compatible tapes is described. The translational registration of the segments is performed by correlating image edges in different acquisitions. The system was constructed for the Burroughs B6800 computer in ALGOL language.

Landsat ETM+ False-Color Image Mosaics of Afghanistan

USGS Publications Warehouse

Davis, Philip A.

2007-01-01

In 2005, the U.S. Agency for International Development and the U.S. Trade and Development Agency contracted with the U.S. Geological Survey to perform assessments of the natural resources within Afghanistan. The assessments concentrate on the resources that are related to the economic development of that country. Therefore, assessments were initiated in oil and gas, coal, mineral resources, water resources, and earthquake hazards. All of these assessments require geologic, structural, and topographic information throughout the country at a finer scale and better accuracy than that provided by the existing maps, which were published in the 1970's by the Russians and Germans. The very rugged terrain in Afghanistan, the large scale of these assessments, and the terrorist threat in Afghanistan indicated that the best approach to provide the preliminary assessments was to use remotely sensed, satellite image data, although this may also apply to subsequent phases of the assessments. Therefore, the first step in the assessment process was to produce satellite image mosaics of Afghanistan that would be useful for these assessments. This report discusses the production of the Landsat false-color image database produced for these assessments, which was produced from the calibrated Landsat ETM+ image mosaics described by Davis (2006).

Landsat Image Map Production Methods at the U. S. Geological Survey

USGS Publications Warehouse

Kidwell, R.D.; Binnie, D.R.; Martin, S.

1987-01-01

To maintain consistently high quality in satellite image map production, the U. S. Geological Survey (USGS) has developed standard procedures for the photographic and digital production of Landsat image mosaics, and for lithographic printing of multispectral imagery. This paper gives a brief review of the photographic, digital, and lithographic procedures currently in use for producing image maps from Landsat data. It is shown that consistency in the printing of image maps is achieved by standardizing the materials and procedures that affect the image detail and color balance of the final product. Densitometric standards are established by printing control targets using the pressplates, inks, pre-press proofs, and paper to be used for printing.

BOREAS Landsat MSS Imagery: Digital Counts

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Strub, Richard; Newcomer, Jeffrey A.

2000-01-01

The Boreal Ecosystem-Atmospheric Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. The Earth Resources Technology Satellite (ERTS) Program launched the first of a series of satellites (ERTS-1) in 1972. Part of the NASA Earth Resources Survey Program, the ERTS Program and the ERTS satellites were later renamed Landsat to better represent the civil satellite program's prime emphasis on remote sensing of land resources. Landsat satellites 1 through 5 carry the Multispectral Scanner (MSS) sensor. Canada for Remote Sensing (CCRS) and BOREAS personnel gathered a set of MSS images of the BOREAS region from Landsat satellites 1, 2, 4, and 5 covering the dates of 21 Aug 1972 to 05 Sep 1988. The data are provided in binary image format files of various formats. The Landsat MSS imagery is available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Landsat Data

USGS Publications Warehouse

,

1997-01-01

In the mid-1960's, the National Aeronautics and Space Administration (NASA) embarked on an initiative to develop and launch the first Earth monitoring satellite to meet the needs of resource managers and earth scientists. The U.S. Geological Survey (USGS) entered into a partnership with NASA in the early 1970?s to assume responsibility for archiving data and distributing data products. On July 23, 1972, NASA launched the first in a series of satellites designed to provide repetitive global coverage of the Earth?s land masses. Designated initially as the "Earth Resources Technology Satellite-A" ("ERTS-A"), it used a Nimbus-type platform that was modified to carry sensor systems and data relay equipment. When operational orbit was achieved, it was designated "ERTS-1." The satellite continued to function beyond its designed life expectancy of 1 year and finally ceased to operate on January 6, 1978, more than 5 years after its launch date. The second in this series of Earth resources satellites (designated ?ERTS-B?) was launched January 22, 1975. It was renamed "Landsat 2" by NASA, which also renamed "ERTS-1" as "Landsat 1." Three additional Landsats were launched in 1978, 1982, and 1984 (Landsats 3, 4, and 5 ). (See table 1). NASA was responsible for operating the program through the early 1980?s. In January 1983, operation of the Landsat system was transferred to the National Oceanic and Atmospheric Administration (NOAA). In October 1985, the Landsat system was commercialized and the Earth Observation Satellite Company, now Space Imaging EOSAT, assumed responsibility for its operation under contract to NOAA. Throughout these changes, the USGS EROS Data Center (EDC) retained primary responsibility as the Government archive of Landsat data. The Land Remote Sensing Policy Act of 1992 (Public Law 102-5555) officially authorized the National Satellite Land Remote Sensing Data Archive and assigned responsibility to the Department of the Interior. In addition to its Landsat

Measuring snow cover using satellite imagery during 1973 and 1974 melt season: North Santiam, Boise, and Upper Snake Basins, phase 1. [LANDSAT satellites, imaging techniques

NASA Technical Reports Server (NTRS)

Wiegman, E. J.; Evans, W. E.; Hadfield, R.

1975-01-01

Measurements are examined of snow coverage during the snow-melt season in 1973 and 1974 from LANDSAT imagery for the three Columbia River Subbasins. Satellite derived snow cover inventories for the three test basins were obtained as an alternative to inventories performed with the current operational practice of using small aircraft flights over selected snow fields. The accuracy and precision versus cost for several different interactive image analysis procedures was investigated using a display device, the Electronic Satellite Image Analysis Console. Single-band radiance thresholding was the principal technique employed in the snow detection, although this technique was supplemented by an editing procedure involving reference to hand-generated elevation contours. For each data and view measured, a binary thematic map or "mask" depicting the snow cover was generated by a combination of objective and subjective procedures. Photographs of data analysis equipment (displays) are shown.

On-orbit performance of the Landsat 8 Operational Land Imager

USGS Publications Warehouse

Micijevic, Esad; Vanderwerff, Kelly; Scaramuzza, Pat; Morfitt, Ron; Barsi, Julia A.; Levy, Raviv

2014-01-01

The Landsat 8 satellite was launched on February 11, 2013, to systematically collect multispectral images for detection and quantitative analysis of changes on the Earth’s surface. The collected data are stored at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and continue the longest archive of medium resolution Earth images. There are two imaging instruments onboard the satellite: the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS). This paper summarizes radiometric performance of the OLI including the bias stability, the system noise, saturation and other artifacts observed in its data during the first 1.5 years on orbit. Detector noise levels remain low and Signal-To-Noise Ratio high, largely exceeding the requirements. Impulse noise and saturation are present in imagery, but have negligible effect on Landsat 8 products. Oversaturation happens occasionally, but the affected detectors quickly restore their nominal responsivity. Overall, the OLI performs very well on orbit and provides high quality products to the user community. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Improving the mapping of crop types in the Midwestern U.S. by fusing Landsat and MODIS satellite data

NASA Astrophysics Data System (ADS)

Zhu, Likai; Radeloff, Volker C.; Ives, Anthony R.

2017-06-01

Mapping crop types is of great importance for assessing agricultural production, land-use patterns, and the environmental effects of agriculture. Indeed, both radiometric and spatial resolution of Landsat's sensors images are optimized for cropland monitoring. However, accurate mapping of crop types requires frequent cloud-free images during the growing season, which are often not available, and this raises the question of whether Landsat data can be combined with data from other satellites. Here, our goal is to evaluate to what degree fusing Landsat with MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) data can improve crop-type classification. Choosing either one or two images from all cloud-free Landsat observations available for the Arlington Agricultural Research Station area in Wisconsin from 2010 to 2014, we generated 87 combinations of images, and used each combination as input into the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to predict Landsat-like images at the nominal dates of each 8-day MODIS NBAR product. Both the original Landsat and STARFM-predicted images were then classified with a support vector machine (SVM), and we compared the classification errors of three scenarios: 1) classifying the one or two original Landsat images of each combination only, 2) classifying the one or two original Landsat images plus all STARFM-predicted images, and 3) classifying the one or two original Landsat images together with STARFM-predicted images for key dates. Our results indicated that using two Landsat images as the input of STARFM did not significantly improve the STARFM predictions compared to using only one, and predictions using Landsat images between July and August as input were most accurate. Including all STARFM-predicted images together with the Landsat images significantly increased average classification error by 4% points (from 21% to 25%) compared to using only Landsat

Landsat Data Continuity Mission, now Landsat-8: six months on-orbit

USGS Publications Warehouse

Markham, Brian L.; Storey, James C.; Irons, James R.

2013-01-01

The Landsat Data Continuity Mission (LDCM) with two pushbroom Earth-imaging sensors, the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS), was launched on February 11, 2013. Its on-orbit check out period or commissioning phase lasted about 90 days. During this phase the spacecraft and its instruments were activated, operationally tested and their performance verified. In addition, during this period, the spacecraft was temporarily placed in an intermediary orbit where it drifted relative to the Landsat-7 spacecraft, providing near simultaneous imaging for about 3 days, allowing data comparison and cross calibration. After this tandem-imaging period, LDCM was raised to its final altitude and placed in the position formerly occupied by Landsat-5, i.e., 8 days out of phase with Landsat-7, with about a 10:10 AM equatorial crossing time. At the end of commissioning, the satellite was transferred to the United States Geological Survey (USGS), officially renamed Landsat-8 and declared operational. Data were made available to the public beginning May 31, 2013. The performance of the satellite and two instruments has generally been excellent as evidenced in the quality of the distributed data products. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Landsat: A global land-observing program

USGS Publications Warehouse

,

2005-01-01

Landsat represents the world’s longest continuously acquired collection of space-based land remote sensing data. The Landsat Project is a joint initiative of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) designed to gather Earth resource data from space. NASA developed and launched the spacecrafts, while the USGS handles the operations, maintenance, and management of all ground data reception, processing, archiving, product generation, and distribution.Landsat satellites have been collecting images of the Earth’s surface for more than thirty years. Landsat’s Global Survey Mission is to repeatedly capture images of the Earth’s land mass, coastal boundaries, and coral reefs, and to ensure that sufficient data are acquired to support the observation of changes on the Earth’s land surface and surrounding environment. NASA launched the first Landsat satellite in 1972, and the most recent one, Landsat 7, in 1999. Landsats 5 and 7 continue to capture hundreds of additional images of the Earth’s surface each day. These images provide a valuable resource for people who work

NASA Satellite Captures Super Bowl Cities - Seattle

NASA Image and Video Library

2015-01-30

Landsat 7 image of Seattle, Washington acquired August 23, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Phoenix

NASA Image and Video Library

2015-01-30

Landsat 7 image of Phoenix, Arizona acquired November 28, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

40 years of Landsat images: What we learned about science and politics

NASA Astrophysics Data System (ADS)

Dozier, Jeff

2014-03-01

The first Landsat (then called ERTS - Earth Resources Technology Satellite) launched in 1972. Landsat 8 launched in February 2013. The 40 + years of images have yielded a remarkable history of changes in Earth's land surface, and the program has accomplished significant technological achievements. However, the sustained long-term record owes more to luck than careful program planning, and especially benefitted from the remarkable 27-year life of Landsat 5. Recommendations for the future center mainly on making the program a real Program with a commitment to sustaining it, as well as some ideas to reduce cost and improve effectiveness.

Applications based on restored satellite images

NASA Astrophysics Data System (ADS)

Arbel, D.; Levin, S.; Nir, M.; Bhasteker, I.

2005-08-01

Satellites orbit the earth and obtain imagery of the ground below. The quality of satellite images is affected by the properties of the atmospheric imaging path, which degrade the image by blurring it and reducing its contrast. Applications involving satellite images are many and varied. Imaging systems are also different technologically and in their physical and optical characteristics such as sensor types, resolution, field of view (FOV), spectral range of the acquiring channels - from the visible to the thermal IR (TIR), platforms (mobilization facilities; aircrafts and/or spacecrafts), altitude above ground surface etc. It is important to obtain good quality satellite images because of the variety of applications based on them. The more qualitative is the recorded image, the more information is yielded from the image. The restoration process is conditioned by gathering much data about the atmospheric medium and its characterization. In return, there is a contribution to the applications based on those restorations i.e., satellite communication, warfare against long distance missiles, geographical aspects, agricultural aspects, economical aspects, intelligence, security, military, etc. Several manners to use restored Landsat 7 enhanced thematic mapper plus (ETM+) satellite images are suggested and presented here. In particular, using the restoration results for few potential geographical applications such as color classification and mapping (roads and streets localization) methods.

Radiometric calibration of Landsat Thematic Mapper multispectral images

USGS Publications Warehouse

Chavez, P.S.

1989-01-01

A main problem encountered in radiometric calibration of satellite image data is correcting for atmospheric effects. Without this correction, an image digital number (DN) cannot be converted to a surface reflectance value. In this paper the accuracy of a calibration procedure, which includes a correction for atmospheric scattering, is tested. Two simple methods, a stand-alone and an in situ sky radiance measurement technique, were used to derive the HAZE DN values for each of the six reflectance Thematic Mapper (TM) bands. The DNs of two Landsat TM images of Phoenix, Arizona were converted to surface reflectances. -from Author

Landsat Image Mosaic of Antarctica (LIMA)

USGS Publications Warehouse

,

2007-01-01

For most of us, Antarctica was at best a distant acquaintance. Now, with the Landsat Image Mosaic of Antarctica (LIMA), we are on intimate terms. In stunning, up-close and personal detail, LIMA brings Antarctica to life. Explore this virtually cloudless, seamless, most geometrically accurate, and highest resolution satellite mosaic of Antarctica. A team of scientists from the U.S. Geological Survey, the British Antarctic Survey, and the National Aeronautics and Space Administration, with funding from the National Science Foundation, created LIMA in support of the International Polar Year (IPY; 2007?08). As the first major scientific outcome of the IPY, LIMA truly fulfills the IPY goals. LIMA is an international effort, supports current scientific polar research, encourages new projects, and helps the general public visualize Antarctica and changes happening in this southernmost environment. Researchers and the general public can download LIMA and all component Landsat scenes at no charge.

Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content.

NASA Astrophysics Data System (ADS)

Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

2016-04-01

Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil

Landsat-7 Mission and Early Results

NASA Technical Reports Server (NTRS)

Dolan, S. Kenneth; Sabelhaus, Phillip A.; Williams, Darrel L.; Irons, James R.; Barker, John L.; Markham, Brian L.; Bolek, Joseph T.; Scott, Steven S.; Thompson, R. J.; Rapp, Jeffrey J.

1999-01-01

The Landsat-7 mission has the goal of acquiring annual data sets of reflective band digital imagery of the landmass of the Earth at a spatial resolution of 30 meters for a period of five years using the Enhanced Thematic Mapper Plus (ETM+) imager on the Landsat-7 satellite. The satellite was launched on April 15, 1999. The mission builds on the 27-year continuous archive of thematic images of the Earth from previous Landsat satellites. This paper will describe the ETM+ instrument, the spacecraft, and the ground processing system in place to accomplish the mission. Results from the first few months in orbit will be given, with emphasis on performance parameters that affect image quality, quantity, and availability. There will also be a discussion of the Landsat Data Policy and the user interface designed to make contents of the archive readily available, expedite ordering, and distribute the data quickly. Landsat-7, established by a Presidential Directive and a Public Law, is a joint program of the National Aeronautics and Space Administration (NASA) Earth Science Enterprise and the United States Geological Survey (USGS) Earth Resources Observing System (EROS) Data Center.

NASA Satellite Captures Super Bowl Cities - Denver, CO

NASA Image and Video Library

2016-02-06

Landsat 7 image of Denver area acquired Nov 3, 2015. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD...Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Seattle [annotated

NASA Image and Video Library

2015-01-30

Landsat 7 image of Seattle, Washington acquired August 23, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Boston/Providence

NASA Image and Video Library

2015-01-30

Landsat 7 image of Boston/Providence area acquired August 25, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD...Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Phoenix [annotated

NASA Image and Video Library

2015-01-30

Landsat 7 image of Phoenix, Arizona acquired November 28, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Landsat View: Santiago, Chile

NASA Image and Video Library

2017-12-08

Santiago, Chile, ranks among the world's fastest growing cities. Chile is South America's fifth largest economy with strong export and tourism markets. More than a third of Chile's population lives in Santiago as of 2009. Taken on January 9, 1985, and January 30, 2010, this pair of images from the Landsat 5 satellite illustrates the city's steady growth. The images were made with infrared and visible light (Landsat bands 4, 3, and 2) so that plant-covered land is red. Bare or sparsely vegetated land is tan, and the city is dark silver. In the fifteen years that elapsed between 1985 and 2010, the city expanded away from the Andes Mountains along spoke-like lines, which are major roads. ---- NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Simulation of meteorological satellite (METSAT) data using LANDSAT data

NASA Technical Reports Server (NTRS)

Austin, W. W.; Ryland, W. E.

1983-01-01

The information content which can be expected from the advanced very high resolution radiometer system, AVHRR, on the NOAA-6 satellite was assessed, and systematic techniques of data interpretation for use with meteorological satellite data were defined. In-house data from LANDSAT 2 and 3 were used to simulate the spatial, spectral, and sampling methods of the NOAA-6 satellite data.

Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

NASA Astrophysics Data System (ADS)

Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

2016-06-01

The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

NASA Satellite Captures Super Bowl Cities - Boston/Providence [annotated

NASA Image and Video Library

2015-01-30

Landsat 7 image of Boston/Providence area acquired August 25, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Charlotte, NC

NASA Image and Video Library

2016-02-06

Landsat 7 image of the Charlotte, NC area acquired Oct 18, 2015. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD...Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Application of LANDSAT data and digital image processing. [Ruhr Valley, Germany

NASA Technical Reports Server (NTRS)

Bodechtel, J. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Based on LANDSAT 1 and 2 data, applications in the fields of coal mining, lignite exploration, and thematic mapping in geology are demonstrated. The hybrid image processing system, its software, and its utilization for educational purposes is described. A pre-operational European satellite is proposed.

Multispectral Landsat images of Antartica

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lucchitta, B.K.; Bowell, J.A.; Edwards, K.L.

1988-01-01

The U.S. Geological Survey has a program to map Antarctica by using colored, digitally enhanced Landsat multispectral scanner images to increase existing map coverage and to improve upon previously published Landsat maps. This report is a compilation of images and image mosaic that covers four complete and two partial 1:250,000-scale quadrangles of the McMurdo Sound region.

Landsat and water pollution

NASA Technical Reports Server (NTRS)

Castruccio, P.; Fowler, T.; Loats, H., Jr.

1979-01-01

Report presents data derived from satellite images predicting pollution loads after rainfall. It explains method for converting Landsat images of Eastern United States into cover maps for Baltimore/five county region.

Landsat View: Ouagadougou, Burkina Faso

NASA Image and Video Library

2017-12-08

The landlocked western African nation of Burkina Faso experienced a 200 percent increase in urban population between 1975 and 2000. As a result, the area of the capital city Ouagadougou grew 14-fold during this period. These Landsat images show the city expanding outward from its center in the two decades between 1986 and 2006. On Nov. 18, 1986, the Landsat 5 satellite acquired this image of the capital. This false-color image shows vegetation in shades of green and gray, water in various shades of blue, and urban areas in pink and purple. The runway of the city’s airport can be seen as a long straight line that extends from southwest to northeast south of the large lake, Bois de Boulogne. Two decades later, on Oct. 16, 2006 Landsat 7 acquired this image of Ouagadougou. Growth radiated from the city center in all directions. The green strip of vegetation north of Bois de Boulogne has been paved over and a massive new development including a large thoroughfare and traffic circle can be seen south of the airport. ---- NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find

Automatic Co-Registration of Multi-Temporal Landsat-8/OLI and Sentinel-2A/MSI Images

NASA Technical Reports Server (NTRS)

Skakun, S.; Roger, J.-C.; Vermote, E.; Justice, C.; Masek, J.

2017-01-01

Many applications in climate change and environmental and agricultural monitoring rely heavily on the exploitation of multi-temporal satellite imagery. Combined use of freely available Landsat-8 and Sentinel-2 images can offer high temporal frequency of about 1 image every 3-5 days globally.

An efficient framework for modeling clouds from Landsat8 images

NASA Astrophysics Data System (ADS)

Yuan, Chunqiang; Guo, Jing

2015-03-01

Cloud plays an important role in creating realistic outdoor scenes for video game and flight simulation applications. Classic methods have been proposed for cumulus cloud modeling. However, these methods are not flexible for modeling large cloud scenes with hundreds of clouds in that the user must repeatedly model each cloud and adjust its various properties. This paper presents a meteorologically based method to reconstruct cumulus clouds from high resolution Landsat8 satellite images. From these input satellite images, the clouds are first segmented from the background. Then, the cloud top surface is estimated from the temperature of the infrared image. After that, under a mild assumption of flat base for cumulus cloud, the base height of each cloud is computed by averaging the top height for pixels on the cloud edge. Then, the extinction is generated from the visible image. Finally, we enrich the initial shapes of clouds using a fractal method and represent the recovered clouds as a particle system. The experimental results demonstrate our method can yield realistic cloud scenes resembling those in the satellite images.

Operational calibration and validation of landsat data continuity mission (LDCM) sensors using the image assessment system (IAS)

USGS Publications Warehouse

Micijevic, Esad; Morfitt, Ron

2010-01-01

Systematic characterization and calibration of the Landsat sensors and the assessment of image data quality are performed using the Image Assessment System (IAS). The IAS was first introduced as an element of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) ground segment and recently extended to Landsat 4 (L4) and 5 (L5) Thematic Mappers (TM) and Multispectral Sensors (MSS) on-board the Landsat 1-5 satellites. In preparation for the Landsat Data Continuity Mission (LDCM), the IAS was developed for the Earth Observer 1 (EO-1) Advanced Land Imager (ALI) with a capability to assess pushbroom sensors. This paper describes the LDCM version of the IAS and how it relates to unique calibration and validation attributes of its on-board imaging sensors. The LDCM IAS system will have to handle a significantly larger number of detectors and the associated database than the previous IAS versions. An additional challenge is that the LDCM IAS must handle data from two sensors, as the LDCM products will combine the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) spectral bands.

NASA Satellite Captures Super Bowl Cities - Santa Clara, CA

NASA Image and Video Library

2017-12-08

Landsat 7 image of the Santa Clara area acquired Nov 16, 2015. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD...Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Twenty years of Landsat data accessible through the national satellite land remote sensing data archive

USGS Publications Warehouse

Larsen, Dana M.

1993-01-01

The EROS Data Center has managed to National Satellite Land Remote Sensing Data Archive's (NSLRSDA) Landsat data since 1972. The NSLRSDA includes Landsat MSS data from 1972 through 1991 and T M data from 1982 through 1993. In response to many requests from multi-disciplined users for an enhanced insight into the availability and volume of Landsat data over specific worldwide land areas, numerous world plots and corresponding statical overviews have been prepared. These presentations include information related to image quality, cloud cover, various types of data overage (i.e. regions, countries, path, rows), acquisition station coverage areas, various archive media formats (i.e. wide band video tapes, computer compatible tapes, high density tapes, etc.) and acquisition time periods (i.e. years, seasons). Plans are to publish this information in a paper sample booklet at the Pecora 12 Symposium, in a USGS circular and on a Landsat CD-ROM; the data will be also be incorporated into GLIS.

Application of LANDSAT images to the study of level soils for recognizing drainage areas. Thesis Paper

NASA Technical Reports Server (NTRS)

Espinoza, M. U.

1977-01-01

Photographic images from LANDSAT 1 were applied to the study of soil in Desaguadero, Bolivia, in order to locate areas with high agricultural and livestock potential. Photointerpretation techniques were emphasized and advantages of information obtained via multispectral satellite images in various bands and combinations were demonstrated.

Assembly of Landsat's TIRS Instrument

NASA Image and Video Library

2012-02-14

Aleksandra Bogunovic reaches across the instrument to affix the corners of a Multi-Layer Insulation blanket to the TIRS instrument. The Thermal Infrared Sensor (TIRS) will fly on the next Landsat satellite, the Landsat Data Continuity Mission (LDCM). TIRS was built on an accelerated schedule at NASA's Goddard Space Flight Center, Greenbelt, Md. and will now be integrated into the LDCM spacecraft at Orbital Science Corp. in Gilbert, Ariz. The Landsat Program is a series of Earth observing satellite missions jointly managed by NASA and the U.S. Geological Survey. Landsat satellites have been consistently gathering data about our planet since 1972. They continue to improve and expand this unparalleled record of Earth's changing landscapes for the benefit of all. For more information on Landsat, visit: www.nasa.gov/landsat Credit: NASA/GSFC/Rebecca Roth NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Landsat View: Chandler, Arizona

NASA Image and Video Library

2017-12-08

Over the last 25 years, Chandler, Arizona has traded its grid of fields for a grid of streets. Founded in 1912 on cotton, grains, alfalfa, and ostrich farms, brown and green irrigated fields still dominate the region southeast of Phoenix in this 1985 natural color image taken by Landsat 5. By 2011, the blue gray city streets in this Landsat 5 image have taken over. Chandler's economy has shifted from agriculture to manufacturing and electronics, and its population boomed from 30,000 people in 1980 to 236,000 in 2010. ---- Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Landsat image and sample design for water reservoirs (Rapel dam Central Chile).

PubMed

Lavanderos, L; Pozo, M E; Pattillo, C; Miranda, H

1990-01-01

Spatial heterogeneity of the Rapel reservoir surface waters is analyzed through Landsat images. The image digital counts are used with the aim or developing an aprioristic quantitative sample design.Natural horizontal stratification of the Rapel Reservoir (Central Chile) is produced mainly by suspended solids. The spatial heterogeneity conditions of the reservoir for the Spring 86-Summer 87 period were determined by qualitative analysis and image processing of the MSS Landsat, bands 1 and 3. The space-time variations of the different observed strata obtained with multitemporal image analysis.A random stratified sample design (r.s.s.d) was developed, based on the digital counts statistical analysis. Strata population size as well as the average, variance and sampling size of the digital counts were obtained by the r.s.s.d method.Stratification determined by analysis of satellite images were later correlated with ground data. Though the stratification of the reservoir is constant over time, the shape and size of the strata varys.

Software for Viewing Landsat Mosaic Images

NASA Technical Reports Server (NTRS)

Watts, Zack; Farve, Catharine L.; Harvey, Craig

2003-01-01

A Windows-based computer program has been written to enable novice users (especially educators and students) to view images of large areas of the Earth (e.g., the continental United States) generated from image data acquired in the Landsat observations performed circa the year 1990. The large-area images are constructed as mosaics from the original Landsat images, which were acquired in several wavelength bands and each of which spans an area (in effect, one tile of a mosaic) of .5 in latitude by .6 in longitude. Whereas the original Landsat data are registered on a universal transverse Mercator (UTM) grid, the program converts the UTM coordinates of a mouse pointer in the image to latitude and longitude, which are continuously updated and displayed as the pointer is moved. The mosaic image currently on display can be exported as a Windows bitmap file. Other images (e.g., of state boundaries or interstate highways) can be overlaid on Landsat mosaics. The program interacts with the user via standard toolbar, keyboard, and mouse user interfaces. The program is supplied on a compact disk along with tutorial and educational information.

Strait of Gibraltar, Perspective with Landsat Image Overlay

NASA Image and Video Library

2003-10-24

This perspective view shows the Strait of Gibraltar, which is the entrance to the Mediterranean Sea from the Atlantic Ocean. Europe (Spain) is on the left. Africa (Morocco) is on the right. The Rock of Gibraltar, administered by Great Britain, is the peninsula in the back left. The Strait of Gibraltar is the only natural gap in the topographic barriers that separate the Mediterranean Sea from the world's oceans. The Sea is about 3700 kilometers (2300 miles) long and covers about 2.5 million square kilometers (one million square miles), while the Strait is only about 13 kilometers (8 miles) wide. Sediment samples from the bottom of the Mediterranean Sea that include evaporite minerals, soils, and fossil plants show that about five million years ago the Strait was topographically blocked and the Sea had evaporated into a deep basin far lower in elevation than the oceans. Consequent changes in the world's hydrologic cycle, including effects upon ocean salinity, likely led to more ice formation in polar regions and more reflection of sunlight back to space, resulting in a cooler global climate at that time. Today, topography plays a key role in our regional climate patterns. But through Earth history, topographic change, even perhaps over areas as small as 13 kilometers across, has also affected the global climate. This image was generated from a Landsat satellite image draped over an elevation model produced by the Shuttle Radar Topography Mission (SRTM). The view is eastward with a 3-times vertical exaggeration to enhance topographic expression. Natural colors of the scene (green vegetation, blue water, brown soil, white beaches) are enhanced by image processing, inclusion of some infrared reflectance (as green) to highlight the vegetation pattern, and inclusion of shading of the elevation model to further highlight the topographic features. Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (99

Landsat 8 on-orbit characterization and calibration system

USGS Publications Warehouse

Micijevic, Esad; Morfitt, Ron; Choate, Michael J.

2011-01-01

The Landsat Data Continuity Mission (LDCM) is planning to launch the Landsat 8 satellite in December 2012, which continues an uninterrupted record of consistently calibrated globally acquired multispectral images of the Earth started in 1972. The satellite will carry two imaging sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will provide visible, near-infrared and short-wave infrared data in nine spectral bands while the TIRS will acquire thermal infrared data in two bands. Both sensors have a pushbroom design and consequently, each has a large number of detectors to be characterized. Image and calibration data downlinked from the satellite will be processed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center using the Landsat 8 Image Assessment System (IAS), a component of the Ground System. In addition to extracting statistics from all Earth images acquired, the IAS will process and trend results from analysis of special calibration acquisitions, such as solar diffuser, lunar, shutter, night, lamp and blackbody data, and preselected calibration sites. The trended data will be systematically processed and analyzed, and calibration and characterization parameters will be updated using both automatic and customized manual tools. This paper describes the analysis tools and the system developed to monitor and characterize on-orbit performance and calibrate the Landsat 8 sensors and image data products.

Evaluation of Landsat-7 SLC-off image products for forest change detection

USGS Publications Warehouse

Wulder, Michael A.; Ortlepp, Stephanie M.; White, Joanne C.; Maxwell, Susan

2008-01-01

Since July 2003, Landsat-7 ETM+ has been operating without the scan line corrector (SLC), which compensates for the forward motion of the satellite in the imagery acquired. Data collected in SLC-off mode have gaps in a systematic wedge-shaped pattern outside of the central 22 km swath of the imagery; however, the spatial and spectral quality of the remaining portions of the imagery are not diminished. To explore the continued use of Landsat-7 ETM+ SLC-off imagery to characterize change in forested environments, we compare the change detection results generated from a reference image pair (a 1999 Landsat-7 ETM+ image and a 2003 Landsat-5 TM image) with change detection results generated from the same 1999 Landsat-7 ETM+ image coupled with three different 2003 Landsat-7 SLC-off products: unremediated SLC-off (i.e., with gaps); histogram-based gap-filled; and segment-based gap-filled. The results are compared on both a pixel and polygon basis; on a pixel basis, the unremediated SLC-off product missed 35% of the change identified by the reference data, and the histogram- and segment-based gap-filled products missed 23% and 21% of the change, respectively. When using forest inventory polygons as a context for change (to reduce commission error), the amount of change missed was 31%, 14%, and 12% for the each of the unremediated, histogram-based gap-filled, and segment-based gap-filled products, respectively. Our results indicate that over the time period considered, and given the types and spatial distribution of change events within our study area, the gap-filled products can provide a useful data source for change detection in forested environments. The selection of which product to use is, however, very dependent on the nature of the application and the spatial configuration of change events. ?? 2008 Government of Canada.

Quantitative Assessment of Spatio-Temporal Desertification Rates in Azerbaijan during Using Timeseries Landsat-8 Satellite Images

NASA Astrophysics Data System (ADS)

Bayramov, Emil; Mammadov, Ramiz

2016-07-01

The main goals of this research are the object-based landcover classification of LANDSAT-8 multi-spectral satellite images in 2014 and 2015, quantification of Normalized Difference Vegetation Indices (NDVI) rates within the land-cover classes, change detection analysis between the NDVIs derived from multi-temporal LANDSAT-8 satellite images and the quantification of those changes within the land-cover classes and detection of changes between land-cover classes. The object-based classification accuracy of the land-cover classes was validated through the standard confusion matrix which revealed 80 % of land-cover classification accuracy for both years. The analysis revealed that the area of agricultural lands increased from 30911 sq. km. in 2014 to 31999 sq. km. in 2015. The area of barelands increased from 3933 sq. km. in 2014 to 4187 sq. km. in 2015. The area of forests increased from 8211 sq. km. in 2014 to 9175 sq. km. in 2015. The area of grasslands decreased from 27176 sq. km. in 2014 to 23294 sq. km. in 2015. The area of urban areas increased from 12479 sq. km. in 2014 to 12956 sq. km. in 2015. The decrease in the area of grasslands was mainly explained by the landuse shifts of grasslands to agricultural and urban lands. The quantification of low and medium NDVI rates revealed the increase within the agricultural, urban and forest land-cover classes in 2015. However, the high NDVI rates within agricultural, urban and forest land-cover classes in 2015 revealed to be lower relative to 2014. The change detection analysis between landscover types of 2014 and 2015 allowed to determine that 7740 sq. km. of grasslands shifted to agricultural landcover type whereas 5442sq. km. of agricultural lands shifted to rangelands. This means that the spatio-temporal patters of agricultural activities occurred in Azerbaijan because some of the areas reduced agricultural activities whereas some of them changed their landuse type to agricultural. Based on the achieved results, it

Landsat continuity: Issues and opportunities for land cover monitoring

USGS Publications Warehouse

Wulder, M.A.; White, Joanne C.; Goward, S.N.; Masek, J.G.; Irons, J.R.; Herold, M.; Cohen, W.B.; Loveland, Thomas R.; Woodcock, C.E.

2008-01-01

Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures

Landsat's TIRS Instrument

NASA Image and Video Library

2017-12-08

The Thermal Infrared Sensor (TIRS) will fly on the next Landsat satellite, the Landsat Data Continuity Mission (LDCM). The right side of the instrument is what's called the 'nadir side,' that's the side that points toward Earth when the instrument is in space. The black circle visible on the right side is where the optics for the instrument are located. In that area are the lens and the detectors. The white area is a radiator that radiates heat to keep the telescope and the detector cool. The black hole on the white area on the left is what the satellite operators point to deep space when they calibrate the instrument to the cold temperatures of space. TIRS was built on an accelerated schedule at NASA's Goddard Space Flight Center, Greenbelt, Md. and will now be integrated into the LDCM spacecraft at Orbital Science Corp. in Gilbert, Ariz. The Landsat Program is a series of Earth observing satellite missions jointly managed by NASA and the U.S. Geological Survey. Landsat satellites have been consistently gathering data about our planet since 1972. They continue to improve and expand this unparalleled record of Earth's changing landscapes for the benefit of all. For more information on Landsat, visit: www.nasa.gov/landsat Credit: NASA/GSFC/Rebecca Roth NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Landsat: building a strong future

USGS Publications Warehouse

Loveland, Thomas R.; Dwyer, John L.

2012-01-01

Conceived in the 1960s, the Landsat program has experienced six successful missions that have contributed to an unprecedented 39-year record of Earth Observations that capture global land conditions and dynamics. Incremental improvements in imaging capabilities continue to improve the quality of Landsat science data, while ensuring continuity over the full instrument record. Landsats 5 and 7 are still collecting imagery. The planned launch of the Landsat Data Continuity Mission in December 2012 potentially extends the Landsat record to nearly 50 years. The U.S. Geological Survey (USGS) Landsat archive contains nearly three million Landsat images. All USGS Landsat data are available at no cost via the Internet. The USGS is committed to improving the content of the historical Landsat archive though the consolidation of Landsat data held in international archives. In addition, the USGS is working on a strategy to develop higher-level Landsat geo- and biophysical datasets. Finally, Federal efforts are underway to transition Landsat into a sustained operational program within the Department of the Interior and to authorize the development of the next two satellites — Landsats 9 and 10.

Application of LANDSAT satellite imagery for iron ore prospecting in the Western Desert of Egypt

NASA Technical Reports Server (NTRS)

Elshazly, E. M.; Abdelhady, M. A.; Elghawaby, M. A.; Khawasik, S. M.

1977-01-01

Prospecting for iron ore occurrences was conducted by the Remote Sensing Center in Bahariya Oasis-El Faiyum area covering some 100,000 km squared in the Western Desert of Egypt. LANDSAT-1 satellite images were utilized as the main tool in the regional prospecting of the iron ores. The delineation of the geological units and geological structure through the interpretation of the images corroborated by field observations and structural analysis led to the discovery of new iron ore occurrences in the area of investigation.

Simulation of Image Performance Characteristics of the Landsat Data Continuity Mission (LDCM) Thermal Infrared Sensor (TIRS)

NASA Technical Reports Server (NTRS)

Schott, John; Gerace, Aaron; Brown, Scott; Gartley, Michael; Montanaro, Matthew; Reuter, Dennis C.

2012-01-01

The next Landsat satellite, which is scheduled for launch in early 2013, will carry two instruments: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). Significant design changes over previous Landsat instruments have been made to these sensors to potentially enhance the quality of Landsat image data. TIRS, which is the focus of this study, is a dual-band instrument that uses a push-broom style architecture to collect data. To help understand the impact of design trades during instrument build, an effort was initiated to model TIRS imagery. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool was used to produce synthetic "on-orbit" TIRS data with detailed radiometric, geometric, and digital image characteristics. This work presents several studies that used DIRSIG simulated TIRS data to test the impact of engineering performance data on image quality in an effort to determine if the image data meet specifications or, in the event that they do not, to determine if the resulting image data are still acceptable.

Calibrated Landsat ETM+ nonthermal-band image mosaics of Afghanistan

USGS Publications Warehouse

Davis, Philip A.

2006-01-01

In 2005, the U.S. Agency for International Development and the U.S. Trade and Development Agency contracted with the U.S. Geological Survey to perform assessments of the natural resources within Afghanistan. The assessments concentrate on the resources that are related to the economic development of that country. Therefore, assessments were initiated in oil and gas, coal, mineral resources, water resources, and earthquake hazards. All of these assessments require geologic, structural, and topographic information throughout the country at a finer scale and better accuracy than that provided by the existing maps, which were published in the 1970s by the Russians and Germans. The very rugged terrain in Afghanistan, the large scale of these assessments, and the terrorist threat in Afghanistan indicated that the best approach to provide the preliminary assessments was to use remotely sensed, satellite image data, although this may also apply to subsequent phases of the assessments. Therefore, the first step in the assessment process was to produce satellite image mosaics of Afghanistan that would be useful for these assessments. This report discusses the production and characteristics of the fundamental satellite image databases produced for these assessments, which are calibrated image mosaics of all six Landsat nonthermal (reflected) bands.

Landsat Celebrates 40 Years of Observing Earth

NASA Image and Video Library

2017-12-08

An artist's rendition of the next Landsat satellite, the Landsat Data Continuity Mission (LDCM) that will launch in Feb. 2013. Credit: NASA The Landsat program is the longest continuous global record of Earth observations from space – ever. Since its first satellite went up in the summer of 1972, Landsat has been looking at our planet. The view of Earth that this 40-year satellite program has recorded allows scientists to see, in ways they never imagined, how the Earth's surface has transformed, over time. In the 1970s Landsat captured the first views from space of the Amazonian rainforest and continued to track the area year after year after year, giving the world an unprecedented view of systemic and rapid deforestation. This view from space let us see an activity that was taking place in an exceptionally remote part of our world. These now iconic-images of tropical deforestation spurred the global environmental community to rally in an unprecedented way, and resulted in worldwide attention and action. To read more go to: www.nasa.gov/mission_pages/landsat/news/landsat-history.html NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Green leaf phenology at Landsat resolution: scaling from the plot to satellite

NASA Astrophysics Data System (ADS)

Fisher, J. I.; Mustard, J. F.; Vadeboncour, M.

2005-12-01

Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In particular, while most phenological patterns and trends derived from satellites appear realistic and coherent, they may not reflect spatial and temporal patterns at the plot level. An obvious explanation is the drastic scale difference from plot-level to most satellite observations. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r2 = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (<500 m). These dramatic gradients, of a similar magnitude to differences in leaf-onset from MD to MA, occur in of low-relief (<40 m) upland regions. The patterns suggest that microclimates resulting from springtime cold-air drainage may be influential in governing the start of leaf growth. These microclimates may be of crucial importance in interpreting in situ records and interpolating phenology from satellite data. Regional patterns from the Landsat analyses suggest topographic, coastal, and land-use controls on phenology. For example, our results indicate that deciduous forests

Radarsat Satellite Images: A New Geography Tool for Upper Elementary Classrooms.

ERIC Educational Resources Information Center

Kirman, Joseph M.

1999-01-01

Describes the Canadian Radarsat Satellite and remote sensing in order to demonstrate that teachers can incorporate this technology into the classroom. Maintains that third, fourth, fifth, and sixth grade students can understand and interpret remote sensing images and Landsat images. Provides a list of teaching resources other than the expensive…

Geometric accuracy of Landsat-4 and Landsat-5 Thematic Mapper images.

USGS Publications Warehouse

Borgeson, W.T.; Batson, R.M.; Kieffer, H.H.

1985-01-01

The geometric accuracy of the Landsat Thematic Mappers was assessed by a linear least-square comparison of the positions of conspicuous ground features in digital images with their geographic locations as determined from 1:24 000-scale maps. For a Landsat-5 image, the single-dimension standard deviations of the standard digital product, and of this image with additional linear corrections, are 11.2 and 10.3 m, respectively (0.4 pixel). An F-test showed that skew and affine distortion corrections are not significant. At this level of accuracy, the granularity of the digital image and the probable inaccuracy of the 1:24 000 maps began to affect the precision of the comparison. The tested image, even with a moderate accuracy loss in the digital-to-graphic conversion, meets National Horizontal Map Accuracy standards for scales of 1:100 000 and smaller. Two Landsat-4 images, obtained with the Multispectral Scanner on and off, and processed by an interim software system, contain significant skew and affine distortions. -Authors

Analysis On Land Cover In Municipality Of Malang With Landsat 8 Image Through Unsupervised Classification

NASA Astrophysics Data System (ADS)

Nahari, R. V.; Alfita, R.

2018-01-01

Remote sensing technology has been widely used in the geographic information system in order to obtain data more quickly, accurately and affordably. One of the advantages of using remote sensing imagery (satellite imagery) is to analyze land cover and land use. Satellite image data used in this study were images from the Landsat 8 satellite combined with the data from the Municipality of Malang government. The satellite image was taken in July 2016. Furthermore, the method used in this study was unsupervised classification. Based on the analysis towards the satellite images and field observations, 29% of the land in the Municipality of Malang was plantation, 22% of the area was rice field, 12% was residential area, 10% was land with shrubs, and the remaining 2% was water (lake/reservoir). The shortcoming of the methods was 25% of the land in the area was unidentified because it was covered by cloud. It is expected that future researchers involve cloud removal processing to minimize unidentified area.

An operational application of satellite snow cover observations, northwest United States. [using LANDSAT 1

NASA Technical Reports Server (NTRS)

Dillard, J. P.

1975-01-01

LANDSAT-1 imagery showing extent of snow cover was collected and is examined for the 1973 and 1974 snowmelt seasons for three Columbia River Basins. Snowlines were mapped and the aerial snow cover was determined using satellite data. Satellite snow mapping products were compared products from conventional information sources (computer programming and aerial photography was used). Available satellite data were successfully analyzed by radiance thresholding to determine snowlines and the attendant snow-covered area. Basin outline masks, contour elevation masks, and grid overlays were utilized as satellite data interpretation aids. Verification of the LANDSAT-1 data was generally good although there were exceptions. A major problem was lack of adequate cloud-free satellite imagery of high resolution and determining snowlines in forested areas.

Landsat View: Las Vegas, Nevada

NASA Image and Video Library

2017-12-08

Over the years of the Landsat program, the desert city of Las Vegas has gone through a massive growth spurt. The outward expansion of the city over the last quarter of a century is shown here with two false-color Landsat 5 images (August 3, 1984, and November 2, 2011). The dark purple grid of city streets and the green of irrigated vegetation grow out in every direction into the surrounding desert. These images were created using reflected light from the shortwave infrared, near-infrared, and green portions of the electromagnetic spectrum (Landsat 5 TM bands 7,4,2). ---- NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Satellite image maps of Pakistan

USGS Publications Warehouse

,

1997-01-01

Georeferenced Landsat satellite image maps of Pakistan are now being made available for purchase from the U.S. Geological Survey (USGS). The first maps to be released are a series of Multi-Spectral Scanner (MSS) color image maps compiled from Landsat scenes taken before 1979. The Pakistan image maps were originally developed by USGS as an aid for geologic and general terrain mapping in support of the Coal Resource Exploration and Development Program in Pakistan (COALREAP). COALREAP, a cooperative program between the USGS, the United States Agency for International Development, and the Geological Survey of Pakistan, was in effect from 1985 through 1994. The Pakistan MSS image maps (bands 1, 2, and 4) are available as a full-country mosaic of 72 Landsat scenes at a scale of 1:2,000,000, and in 7 regional sheets covering various portions of the entire country at a scale of 1:500,000. The scenes used to compile the maps were selected from imagery available at the Eros Data Center (EDC), Sioux Falls, S. Dak. Where possible, preference was given to cloud-free and snow-free scenes that displayed similar stages of seasonal vegetation development. The data for the MSS scenes were resampled from the original 80-meter resolution to 50-meter picture elements (pixels) and digitally transformed to a geometrically corrected Lambert conformal conic projection. The cubic convolution algorithm was used during rotation and resampling. The 50-meter pixel size allows for such data to be imaged at a scale of 1:250,000 without degradation; for cost and convenience considerations, however, the maps were printed at 1:500,000 scale. The seven regional sheets have been named according to the main province or area covered. The 50-meter data were averaged to 150-meter pixels to generate the country image on a single sheet at 1:2,000,000 scale

Long-Term Vegetation Trends Detected In Northern Canada Using Landsat Image Stacks

NASA Astrophysics Data System (ADS)

Fraser, R.; Olthof, I.; Carrière, M.; Deschamps, A.; Pouliot, D.

2011-12-01

Evidence of recent productivity increases in arctic vegetation comes from a variety of sources. At local scales, long-term plot measurements in North America are beginning to record increases in vascular plant cover and biomass. At landscape scales, expansion and densification of shrubs has been observed using repeat oblique photographs. Finally, continental-scale increases in vegetation "greenness" have been documented based on analysis of coarse resolution (≥ 1 km) NOAA-AVHRR satellite imagery. In this study we investigated intermediate, regional-level changes occurring in tundra vegetation since 1984 using the Landsat TM and ETM+ satellite image archive. Four study areas averaging 13,619 km2 were located over widely distributed national parks in northern Canada (Ivvavik, Sirmilik, Torngat Mountains, and Wapusk). Time-series image stacks of 16-41 growing-season Landsat scenes from overlapping WRS-2 frames were acquired spanning periods of 17-25 years. Each pixel's unique temporal database of clear-sky values was then analyzed for trends in four indices (NDVI, Tasseled Cap Brightness, Greenness and Wetness) using robust linear regression. The trends were further related to changes in the fractional cover of functional vegetation types using regression tree models trained with plot data and high resolution (≤ 10 m) satellite imagery. We found all four study areas to have a larger proportion of significant (p<0.05) positive greenness trends (range 6.1-25.5%) by comparison to negative trends (range 0.3-4.1%). For the three study areas where regression tree models could be derived, consistent trends of increasing shrub or vascular fractional cover and decreasing bare cover were predicted. The Landsat-based observations were associated with warming trends in each park over the analysis periods. Many of the major changes observed could be corroborated using published studies or field observations.

Training site statistics from Landsat and Seasat satellite imagery registered to a common map base

NASA Technical Reports Server (NTRS)

Clark, J.

1981-01-01

Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.

Assembly of Landsat's TIRS Instrument

NASA Image and Video Library

2012-02-14

Aleksandra Bogunovic (left) and Veronica Otero (right) look on while Pete Steigner (in the middle) adds a flow tube that will make sure that nitrogen gas flows through the instrument while it's being shipped. The gas will keep contaminating particles from infiltrating the instrument. The Thermal Infrared Sensor (TIRS) will fly on the next Landsat satellite, the Landsat Data Continuity Mission (LDCM). TIRS was built on an accelerated schedule at NASA's Goddard Space Flight Center, Greenbelt, Md. and will now be integrated into the LDCM spacecraft at Orbital Science Corp. in Gilbert, Ariz. The Landsat Program is a series of Earth observing satellite missions jointly managed by NASA and the U.S. Geological Survey. Landsat satellites have been consistently gathering data about our planet since 1972. They continue to improve and expand this unparalleled record of Earth's changing landscapes for the benefit of all. For more information on Landsat, visit: www.nasa.gov/landsat Credit: NASA/GSFC/Rebecca Roth NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Distributing FIA Information onto Segmented Landsat Thematic Mapper Images Stratified with Industrial Ground Data

Treesearch

Tripp Lowe; Chris Cieszewski; Michael Zasada; Jarek Zawadzki

2005-01-01

The ability to evaluate the ecological and economical effects of proposed modifications to Georgia's best management practices is an important issue in the State. We have incorporated tabular FIA data with Landsat Thematic Mapper satellite images and other spatial data to model Georgia's forested land and assess the area, volume, age, and site quality...

Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images

USGS Publications Warehouse

Chen, Xuexia; Vogelmann, James E.; Chander, Gyanesh; Ji, Lei; Tolk, Brian; Huang, Chengquan; Rollins, Matthew

2013-01-01

Routine acquisition of Landsat 5 Thematic Mapper (TM) data was discontinued recently and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) has an ongoing problem with the scan line corrector (SLC), thereby creating spatial gaps when covering images obtained during the process. Since temporal and spatial discontinuities of Landsat data are now imminent, it is therefore important to investigate other potential satellite data that can be used to replace Landsat data. We thus cross-compared two near-simultaneous images obtained from Landsat 5 TM and the Indian Remote Sensing (IRS)-P6 Advanced Wide Field Sensor (AWiFS), both captured on 29 May 2007 over Los Angeles, CA. TM and AWiFS reflectances were compared for the green, red, near-infrared (NIR), and shortwave infrared (SWIR) bands, as well as the normalized difference vegetation index (NDVI) based on manually selected polygons in homogeneous areas. All R2 values of linear regressions were found to be higher than 0.99. The temporally invariant cluster (TIC) method was used to calculate the NDVI correlation between the TM and AWiFS images. The NDVI regression line derived from selected polygons passed through several invariant cluster centres of the TIC density maps and demonstrated that both the scene-dependent polygon regression method and TIC method can generate accurate radiometric normalization. A scene-independent normalization method was also used to normalize the AWiFS data. Image agreement assessment demonstrated that the scene-dependent normalization using homogeneous polygons provided slightly higher accuracy values than those obtained by the scene-independent method. Finally, the non-normalized and relatively normalized ‘Landsat-like’ AWiFS 2007 images were integrated into 1984 to 2010 Landsat time-series stacks (LTSS) for disturbance detection using the Vegetation Change Tracker (VCT) model. Both scene-dependent and scene-independent normalized AWiFS data sets could generate disturbance maps similar to

SRTM Stereo Pair with Landsat Overlay: Miquelon and Saint Pierre Islands

NASA Image and Video Library

2000-10-20

This stereoscopic satellite image showing Miquelon and Saint Pierre Islands, located south of Newfoundland, Canada, was generated by draping NASA Landsat satellite image over a preliminary Shuttle Radar Topography Mission SRTM elevation model.

Landsat View: Tehran, Iran

NASA Image and Video Library

2017-12-08

Between 1985 and 2009, the population of Tehran, Iran, grew from six million to just over seven million. The city's growth was spurred largely by migration from other parts of the country. In addition to being the hub of government and associated public sector jobs, Tehran houses more than half of Iran's industry. Landsat 5 acquired these false-color images of Tehran on August 2, 1985, and July 19, 2009. The city is a web of dark purple lines, vegetation is green and bare ground is pink and tan. The images were created using both infrared and visible light (band combination 7, 4, and 2) to distinguish urban areas from the surrounding desert. ---- NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Landsat View: Istanbul, Turkey

NASA Image and Video Library

2017-12-08

Istanbul has been a bustling trade city for thousands of years. In this 1975 image, taken by Landsat, the city centers on the Golden Horn the estuary that flows into the Bosporus Straight at the center of the scene. Shown in false color, vegetation is red, urban areas are gray, and water appears black. A bridge built in 1973 to connect the Asian and European sides of Istanbul is barely visible. By 2011, Istanbul's population had exploded from 2 to 13 million people, and the city has gone through a dramatic expansion. This Landsat 5 image shows densely packed urban areas stretching along the Sea of Marmara and up the Bosporus Straight where a second bridge built in 1988 now crosses the water. ---- NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Landsat's Enduring Legacy: Pioneering Global Land Observations from Space

NASA Technical Reports Server (NTRS)

Goward, Samuel N.; Williams, Darerl L.; Arvidson, Terry; Rocchio, Laura E. P.; Irons, James R.; Russell, Carol A.; Johnston, Shaida S.

2017-01-01

It is our hope that the "Landsat Legacy" story will appeal to a broader audience than just those who use Landsat data on a regular basis. In an era when ready access to images and data from Earth-observing satellites is routine, it is hard to believe that only a few decades ago this was not the case. As the world's first digital land-observing satellite program, Landsat missions laid the foundation for modern space-based Earth observation and blazed the trail in the new field of quantitative remote sensing.

USGS Releases Landsat Orthorectified State Mosaics

USGS Publications Warehouse

,

2005-01-01

The U.S. Geological Survey (USGS) National Remote Sensing Data Archive, located at the USGS Center for Earth Resources Observation and Science (EROS) in Sioux Falls, South Dakota, maintains the Landsat orthorectified data archive. Within the archive are Landsat Enhanced Thematic Mapper Plus (ETM+) data that have been pansharpened and orthorectified by the Earth Satellite Corporation. This imagery has acquisition dates ranging from 1999 to 2001 and was created to provide users with access to quality-screened, high-resolution satellite images with global coverage over the Earth's landmasses.

LANDSAT language at our reach. First Swedish satellite. Civilization detectors

NASA Technical Reports Server (NTRS)

Wayne, D. L.; Bravo, V.

1981-01-01

Information on the use of LANDSAT data by Argentina is presented. Details on a Swedish satellite to be completed in 1984 and to be called VIKING are reported. Attempts to contact other civilizations in space by the use of radiotelescopes are discussed.

Synthetic aperture radar/LANDSAT MSS image registration

NASA Technical Reports Server (NTRS)

Maurer, H. E. (Editor); Oberholtzer, J. D. (Editor); Anuta, P. E. (Editor)

1979-01-01

Algorithms and procedures necessary to merge aircraft synthetic aperture radar (SAR) and LANDSAT multispectral scanner (MSS) imagery were determined. The design of a SAR/LANDSAT data merging system was developed. Aircraft SAR images were registered to the corresponding LANDSAT MSS scenes and were the subject of experimental investigations. Results indicate that the registration of SAR imagery with LANDSAT MSS imagery is feasible from a technical viewpoint, and useful from an information-content viewpoint.

Strait of Gibraltar, Perspective with Landsat Image Overlay

NASA Technical Reports Server (NTRS)

2003-01-01

This perspective view shows the Strait of Gibraltar, which is the entrance to the Mediterranean Sea from the Atlantic Ocean. Europe (Spain) is on the left. Africa (Morocco) is on the right. The Rock of Gibraltar, administered by Great Britain, is the peninsula in the back left.

The Strait of Gibraltar is the only natural gap in the topographic barriers that separate the Mediterranean Sea from the world's oceans. The Sea is about 3700 kilometers (2300 miles) long and covers about 2.5 million square kilometers (one million square miles), while the Strait is only about 13 kilometers (8 miles) wide. Sediment samples from the bottom of the Mediterranean Sea that include evaporite minerals, soils, and fossil plants show that about five million years ago the Strait was topographically blocked and the Sea had evaporated into a deep basin far lower in elevation than the oceans. Consequent changes in the world's hydrologic cycle, including effects upon ocean salinity, likely led to more ice formation in polar regions and more reflection of sunlight back to space, resulting in a cooler global climate at that time. Today, topography plays a key role in our regional climate patterns. But through Earth history, topographic change, even perhaps over areas as small as 13 kilometers across, has also affected the global climate.

This image was generated from a Landsat satellite image draped over an elevation model produced by the Shuttle Radar Topography Mission (SRTM). The view is eastward with a 3-times vertical exaggeration to enhance topographic expression. Natural colors of the scene (green vegetation, blue water, brown soil, white beaches) are enhanced by image processing, inclusion of some infrared reflectance (as green) to highlight the vegetation pattern, and inclusion of shading of the elevation model to further highlight the topographic features.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30

Analyzing remote sensing data in R: the landsat package

USDA-ARS?s Scientific Manuscript database

Research and development on atmospheric and topographic correction methods for multispectral satellite data such as Landsat images has far outpaced the availability of those methods in Geographic Information Systems software. As Landsat and other data become more widely available, demand for these i...

Mapping Antarctica using Landsat-8 - the preliminary results

NASA Astrophysics Data System (ADS)

Cheng, X.; Hui, F.; Qi, X.

2014-12-01

The first Landsat Image Mosaic of Antarctica (LIMA) was released in 2009, which was created by USGS, BAS, and NASA from more than 1,000 Landsat ETM+ scenes. As the first major scientific outcome of the IPY, LIMA supports current scientific polar research, encourages new projects, and helps the general public visualize Antarctica and changes happening to this southernmost environment. As the latest satellite of Landsat mission, the Landsat-8 images the entire Earth every 16 days in an 8-day offset from Landsat-7. Data collected by the instruments onboard the satellite are available to download at no charge within 24 hours of reception. The standard Landsat 8 products provided by the USGS EROS Center consist of quantized and calibrated scaled Digital Numbers (DN) in 16-bit unsigned integer format and can be rescaled to the Top Of Atmosphere (TOA) reflectance and/or radiance. With the support of USGS portal, we searched and downloaded more than 1600 scenes of Level 1 T- Terrain Corrected Landsat 8 image products covering Antarctica from late 2013 to early 2014. These data were converted to planetary radiance for further processing. Since the distribution of clouds in these images are random and much complicated, statistics on the distribution of clouds were performed and then help to decide masking those thicker cloud to keep more useful information left and avoid observation holes. A preliminary result of the Landsat-8 mosaic of Antarctica under the joint efforts of Beijing Normal University, NSIDC and University of Maryland will be released on this AGU fall meeting. Comparison between Landsat 7 and 8 mosaic products will also be done to find the difference or advantage of the two products.

Delineation of a Re-establishing Drainage Network Using SPOT and Landsat Images

NASA Astrophysics Data System (ADS)

Bailey, J. E.; Self, S.; Mouginis-Mark, P. J.

2008-12-01

The 1991 eruption of Mt. Pinatubo, The Philippines, provided a unique opportunity to study the effects on the landscape of a large eruption in part because it took place after the advent of regular satellite-based observations. The eruption formed one large (>100km2) ignimbrite sheet, with over 70% of the total deposit deposited in three primary drainage basins to the west of the volcano. High-resolution (20 m/pixel) satellite images, showing the western drainage basins and surrounding region both before and after the eruption were used to observe the re-establishment and evolution of drainage networks on the newly emplaced ignimbrite sheet. Changes in the drainage networks were delineated from a time series of SPOT (Satellite Pour l'Observation de la Terre) and Landsat multi-spectral satellite images. The analysis of which was supplemented by ground- based observations. The satellite images showed that the blue prints for the new drainage systems were established early (within days of the eruption) and at a large-scale followed the pre-eruption pattern. However, the images also illustrated the ephemeral nature of many channels due to the influence of secondary pyroclastic flows, lahar- dammed lake breakouts, stream piracy and shifts due to erosion. Characteristics of the defined drainage networks were used to infer the relative influence on the lahar hazard within each drainage basin.

Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data

USGS Publications Warehouse

Krizanich, Gary; Finn, Michael P.

2009-01-01

Water quality of Table Rock Lake in southwestern Missouri is assessed using Landsat Thematic Mapper satellite data. A pilot study uses multidate satellite image scenes in conjunction with physical measurements of secchi disk transparency collected by the Lakes of Missouri Volunteer Program to construct a regression model used to estimate water clarity. The natural log of secchi disk transparency is the dependent variable in the regression and the independent variables are Thematic Mapper band 1 (blue) reflectance and a ratio of the band 1 and band 3 (red) reflectance. The regression model can be used to reliably predict water clarity anywhere within the lake. A pixel-level lake map of predicted water clarity or computed trophic state can be produced from the model output. Information derived from this model can be used by water-resource managers to assess water quality and evaluate effects of changes in the watershed on water quality.

Assembly of Landsat's TIRS Instrument

NASA Image and Video Library

2017-12-08

Pete Steigner, and Mike Golob (middle and right) assist an Chris Kolos in carefully moving a TIRS component across the clean room at Goddard. On the far right Robin Knight holds the component's 'grounding strap.' It's used to make sure that any static electricity that could possibly build up while the component is being moved doesn't affect the damage the sensitive electronics. The Thermal Infrared Sensor (TIRS) will fly on the next Landsat satellite, the Landsat Data Continuity Mission (LDCM). TIRS was built on an accelerated schedule at NASA's Goddard Space Flight Center, Greenbelt, Md. and will now be integrated into the LDCM spacecraft at Orbital Science Corp. in Gilbert, Ariz. The Landsat Program is a series of Earth observing satellite missions jointly managed by NASA and the U.S. Geological Survey. Landsat satellites have been consistently gathering data about our planet since 1972. They continue to improve and expand this unparalleled record of Earth's changing landscapes for the benefit of all. For more information on Landsat, visit: www.nasa.gov/landsat Credit: NASA/GSFC/Rebecca Roth NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Observation of coral reefs on Ishigaki Island, Japan, using Landsat TM images and aerial photographs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matsunaga, Tsuneo; Kayanne, Hajime

1997-06-01

Ishigaki Island is located at the southwestern end of Japanese Islands and famous for its fringing coral reefs. More than twenty LANDSAT TM images in twelve years and aerial photographs taken on 1977 and 1994 were used to survey two shallow reefs on this island, Shiraho and Kabira. Intensive field surveys were also conducted in 1995. All satellite images of Shiraho were geometrically corrected and overlaid to construct a multi-date satellite data set. The effects of solar elevation and tide on satellite imagery were studied with this data set. The comparison of aerial and satellite images indicated that significant changesmore » occurred between 1977 and 1984 in Kabira: rapid formation in the western part and decrease in the eastern part of dark patches. The field surveys revealed that newly formed dark patches in the west contain young corals. These results suggest that remote sensing is useful for not only mapping but also monitoring of shallow coral reefs.« less

Visualizing Airborne and Satellite Imagery

NASA Technical Reports Server (NTRS)

Bierwirth, Victoria A.

2011-01-01

Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

Landsat View: Tokyo, Japan

NASA Image and Video Library

2017-12-08

Tokyo is the world’s largest metropolitan region, home to nearly 37 million people. During the past two decades, Tokyo’s population has grown by more than 7 million. The city’s growth has continued despite Japan’s overall stagnating population, mainly due to a continued trend of centralization—citizens moving out of the country and into the city. Landsat 4 collected this first false-color image of Tokyo on Feb. 2, 1989. The upper half of Tokyo Bay is the large water body visible in a dark blue. In the middle of the image, central Tokyo appears a deep purple just north of the bay. Twenty-two years later, Landsat 5, captured this second image of Tokyo on April 5, 2011. The urban reaches of metropolitan Tokyo have grown in both distance and density, as seen where the green color of vegetation has turned to pink and purple shades of urbanization. A major expansion of Tokyo’s Haneda Airport, can be seen south of the city, on land built out into the bay. The constant circular spot of green in the dense city-center, visible on both images, is the Tokyo Imperial Palace and its gardens. (Landsat 5 TM Bands 7,4,2) ---- NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing

Landsat Thematic Mapper Image Mosaic of Colorado

USGS Publications Warehouse

Cole, Christopher J.; Noble, Suzanne M.; Blauer, Steven L.; Friesen, Beverly A.; Bauer, Mark A.

2010-01-01

The U.S. Geological Survey (USGS) Rocky Mountain Geographic Science Center (RMGSC) produced a seamless, cloud-minimized remotely-sensed image spanning the State of Colorado. Multiple orthorectified Landsat 5 Thematic Mapper (TM) scenes collected during 2006-2008 were spectrally normalized via reflectance transformation and linear regression based upon pseudo-invariant features (PIFS) following the removal of clouds. Individual Landsat scenes were then mosaicked to form a six-band image composite spanning the visible to shortwave infrared spectrum. This image mosaic, presented here, will also be used to create a conifer health classification for Colorado in Scientific Investigations Map 3103. An archive of past and current Landsat imagery exists and is available to the scientific community (http://glovis.usgs.gov/), but significant pre-processing was required to produce a statewide mosaic from this information. Much of the data contained perennial cloud cover that complicated analysis and classification efforts. Existing Landsat mosaic products, typically three band image composites, did not include the full suite of multispectral information necessary to produce this assessment, and were derived using data collected in 2001 or earlier. A six-band image mosaic covering Colorado was produced. This mosaic includes blue (band 1), green (band 2), red (band 3), near infrared (band 4), and shortwave infrared information (bands 5 and 7). The image composite shown here displays three of the Landsat bands (7, 4, and 2), which are sensitive to the shortwave infrared, near infrared, and green ranges of the electromagnetic spectrum. Vegetation appears green in this image, while water looks black, and unforested areas appear pink. The lines that may be visible in the on-screen version of the PDF are an artifact of the export methods used to create this file. The file should be viewed at 150 percent zoom or greater for optimum viewing.

Cross-calibration of the Landsat-7 ETM+ and Landsat-5 TM with the ResourceSat-1 (IRS-P6) AWiFS and LISS-III sensors

USGS Publications Warehouse

Chander, G.; Scaramuzza, P.L.

2006-01-01

Increasingly, data from multiple sensors are used to gain a more complete understanding of land surface processes at a variety of scales. The Landsat suite of satellites has collected the longest continuous archive of multispectral data. The ResourceSat-1 Satellite (also called as IRS-P6) was launched into the polar sunsynchronous orbit on Oct 17, 2003. It carries three remote sensing sensors: the High Resolution Linear Imaging Self-Scanner (LISS-IV), Medium Resolution Linear Imaging Self-Scanner (LISS-III), and the Advanced Wide Field Sensor (AWiFS). These three sensors are used together to provide images with different resolution and coverage. To understand the absolute radiometric calibration accuracy of IRS-P6 AWiFS and LISS-III sensors, image pairs from these sensors were compared to the Landsat-5 TM and Landsat-7 ETM+ sensors. The approach involved the calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors.

Rock type discrimination techniques using Landsat and Seasat image data

NASA Technical Reports Server (NTRS)

Blom, R.; Abrams, M.; Conrad, C.

1981-01-01

Results of a sedimentary rock type discrimination project using Seasat radar and Landsat multispectral image data of the San Rafael Swell, in eastern Utah, are presented, which has the goal of determining the potential contribution of radar image data to Landsat image data for rock type discrimination, particularly when the images are coregistered. The procedure employs several images processing techniques using the Landsat and Seasat data independently, and then both data sets are coregistered. The images are evaluated according to the ease with which contacts can be located and rock units (not just stratigraphically adjacent ones) separated. Results show that of the Landsat images evaluated, the image using a supervised classification scheme is the best for sedimentary rock type discrimination. Of less value, in decreasing order, are color ratio composites, principal components, and the standard color composite. In addition, for rock type discrimination, the black and white Seasat image is less useful than any of the Landsat color images by itself. However, it is found that the incorporation of the surface textural measures made from the Seasat image provides a considerable and worthwhile improvement in rock type discrimination.

Landsat View: Pearl River Delta, China

NASA Image and Video Library

2017-12-08

In 1979, China established two special economic zones around the Pearl River Delta, north of Hong Kong. This image, taken by Landsat 3 on October 19, 1973, shows that the region was rural when the zone was established. Plant-covered land, which is red in this false-color image, dominates the scene. Square grids are agriculture. By January 10, 2003, when Landsat 7 took this image, the Pearl River Delta was a densely populated urban corridor with several large cities. The urban areas are gray in this image. The region is a major manufacturing center with an economy the size of Taiwan’s. As of 2010, the Pearl River Economic Zone had a population of 36 million people. ---- NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

NASA Astrophysics Data System (ADS)

Song, Huihui

Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat

Landsat's international partners

USGS Publications Warehouse

Byrnes, Raymond A.

2012-01-01

Since the launch of the first Landsat satellite 40 years ago, International Cooperators (ICs) have formed a key strategic alliance with the U.S. Geological Survey (USGS) to not only engage in Landsat data downlink services but also to enable a foundation for scientific and technical collaboration. The map below shows the locations of all ground stations operated by the United States and IC ground station network for the direct downlink and distribution of Landsat 5 (L5) and Landsat 7 (L7) image data. The circles show the approximate area over which each station has the capability for direct reception of Landsat data. The red circles show the components of the L5 ground station network, the green circles show components of the L7 station network, and the dashed circles show stations with dual (L5 and L7) status. The yellow circles show L5 short-term ("campaign") stations that contribute to the USGS Landsat archive. Ground stations in South Dakota and Australia currently serve as the primary data capture facilities for the USGS Landsat Ground Network (LGN). The Landsat Ground Station (LGS) is located at the USGS Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The Alice Springs (ASN) ground station is located at the Geoscience Australia facility in Alice Springs, Australia. These sites receive the image data, via X-band Radio Frequency (RF) link, and the spacecraft housekeeping data, via S-band RF link. LGS also provides tracking services and a command link to the spacecrafts.

Get Close to Glaciers with Satellite Imagery.

ERIC Educational Resources Information Center

Hall, Dorothy K.

1986-01-01

Discusses the use of remote sensing from satellites to monitor glaciers. Discusses efforts to use remote sensing satellites of the Landsat series for examining the global distribution, mass, balance, movements, and dynamics of the world's glaciers. Includes several Landsat images of various glaciers. (TW)

Effects of Spectral Band Differences between Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI)

NASA Astrophysics Data System (ADS)

Micijevic, E.; Haque, M. O.

2015-12-01

In satellite remote sensing, Landsat sensors are recognized for providing well calibrated satellite images for over four decades. This image data set provides an important contribution to detection and temporal analysis of land changes. Landsat 8 (L8), the latest satellite of the Landsat series, was designed to continue its legacy as well as to embrace advanced technology and satisfy the demand of the broader scientific community. Sentinel 2A (S2A), a European satellite launched in June 2015, is designed to keep data continuity of Landsat and SPOT like satellites. The S2A MSI sensor is equipped with spectral bands similar to L8 OLI and includes some additional ones. Compared to L8 OLI, green and near infrared MSI bands have narrower bandwidths, whereas coastal-aerosol (CA) and cirrus have larger bandwidths. The blue and red MSI bands cover higher wavelengths than the matching OLI bands. Although the spectral band differences are not large, their combination with the spectral signature of a studied target can largely affect the Top Of Atmosphere (TOA) reflectance seen by the sensors. This study investigates the effect of spectral band differences between S2A MSI and L8 OLI sensors. The differences in spectral bands between sensors can be assessed by calculating Spectral Band Adjustment Factors (SBAF). For radiometric calibration purposes, the SBAFs for the calibration test site are used to bring the two sensors to the same radiometric scale. However, the SBAFs are target dependent and different sensors calibrated to the same radiometric scale will (correctly!) measure different reflectance for the same target. Thus, when multiple sensors are used to study a given target, the sensor responses need to be adjusted using SBAFs specific to that target. Comparison of the SBAFs for S2A MSI and L8 OLI based on various vegetation spectral profiles revealed variations in radiometric responses as high as 15%. Depending on target under study, these differences could be even

Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale.

PubMed

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to enable temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat assessment at regional scale. For the former, we adapt a previously developed approach for Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution that allows automatic mapping of winter crops taking into account knowledge on crop calendar and without ground truth data. For the latter, we use a generalized winter wheat yield model that is based on NDVI-peak estimation and MODIS data, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A has a positive impact both for winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times comparing to the single satellite usage.

The Black Sea coastal zone in the high resolution satellite images

NASA Astrophysics Data System (ADS)

Yurovskaya, Maria; Dulov, Vladimir; Kozlov, Igor

2016-04-01

Landsat data with spatial resolution of 30-100 m provide the ability of regular monitoring of ocean phenomena with scale of 100-1000 m. Sentinel-1 is equipped with C-band synthetic aperture radar. The images allow recognizing the features that affect either the sea surface roughness, or its color characteristics. The possibilities of using the high spatial resolution satellite data are considered for observation and monitoring of Crimean coastal zone. The analyzed database includes all Landsat-8 (Level 1) multi-channel images from January 2013 to August 2015 and all Sentinel-1 radar images in May-August 2015. The goal of the study is to characterize the descriptiveness of these data for research and monitoring of the Crimean coastal areas. The observed marine effects are reviewed and the physical mechanisms of their signatures in the satellite images are described. The effects associated with the roughness variability are usually manifested in all bands, while the subsurface phenomena are visible only in optical data. Confidently observed structures include internal wave trains, filamentous natural slicks, which reflect the eddy coastal dynamics, traces of moving ships and the oil films referred to anthropogenic pollution of marine environment. The temperature fronts in calm conditions occur due to surfactant accumulation in convergence zone. The features in roughness field can also be manifested in Sentinel-1 data. Subsurface processes observed in Landsat-8 images primarily include transport and distribution of suspended matter as a result of floods and sandy beach erosion. The surfactant always concentrates on the sea surface in contaminated areas, so that these events are also observed in Sentinel-1 images. A search of wastewater discharge manifestations is performed. The investigation provides the basis for further development of approaches to obtain quantitative characteristics of the phenomena themselves. Funding by Russian Science Foundation under grant 15

The global Landsat archive: Status, consolidation, and direction

USGS Publications Warehouse

Wulder, Michael A.; White, Joanne C.; Loveland, Thomas; Woodcock, Curtis; Belward, Alan; Cohen, Warren B.; Fosnight, Eugene A.; Shaw, Jerad; Masek, Jeffery G.; Roy, David P.

2016-01-01

New and previously unimaginable Landsat applications have been fostered by a policy change in 2008 that made analysis-ready Landsat data free and open access. Since 1972, Landsat has been collecting images of the Earth, with the early years of the program constrained by onboard satellite and ground systems, as well as limitations across the range of required computing, networking, and storage capabilities. Rather than robust on-satellite storage for transmission via high bandwidth downlink to a centralized storage and distribution facility as with Landsat-8, a network of receiving stations, one operated by the U.S. government, the other operated by a community of International Cooperators (ICs), were utilized. ICs paid a fee for the right to receive and distribute Landsat data and over time, more Landsat data was held outside the archive of the United State Geological Survey (USGS) than was held inside, much of it unique. Recognizing the critical value of these data, the USGS began a Landsat Global Archive Consolidation (LGAC) initiative in 2010 to bring these data into a single, universally accessible, centralized global archive, housed at the Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The primary LGAC goals are to inventory the data held by ICs, acquire the data, and ingest and apply standard ground station processing to generate an L1T analysis-ready product. As of January 1, 2015 there were 5,532,454 images in the USGS archive. LGAC has contributed approximately 3.2 million of those images, more than doubling the original USGS archive holdings. Moreover, an additional 2.3 million images have been identified to date through the LGAC initiative and are in the process of being added to the archive. The impact of LGAC is significant and, in terms of images in the collection, analogous to that of having had twoadditional Landsat-5 missions. As a result of LGAC, there are regions of the globe that now have markedly improved

Concepts for on-board satellite image registration. Volume 2: IAS prototype performance evaluation standard definition

NASA Astrophysics Data System (ADS)

Daluge, D. R.; Ruedger, W. H.

1981-06-01

Problems encountered in testing onboard signal processing hardware designed to achieve radiometric and geometric correction of satellite imaging data are considered. These include obtaining representative image and ancillary data for simulation and the transfer and storage of a large quantity of image data at very high speed. The high resolution, high speed preprocessing of LANDSAT-D imagery is considered.

Mapping land cover from satellite images: A basic, low cost approach

NASA Technical Reports Server (NTRS)

Elifrits, C. D.; Barney, T. W.; Barr, D. J.; Johannsen, C. J.

1978-01-01

Simple, inexpensive methodologies developed for mapping general land cover and land use categories from LANDSAT images are reported. One methodology, a stepwise, interpretive, direct tracing technique was developed through working with university students from different disciplines with no previous experience in satellite image interpretation. The technique results in maps that are very accurate in relation to actual land cover and relative to the small investment in skill, time, and money needed to produce the products.

Landsat: Sustaining earth observations beyond Landsat 8

USGS Publications Warehouse

Kelly, Francis P.; Holm, Thomas M.

2014-01-01

The Landsat series of Earth-observing satellites began 41-years ago as a partnership between the U.S. Geological Survey (USGS) of the Department of the Interior (DOI) and The National Aeronautics and Space Administration (NASA). For the past 41 years, Landsat satellites and associated U.S. Government ground processing, distribution, and archiving systems have acquired and made available global, moderate-resolution, multispectral measurements of land and coastal regions, providing humankind’s longest record of our planet from space. Landsat information is truly a national asset, providing an important and unique capability that benefits abroad community, including Federal, state, and local governments; globalchange science; academia, and the private sector.

Cape Town, South Africa, Perspective View, Landsat Image over SRTM Elevation

NASA Technical Reports Server (NTRS)

2004-01-01

Cape Town and the Cape of Good Hope, South Africa, appear in the foreground of this perspective view generated from a Landsat satellite image and elevation data from the Shuttle Radar Topography Mission (SRTM). The city center is located at Table Bay (at the lower left), adjacent to Table Mountain, a 1,086-meter (3,563-foot) tall sandstone and granite natural landmark.

Cape Town enjoys a Mediterranean climate but must deal with the limited water supply characteristic of that climate. Until the 1890s the city relied upon streams and springs along the base of Table Mountain, then built a small reservoir atop Table Mountain to capture and store rainfall there. Now the needs of a much larger population are met in part by much larger reservoirs such as seen here far inland (mid-distance left) at the Theewaterskloof Dam.

False Bay is the large bay to the south (right) of Cape Town, just around the Cape of Good Hope. It is one of the largest bays along the entire South African coast, but nearby Cape Town has its harbor at Table Bay. False Bay got its name because mariners approaching Cape Town from the east would see the prominent bay and falsely assume it to be the entrance to Cape Town harbor. Similarly, people often mistake the Cape of Good Hope as the southernmost point of Africa. But the southernmost point is actually Cape Agulhas, located just to the southeast (upper right) of this scene.

This Landsat and SRTM perspective view uses a 2-times vertical exaggeration to enhance topographic expression. The back edges of the data sets form a false horizon and a false sky was added. Colors of the scene were enhanced by image processing but are the natural color band combination from the Landsat satellite.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar

An operational earth resources satellite system: The LANDSAT follow-on program

NASA Technical Reports Server (NTRS)

Stroud, W. G.

1977-01-01

The LANDSATS 1 and 2 have demonstrated the role of remote sensing from satellite in research, development, and operational activities essential to the better management of our resources. Hundreds of agricultural, geological, hydrological, urban land use, and other investigations have raised the question of the development of an operational system providing continuous, timely data. The LANDSAT Follow-on Study addressed the economics, technological performance, and design of a system in transition from R and D to operations. Economic benefits were identified; and a complete system from sensors to the ultilization in forecasting crop production, oil and mineral exploration, and water resources management was designed.

Landsat View: Ontario, California

NASA Image and Video Library

2017-12-08

Thirty-five miles due east of downtown Los Angeles lies the city of Ontario, California. In 1881 two Canadian brothers established the town, naming it after their native city. By 1891 Ontario, Calif., was incorporated as a city. The farming-based economy (olives, citrus, dairy) of the city helped it grow to 20,000 by the 1960s. Subsequently, warehousing and freight trafficking took over as the major industry and the city’s population was over 160,000 by 2010. The L.A./Ontario International Airport is now America’s 15th busiest cargo airport. In these natural color Landsat 5 images, the massive growth of the city between 1985 and 2010 can be seen. The airport, found in the southwest portion of the images, added a number of runways and large warehousing structures now dominate the once rural areas surrounding the airport. In these images vegetation is green and brown and urban structures are bright white and gray. (Note there is a large dry riverbed in the northeast corner that is also bright white, but its nonlinear appearance sets it apart visually). ---- NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission

Estimating seasonal evapotranspiration from temporal satellite images

USGS Publications Warehouse

Singh, Ramesh K.; Liu, Shu-Guang; Tieszen, Larry L.; Suyker, Andrew E.; Verma, Shashi B.

2012-01-01

Estimating seasonal evapotranspiration (ET) has many applications in water resources planning and management, including hydrological and ecological modeling. Availability of satellite remote sensing images is limited due to repeat cycle of satellite or cloud cover. This study was conducted to determine the suitability of different methods namely cubic spline, fixed, and linear for estimating seasonal ET from temporal remotely sensed images. Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model in conjunction with the wet METRIC (wMETRIC), a modified version of the METRIC model, was used to estimate ET on the days of satellite overpass using eight Landsat images during the 2001 crop growing season in Midwest USA. The model-estimated daily ET was in good agreement (R2 = 0.91) with the eddy covariance tower-measured daily ET. The standard error of daily ET was 0.6 mm (20%) at three validation sites in Nebraska, USA. There was no statistically significant difference (P > 0.05) among the cubic spline, fixed, and linear methods for computing seasonal (July–December) ET from temporal ET estimates. Overall, the cubic spline resulted in the lowest standard error of 6 mm (1.67%) for seasonal ET. However, further testing of this method for multiple years is necessary to determine its suitability.

Users and uses of Landsat 8 satellite imagery—2014 survey results

USGS Publications Warehouse

Miller, Holly M.

2016-04-18

To explore the effect of the availability of Landsat 8 imagery on Landsat imagery use in general, established users (those who had consistently used Landsat imagery both before and after Landsat 8 imagery became available) using Landsat 8 imagery were asked about changes in the amount of Landsat imagery they used. The majority of established users using Landsat 8 imagery (60 percent) reported an average increase of 51 percent in the number of scenes obtained after Landsat 8 imagery became available. Landsat 8 users were asked if they had encountered challenges in using Landsat 8 whereas non-Landsat 8 users were asked if such challenges had played a role in why they were not using Landsat 8 imagery. Although many users did not encounter challenges when using or trying to use Landsat 8 data, slightly less than 30 percent did encounter issues with processing the data to a usable point. The most common issue reported was not being able to create or have access to a surface reflectance corrected product. Other challenges were related to the file sizes of images being too large to download, store, or analyze. There were no statistically significant differences between Landsat 8 and non-Landsat 8 users in terms of challenges encountered when using or trying to use the imagery, which indicates that users were not unduly discouraged by the challenges they may have encountered. When asked about potential consequences of not using Landsat 8, more than half of the non-Landsat 8 users did not report detrimental effects on their work from not using the imagery. Of those who did report detrimental effects, decreased quality of work, decreased scope of work, and increased time spent on work were the most common.   

Mount Ararat, Turkey, Perspective with Landsat Image Overlay

NASA Technical Reports Server (NTRS)

2004-01-01

This perspective view shows Mount Ararat in easternmost Turkey, which has been the site of several searches for the remains of Noah's Ark. The main peak, known as Great Ararat, is the tallest peak in Turkey, rising to 5165 meters (16,945 feet). This southerly, near horizontal view additionally shows the distinctly conically shaped peak known as 'Little Ararat' on the left. Both peaks are volcanoes that are geologically young, but activity during historic times is uncertain.

This image was generated from a Landsat satellite image draped over an elevation model produced by the Shuttle Radar Topography Mission (SRTM). The view uses a 1.25-times vertical exaggeration to enhance topographic expression. Natural colors of the scene are enhanced by image processing, inclusion of some infrared reflectance (as green) to highlight the vegetation pattern, and inclusion of shading of the elevation model to further highlight the topographic features.

Volcanoes pose hazards for people, the most obvious being the threat of eruption. But other hazards are associated with volcanoes too. In 1840 an earthquake shook the Mount Ararat region, causing an unstable part of mountain's north slope to tumble into and destroy a village. Visualizations of satellite imagery when combined with elevation models can be used to reveal such hazards leading to disaster prevention through improved land use planning.

But the hazards of volcanoes are balanced in part by the benefits they provide. Over geologic time volcanic materials break down to form fertile soils. Cultivation of these soils has fostered and sustained civilizations, as has occurred in the Mount Ararat region. Likewise, tall volcanic peaks often catch precipitation, providing a water supply to those civilizations. Mount Ararat hosts an icefield and set of glaciers, as seen here in this late summer scene, that are part of this beneficial natural process

Elevation data used in this image was acquired by the Shuttle Radar

LANDSAT-4 multispectral scanner (MSS) subsystem radiometric characterization

NASA Technical Reports Server (NTRS)

Alford, W. (Editor); Barker, J. (Editor); Clark, B. P.; Dasgupta, R.

1983-01-01

The multispectral band scanner (mass) and its spectral characteristics are described and methods are given for relating video digital levels on computer compatible tapes to radiance into the sensor. Topics covered include prelaunch calibration procedures and postlaunch radiometric processng. Examples of current data resident on the MSS image processing system are included. The MSS on LANDSAT 4 is compared with the scanners on earlier LANDSAT satellites.

A Photo Album of Earth Scheduling Landsat 7 Mission Daily Activities

NASA Technical Reports Server (NTRS)

Potter, William; Gasch, John; Bauer, Cynthia

1998-01-01

Landsat7 is a member of a new generation of Earth observation satellites. Landsat7 will carry on the mission of the aging Landsat 5 spacecraft by acquiring high resolution, multi-spectral images of the Earth surface for strategic, environmental, commercial, agricultural and civil analysis and research. One of the primary mission goals of Landsat7 is to accumulate and seasonally refresh an archive of global images with full coverage of Earth's landmass, less the central portion of Antarctica. This archive will enable further research into seasonal, annual and long-range trending analysis in such diverse research areas as crop yields, deforestation, population growth, and pollution control, to name just a few. A secondary goal of Landsat7 is to fulfill imaging requests from our international partners in the mission. Landsat7 will transmit raw image data from the spacecraft to 25 ground stations in 20 subscribing countries. Whereas earlier Landsat missions were scheduled manually (as are the majority of current low-orbit satellite missions), the task of manually planning and scheduling Landsat7 mission activities would be overwhelmingly complex when considering the large volume of image requests, the limited resources available, spacecraft instrument limitations, and the limited ground image processing capacity, not to mention avoidance of foul weather systems. The Landsat7 Mission Operation Center (MOC) includes an image scheduler subsystem that is designed to automate the majority of mission planning and scheduling, including selection of the images to be acquired, managing the recording and playback of the images by the spacecraft, scheduling ground station contacts for downlink of images, and generating the spacecraft commands for controlling the imager, recorder, transmitters and antennas. The image scheduler subsystem autonomously generates 90% of the spacecraft commanding with minimal manual intervention. The image scheduler produces a conflict-free schedule

Ice Sheet Change Detection by Satellite Image Differencing

NASA Technical Reports Server (NTRS)

Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

2010-01-01

Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale

PubMed Central

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2018-01-01

Timely and accurate information on crop yield is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to enable temporal resolution of an image every 3–5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat assessment at regional scale. For the former, we adapt a previously developed approach for Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution that allows automatic mapping of winter crops taking into account knowledge on crop calendar and without ground truth data. For the latter, we use a generalized winter wheat yield model that is based on NDVI-peak estimation and MODIS data, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A has a positive impact both for winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times comparing to the single satellite usage. PMID:29888751

Landsat at 45: How it Changed the Way We See the Earth

NASA Technical Reports Server (NTRS)

Uri, John

2017-01-01

On October 24, 1946, more than 10 years before the launch of the first artificial satellite Sputnik, scientists at the White Sands Missile Range in New Mexico placed a camera on top of a captured German V-2 ballistic missile. As the rocket flew to an altitude of about 65 miles - just above the generally recognized border of outer space - the 35-millimeter motion picture camera snapped a frame every one and a half seconds. Minutes later, the missile came crashing back down and slammed into the ground at more than 340 mph, but the film survived and gave us our first glimpse of Earth from space. Earth Resources Technology Satellite aka Landsat It was images like those first grainy black and white pictures and later those taken by America's first astronauts in the 1960's that inspired the development of the Earth Resources Technology Satellite (ERTS). From the unique vantage point of space, we could now observe Earth using a variety of different instruments to monitor changes over time. The ERTS-1 satellite, wisely renamed Landsat-1, was launched aboard a Delta rocket on July 23, 1972, into a Sun-synchronous polar orbit at an altitude of about 560 miles. In this unique orbit, Landsat could observe the same point on the Earth every 18 days, always with the same solar illumination, allowing for precise monitoring of changes on the ground over time. Landsat-1, derived from the highly successful Nimbus weather satellites, carried two instruments that allowed it to take images not only in visible light but also in infrared, well-suited to track changes in vegetation over time. Designed to last only one year, Landsat-1 actually operated for nearly three years, by which time it had been joined in space by Landsat-2, a near identical copy of the original. Since then, ever more sophisticated instruments were flown aboard Landsat-3 through -8, with Landsat-9 planned for launch in 2020, acquiring millions of images of Earth over more than four decades. At first, images from

Landsat Science: 40 Years of Innovation and Opportunity

NASA Technical Reports Server (NTRS)

Cook, Bruce D.; Irons, James R.; Masek, Jeffrey G.; Loveland, Thomas R.

2012-01-01

Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.

Perspective View with Landsat Overlay, Costa Rica

NASA Technical Reports Server (NTRS)

2002-01-01

This perspective view shows the Caribbean coastal plain of Costa Rica, with the Cordillera Central rising in the background and the Pacific Ocean in the distance. The prominent river in the center of the image is the Rio Sucio, which merges with the Rio Sarapiqui at the bottom of the image and eventually joins with Rio San Juan on the Nicaragua border.

Like much of Central America, Costa Rica is generally cloud covered so very little satellite imagery is available. The ability of the Shuttle Radar Topography Mission (SRTM) instrument to penetrate clouds and make three-dimensional measurements will allow generation of the first complete high-resolution topographic map of the entire region. These data were used to generate the image.

This three-dimensional perspective view was generated using elevation data from SRTM and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated two times.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, S.D.

Elevation data used in this image was acquired by the SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and

Landsat eyes help guard the world's forests

USGS Publications Warehouse

Campbell, Jon

2017-03-03

SummaryThe Landsat program is a joint effort between the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), but the partner agencies have distinct roles. NASA develops remote-sensing instruments and spacecraft, launches satellites, and validates their performance in orbit. The USGS owns and operates Landsat satellites in space and manages their data transmissions, including ground reception, archiving, product generation, and public distribution. In 2008, with support from the U.S. Department of the Interior, the USGS made its Landsat data free to anyone in the world.The current satellites in the Landsat program, Landsat 7 (launched in 1999) and Landsat 8 (launched in 2013), provide complete coverage of the Earth every eight days. A Landsat 9 satellite is scheduled for launch in late 2020.

75 FR 39701 - Revision of a Currently Approved Collection: Users, Uses, and Benefits of Landsat Satellite Imagery

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-12

.... Abstract In 2008, the USGS's Land Remote Sensing (LRS) Program initiated a study to determine the users, uses, and benefits of Landsat imagery. Before that study, there had been very limited assessments of...: Users, Uses, and Benefits of Landsat Satellite Imagery AGENCY: United States Geological Survey (USGS...

Landsat: Space Activities for Students

ERIC Educational Resources Information Center

Marks, Steven K.

1979-01-01

An aerospace education activity is described which is suitable for grades 3-12. Students piece together several images from the Landsat satellite to make a mosaic of their state. From the mosaic clear acetate overlay maps can be made relating to such subjects as agriculture, geology, hydrology, or urban planning. (BB)

The Landsat Image Mosaic of Antarctica

USGS Publications Warehouse

Bindschadler, Robert; Vornberger, P.; Fleming, A.; Fox, A.; Mullins, J.; Binnie, D.; Paulsen, S.J.; Granneman, Brian J.; Gorodetzky, D.

2008-01-01

The Landsat Image Mosaic of Antarctica (LIMA) is the first true-color, high-spatial-resolution image of the seventh continent. It is constructed from nearly 1100 individually selected Landsat-7 ETM+ scenes. Each image was orthorectified and adjusted for geometric, sensor and illumination variations to a standardized, almost seamless surface reflectance product. Mosaicing to avoid clouds produced a high quality, nearly cloud-free benchmark data set of Antarctica for the International Polar Year from images collected primarily during 1999-2003. Multiple color composites and enhancements were generated to illustrate additional characteristics of the multispectral data including: the true appearance of the surface; discrimination between snow and bare ice; reflectance variations within bright snow; recovered reflectance values in regions of sensor saturation; and subtle topographic variations associated with ice flow. LIMA is viewable and individual scenes or user defined portions of the mosaic are downloadable at http://lima.usgs.gov. Educational materials associated with LIMA are available at http://lima.nasa.gov.

An operational earth resources satellite system - The Landsat follow-on program

NASA Technical Reports Server (NTRS)

Stroud, W. G.

1977-01-01

The Landsats 1 and 2 have demonstrated the role of remote sensing from satellite in research, development, and operational activities essential to the better management of our resources. Hundreds of agricultural, geological, hydrological, urban land use, and other investigations have raised the question of the development of an operational system providing continuous, timely data. The Landsat follow-on study addressed the economics, technological performance, and design of a system in transition from R&D to operations. Economic benefits were identified; and a complete system from sensors to the utilization in forecasting crop production, oil and mineral exploration, water resources management was designed. Benefits-to-costs ratio in present-worth dollars is at least 4:1.

Assessment of the availability of the tracking and data relay satellite system for LANDSAT missions

NASA Technical Reports Server (NTRS)

1982-01-01

The telecommunications availability that can realistically be provided by the tracking and data relay satellite system (TDRSS) for LANDSAT D type missions. Although the assessment focusses on the telecommunications requirements of the near Earth orbit missions of the 1985 - 1989 time frame, it emphasizes LANDSAT D and its competing demand for wideband, real-time RF link services from TDRSS. Limitations in availability of communications services are identified, including systematic TDRSS restrictions, conflicting telecommunication requirements and loading problems of all users (missions) which are to be supported by TDRSS. Several telecommunications alternatives for LANDSAT D utilization independent of TDRSS services are discussed.

The use of LANDSAT DCS and imagery in reservoir management and operation

NASA Technical Reports Server (NTRS)

Cooper, S.; Bock, P.; Horowitz, J.; Foran, D.

1975-01-01

Experiments by the New England Division (NED), Corps of Engineers with LANDSAT-1 data collection and imaging systems are reported. Data cover the future usefulness of data products received from satellites such as LANDSAT in the day to day operation of NED water resources systems used to control floods.

Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

NASA Astrophysics Data System (ADS)

Lazaridou, M. A.; Karagianni, A. Ch.

2016-06-01

Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

SAR/LANDSAT image registration study

NASA Technical Reports Server (NTRS)

Murphrey, S. W. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Temporal registration of synthetic aperture radar data with LANDSAT-MSS data is both feasible (from a technical standpoint) and useful (from an information-content viewpoint). The greatest difficulty in registering aircraft SAR data to corrected LANDSAT-MSS data is control-point location. The differences in SAR and MSS data impact the selection of features that will serve as a good control points. The SAR and MSS data are unsuitable for automatic computer correlation of digital control-point data. The gray-level data can not be compared by the computer because of the different response characteristics of the MSS and SAR images.

Landsat satellite evidence of the decline of northern California bull kelp

NASA Astrophysics Data System (ADS)

Renshaw, A.; Houskeeper, H. F.; Kudela, R. M.

2017-12-01

Bull kelp (Nereocystis luetkeana), a species of canopy-forming brown macroalga dominant in the Pacific Northwest of North America, provides critical ecological services such as habitat for a diverse array of marine species, nutrient regulation, photosynthesis, and regional marine carbon cycling. Starting around 2014, annual aerial surveys of bull kelp forests along California's northern coastline conducted by the California Department of Fish and Wildlife (CDFW) have reported a sudden 93% reduction in bull kelp canopy area. Remote sensing using satellite imagery is a robust, highly accurate tool for detecting and quantifying the abundance of the canopy-forming giant kelp, Macrocystis pyrifera; however, it has not been successfully applied to measuring northern bull kelp forests. One of the main difficulties associated with bull kelp detection via satellite is the small surface area of bull kelp canopies. As a result, bull kelp beds often only constitute part of a satellite pixel, making it difficult to obtain a kelp reflectance signal significantly different than water's reflectance signal. As part of the NASA Student Airborne Research Program (SARP), we test a novel method for assessing bull kelp canopy using a multiple endmember spectral mixing analysis (MESMA) applied to Landsat 5 and Landsat 8 imagery from 2003-2016. Water and kelp spectral endmembers are selected along the northern California coastline from Havens Neck cape to Point Arena. MESMA results are ground truthed with the CDFW aerial multispectral imagery data. This project will present a satellite-based time series of bull kelp canopy area and evaluate canopy change in a northern California kelp ecosystem.

The Landsat Image Mosaic of Antarctica (LIMA): A Cutting-Edge Way for Students and Teachers to Learn about Antarctica

ERIC Educational Resources Information Center

Campbell, Brian; Bindschadler, Robert

2009-01-01

By studying Antarctica via satellite and through ground-truthing research, we can learn where the ice is melting and why. The Landsat Image Mosaic of Antarctica (LIMA), a new and cutting-edge way for scientists, researchers, educators, students, and the public to look at Antarctica, supports this research and allows for unprecedented views of our…

Characteristics of the Landsat Multispectral Data System

USGS Publications Warehouse

Taranik, James V.

1978-01-01

Landsat satellites were launched into orbit in 1972 and 1975. Additional Landsat satellites are planned for launch in 1978 and 1981. The satellites orbit the Earth at an altitude of approximately 900 km and each can obtain repetitive coverage of cloud-free areas every 18 days. A sun-synchronous orbit is used to insure repeatable illumination conditions. Repetitive satellite coverage allows optimal cover conditions for geologic applications to be identified. Seasonal variations in solar illumination must be analyzed to select the best Landsat data for geologic applications. Landsat data may be viewed in stereo where there is sufficient sidelap and sufficient topographic relief. Landsat-1 ceased operation on January 10, 1978. Landsat-2 detects, only solar radiation that is reflected from the Earth's surface in visible and near-visible wavelengths. The third Landsat will also detect emitted thermal radiation. The multispectral scanner (MSS) was the only sensing instrument used on the first two satellites. The MSS on Landsats-1 and -2 detect radiation which is reflected from a 79 m by 79 m area, and the data are formatted as if the measurement was made from a 56 m by 79 m area. The MSS integrates spectral response from all cover types within the 79 m by 79 m area. The integrated spectral signature often does not resemble the spectral signature from individual cover types, and the integrated signature is also modified by the atmosphere. Landsat-1 and -2 data are converted to 70 mm film and computer compatible tapes (CCT's) at Goddard Space Flight Center (GSFC); these are shipped to the EROS Data Center (EDC) for duplication and distribution to users. Landsat-C data will be converted to 241 mm-wide film and CCT's at EDC. Landsat-D data will be relayed from the satellite directly to geosynchronous satellites and then to the United States from any location on Earth.

Higher resolution satellite remote sensing and the impact on image mapping

USGS Publications Warehouse

Watkins, Allen H.; Thormodsgard, June M.

1987-01-01

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges.The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

Design and implementation of the next generation Landsat satellite communications system

USGS Publications Warehouse

Mah, Grant R.; O'Brien, Michael; Garon, Howard; Mott, Claire; Ames, Alan; Dearth, Ken

2012-01-01

The next generation Landsat satellite, Landsat 8 (L8), also known as the Landsat Data Continuity Mission (LDCM), uses a highly spectrally efficient modulation and data formatting approach to provide large amounts of downlink (D/L) bandwidth in a limited X-Band spectrum allocation. In addition to purely data throughput and bandwidth considerations, there were a number of additional constraints based on operational considerations for prevention of interference with the NASA Deep-Space Network (DSN) band just above the L8 D/L band, minimization of jitter contributions to prevent impacts to instrument performance, and the need to provide an interface to the Landsat International Cooperator (IC) community. A series of trade studies were conducted to consider either X- or Ka-Band, modulation type, and antenna coverage type, prior to the release of the request for proposal (RFP) for the spacecraft. Through use of the spectrally efficient rate-7/8 Low-Density Parity-Check error-correction coding and novel filtering, an XBand frequency plan was developed that balances all the constraints and considerations, while providing world-class link performance, fitting 384 Mbits/sec of data into the 375 MHz X-Band allocation with bit-error rates better than 10-12 using an earth-coverage antenna.

A hybrid color mapping approach to fusing MODIS and Landsat images for forward prediction

USDA-ARS?s Scientific Manuscript database

We present a new, simple, and efficient approach to fusing MODIS and Landsat images. It is well known that MODIS images have high temporal resolution and low spatial resolution whereas Landsat images are just the opposite. Similar to earlier approaches, our goal is to fuse MODIS and Landsat images t...

Reconstructing Forty Years of Landsat Observations

NASA Astrophysics Data System (ADS)

Meyer, D. J.; Dwyer, J. L.; Steinwand, D.

2013-12-01

In July 1972, NASA launched the Earth Resource Technology Satellite (ERTS), the first of what was to be the series of Earth-observing satellites we now know as the Landsat system. This system, originally conceived in the 1960's within the US Department of the Interior and US Geological Survey (USGS), has continued with little interruption for over 40 years, creating the longest record of satellite-based global land observations. The current USGS archive of Landsat images exceeds 4 million scenes, and the recently launched Landsat 8 platform will extend that archive to nearly 50 years of observations. Clearly, these observations are critical to the study of Earth system processes, and the interaction between these processes and human activities. However, the seven successful Landsat missions represent more of an ad hoc program than a long-term record of consistent observations, due largely to changing Federal policies and challenges finding an operational home for the program. Technologically, these systems evolved from the original Multispectral Scanning System (MSS) through the Thematic Mapper and Enhanced Thematic Mapper Plus (ETM+) systems, to the current Observational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) systems. Landsat data were collected globally by a network of international cooperators having diverse data management policies. Much of the oldest data were stored on archaic media that could not be retrieved using modern media readers. Collecting these data from various sensors and sources, and reconstructing them into coherent Earth observation records, posed numerous challenges. We present here a brief overview of work done to overcome these challenges and create a consistent, long-term Landsat observation record. Much of the current archive was 'repatriated' from international cooperators and often required the reconstruction of (sometimes absent) metadata for geo-location and radiometric calibration. The older MSS data, some of which had

Vegetation Cover Change in the Upper Kings River Basin of the Sierra Nevada Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2015-01-01

The Sierra Nevada of California is a region where large wildfires have been suppressed for over a century. A detailed geographic record of recent changes in vegetation cover across the Sierra Nevada remains a gap that can be filled with satellite remote sensing data. Results from Landsat image analysis over the past 25 years in the Upper Kings River basin showed that consistent, significant increases in the normalized difference vegetation index (NDVI) have not extended above 2000 m elevation, where cold temperatures presumably limit the growing season. Moreover, mean increases in NDVI since 1986 at elevations below 2000 m (which cover about half of the total basin area) have not exceeded 9%, even in the most extreme precipitation yearly comparisons. NDVI has decreased significantly at elevations above 2000 m throughout the basin in relatively wet year comparisons since the mid-1980s. These findings conflict with any assumptions that ET fluxes and river flows downstream could have been markedly altered by vegetation change over most of the Upper Kings River basin in recent decades.

Fusion of MODIS and landsat-8 surface temperature images: a new approach.

PubMed

Hazaymeh, Khaled; Hassan, Quazi K

2015-01-01

Here, our objective was to develop a spatio-temporal image fusion model (STI-FM) for enhancing temporal resolution of Landsat-8 land surface temperature (LST) images by fusing LST images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS); and implement the developed algorithm over a heterogeneous semi-arid study area in Jordan, Middle East. The STI-FM technique consisted of two major components: (i) establishing a linear relationship between two consecutive MODIS 8-day composite LST images acquired at time 1 and time 2; and (ii) utilizing the above mentioned relationship as a function of a Landsat-8 LST image acquired at time 1 in order to predict a synthetic Landsat-8 LST image at time 2. It revealed that strong linear relationships (i.e., r2, slopes, and intercepts were in the range 0.93-0.94, 0.94-0.99; and 2.97-20.07) existed between the two consecutive MODIS LST images. We evaluated the synthetic LST images qualitatively and found high visual agreements with the actual Landsat-8 LST images. In addition, we conducted quantitative evaluations of these synthetic images; and found strong agreements with the actual Landsat-8 LST images. For example, r2, root mean square error (RMSE), and absolute average difference (AAD)-values were in the ranges 084-0.90, 0.061-0.080, and 0.003-0.004, respectively.

Bridging the Divide: Translating Landsat Research Into Usable Science

NASA Astrophysics Data System (ADS)

Rocchio, L. E.; Davis, A. L.

2006-12-01

Science has long served humankind. Breakthroughs in medicine have increased longevity and advances in technology have made modern-day conveniences possible. Yet, social benefits begotten by the environmental sciences, although critical for the survival of humanity, have not always been as widely recognized or used. To benefit today's rapidly growing population, the divides between environmental research, applied environmental science, and use of this information by decision makers must be bridged. Lessons about the translation from research to usable science can be learned from the four decades of Landsat history, and these lessons can serve as useful models for bridging the gaps between new technology, scientific research, and the use of that research and technology in real-world problem solving. In 1965, William Pecora, then-director of the U.S. Geological Survey, proposed the idea of a remote sensing satellite program to gather facts about natural resources of Earth. For the next seven years, an intense campaign showing the depth and diversity of satellite imagery applications was waged. This led to the 1972 launch of the first civilian land-observing satellite, Landsat 1. By 1975, successful application research based on Landsat 1 imagery prompted then-NASA Administrator Dr. James Fletcher to proclaim that if one space age development would save the world, it would be Landsat and its successor satellites. Thirty-four years of continual Landsat imaging and related-research has lead to the implementation of many socially beneficial applications, such as improved water management techniques, crop insurance fraud reduction, illicit crop inventories, natural disaster relief planning, continent-scale carbon estimates, and extensive cartographic advances. Despite these successes, the challenge of translating Landsat research into realized social benefits remains. Even in this geospatially-savvy era, the utility of Landsat largely escapes policymakers. Here, in an

Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2013-01-01

Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

Enhancement of Satellite Image Compression Using a Hybrid (DWT-DCT) Algorithm

NASA Astrophysics Data System (ADS)

Shihab, Halah Saadoon; Shafie, Suhaidi; Ramli, Abdul Rahman; Ahmad, Fauzan

2017-12-01

Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT-DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT-DCT) method to enhance the image compression process on-board satellites.

Evaluation and sensitivity testing of a coupled Landsat-MODIS downscaling method for land surface temperature and vegetation indices in semi-arid regions

NASA Astrophysics Data System (ADS)

Kim, Jongyoun; Hogue, Terri S.

2012-01-01

The current study investigates a method to provide land surface parameters [i.e., land surface temperature (LST) and normalized difference vegetation index (NDVI)] at a high spatial (˜30 and 60 m) and temporal (daily and 8-day) resolution by combining advantages from Landsat and moderate-resolution imaging spectroradiometer (MODIS) satellites. We adopt a previously developed subtraction method that merges the spatial detail of higher-resolution imagery (Landsat) with the temporal change observed in coarser or moderate-resolution imagery (MODIS). Applying the temporal difference between MODIS images observed at two different dates to a higher-resolution Landsat image allows prediction of a combined or fused image (Landsat+MODIS) at a future date. Evaluation of the resultant merged products is undertaken within the Southeastern Arizona region where data is available from a range of flux tower sites. The Landsat+MODIS fused products capture the raw Landsat values and also reflect the MODIS temporal variation. The predicted Landsat+MODIS LST improves mean absolute error around 5°C at the more heterogeneous sites compared to the original satellite products. The fused Landsat+MODIS NDVI product also shows good correlation to ground-based data and is relatively consistent except during the acute (monsoon) growing season. The sensitivity of the fused product relative to temporal gaps in Landsat data appears to be more affected by uncertainty associated with regional precipitation and green-up, than the length of the gap associated with Landsat viewing, suggesting the potential to use a minimal number of original Landsat images during relatively stable land surface and climate conditions. Our extensive validation yields insight on the ability of the proposed method to integrate multiscale platforms and the potential for reducing costs associated with high-resolution satellite systems (e.g., SPOT, QuickBird, IKONOS).

Principles of computer processing of Landsat data for geologic applications

USGS Publications Warehouse

Taranik, James V.

1978-01-01

The main objectives of computer processing of Landsat data for geologic applications are to improve display of image data to the analyst or to facilitate evaluation of the multispectral characteristics of the data. Interpretations of the data are made from enhanced and classified data by an analyst trained in geology. Image enhancements involve adjustments of brightness values for individual picture elements. Image classification involves determination of the brightness values of picture elements for a particular cover type. Histograms are used to display the range and frequency of occurrence of brightness values. Landsat-1 and -2 data are preprocessed at Goddard Space Flight Center (GSFC) to adjust for the detector response of the multispectral scanner (MSS). Adjustments are applied to minimize the effects of striping, adjust for bad-data lines and line segments and lost individual pixel data. Because illumination conditions and landscape characteristics vary considerably and detector response changes with time, the radiometric adjustments applied at GSFC are seldom perfect and some detector striping remain in Landsat data. Rotation of the Earth under the satellite and movements of the satellite platform introduce geometric distortions in the data that must also be compensated for if image data are to be correctly displayed to the data analyst. Adjustments to Landsat data are made to compensate for variable solar illumination and for atmospheric effects. GeoMetric registration of Landsat data involves determination of the spatial location of a pixel in. the output image and the determination of a new value for the pixel. The general objective of image enhancement is to optimize display of the data to the analyst. Contrast enhancements are employed to expand the range of brightness values in Landsat data so that the data can be efficiently recorded in a manner desired by the analyst. Spatial frequency enhancements are designed to enhance boundaries between features

Users, uses, and value of Landsat satellite imagery: results from the 2012 survey of users

USGS Publications Warehouse

Miller, Holly M.; Richardson, Leslie A.; Koontz, Stephen R.; Loomis, John; Koontz, Lynne

2013-01-01

Landsat satellites have been operating since 1972, providing a continuous global record of the Earth’s land surface. The imagery is currently available at no cost through the U.S. Geological Survey (USGS). Social scientists at the USGS Fort Collins Science Center conducted an extensive survey in early 2012 to explore who uses Landsat imagery, how they use the imagery, and what the value of the imagery is to them. The survey was sent to all users registered with USGS who had accessed Landsat imagery in the year prior to the survey and over 11,000 current Landsat imagery users responded. The results of the survey revealed that respondents from many sectors use Landsat imagery in myriad project locations and scales, as well as application areas. The value of Landsat imagery to these users was demonstrated by the high importance of and dependence on the imagery, the numerous environmental and societal benefits observed from projects using Landsat imagery, the potential negative impacts on users’ work if Landsat imagery was no longer available, and the substantial aggregated annual economic benefit from the imagery. These results represent only the value of Landsat to users registered with USGS; further research would help to determine what the value of the imagery is to a greater segment of the population, such as downstream users of the imagery and imagery-derived products.

SRTM Perspective View with Landsat Overlay: Bhuj, India

NASA Image and Video Library

2001-04-05

This perspective view shows the city of Bhuj, India, in the foreground gray area after an earthquake in western India on January 26, 2001. This image was generated from NASA Landsat satellite and data from Shuttle Radar Topography Mission SRTM.

Medium Resolution Global Earth Observations with Landsat: Looking 35 Years Back and 50 Years Forward

NASA Astrophysics Data System (ADS)

Williams, D. L.; Irons, J. R.; Goward, S. N.

2007-12-01

The modern era of global medium resolution satellite remote sensing was inaugurated 35 years ago, in July 1972, with the launch of the first Landsat satellite carrying the Multispectral Scanner (MSS) sensor. Ten years after that first launch, Landsat 4 carried a much-improved sensor aloft, the Thematic Mapper. The TM provided better spatial resolution (30 m versus 79 m) than the MSS, as well as additional spectral bands in the mid- infrared (IR) and thermal IR regions. Roughly another decade later, in April 1999, the Enhanced Thematic Mapper Plus (ETM+) instrument was placed in orbit on Landsat 7. The ETM+ provided a new 15 m panchromatic band and a much-improved thermal band resolution (60 m versus 120 m). Through a combination of planning and good luck, the various Landsat missions have delivered a continuous set of calibrated, multispectral images of the Earth's surface spanning this entire 35-year time period. This imagery database has been used in agricultural evaluations, forest management inventories, geological surveys, water resource estimates, coastal zone appraisals, and a host of other applications to meet the needs of a very broad user community, including business, government, science, education, national security, and now -- even the casual observer -- as Landsat imagery provides the skeletal backbone of Google Earth. Landsat established the U.S. as the world leader in terrestrial remote sensing, contributed significantly to the understanding of the Earth's environment, spawned revolutionary uses of space-based data by the commercial value-added industry, and encouraged a new generation of commercial satellites that provide regional, high-resolution spatial images. In spite of the overall success of the Landsat series of satellites, the first 35 years of the Landsat legacy have been extremely challenging as the push to embrace new technologies was often questioned by those who simply wanted to maintain whatever the current capability was at that

Landsat 7 - First Cloud-free Image of Yellowstone National Park

NASA Technical Reports Server (NTRS)

2002-01-01

This image of Yellowstone Lake, in the center of Yellowstone National Park, was taken by Landsat 7 on July 13, 1999. Bands 5 (1.65um),4 (.825um), and 2 (.565um) were used for red, green, and blue, respectively. Water appears blue/black, snow light blue, mature forest red/green, young forest pink, and grass and fields appear light green. Southwest of the lake is young forest that is growing in the wake of the widespread fires of 1988. For more information, see: Landsat 7 Fact Sheet Landsat 7 in Mission Control Image by Rich Irish, NASA GSFC

Multitemporal and Multiscaled Fractal Analysis of Landsat Satellite Data Using the Image Characterization and Modeling System (ICAMS)

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Emerson, Charles W.; Lam, Nina Siu-Ngan; Laymon, Charles A.

1997-01-01

The Image Characterization And Modeling System (ICAMS) is a public domain software package that is designed to provide scientists with innovative spatial analytical tools to visualize, measure, and characterize landscape patterns so that environmental conditions or processes can be assessed and monitored more effectively. In this study ICAMS has been used to evaluate how changes in fractal dimension, as a landscape characterization index, and resolution, are related to differences in Landsat images collected at different dates for the same area. Landsat Thematic Mapper (TM) data obtained in May and August 1993 over a portion of the Great Basin Desert in eastern Nevada were used for analysis. These data represent contrasting periods of peak "green-up" and "dry-down" for the study area. The TM data sets were converted into Normalized Difference Vegetation Index (NDVI) images to expedite analysis of differences in fractal dimension between the two dates. These NDVI images were also resampled to resolutions of 60, 120, 240, 480, and 960 meters from the original 30 meter pixel size, to permit an assessment of how fractal dimension varies with spatial resolution. Tests of fractal dimension for two dates at various pixel resolutions show that the D values in the August image become increasingly more complex as pixel size increases to 480 meters. The D values in the May image show an even more complex relationship to pixel size than that expressed in the August image. Fractal dimension for a difference image computed for the May and August dates increase with pixel size up to a resolution of 120 meters, and then decline with increasing pixel size. This means that the greatest complexity in the difference images occur around a resolution of 120 meters, which is analogous to the operational domain of changes in vegetation and snow cover that constitute differences between the two dates.

Fusion of MODIS and Landsat-8 Surface Temperature Images: A New Approach

PubMed Central

Hazaymeh, Khaled; Hassan, Quazi K.

2015-01-01

Here, our objective was to develop a spatio-temporal image fusion model (STI-FM) for enhancing temporal resolution of Landsat-8 land surface temperature (LST) images by fusing LST images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS); and implement the developed algorithm over a heterogeneous semi-arid study area in Jordan, Middle East. The STI-FM technique consisted of two major components: (i) establishing a linear relationship between two consecutive MODIS 8-day composite LST images acquired at time 1 and time 2; and (ii) utilizing the above mentioned relationship as a function of a Landsat-8 LST image acquired at time 1 in order to predict a synthetic Landsat-8 LST image at time 2. It revealed that strong linear relationships (i.e., r2, slopes, and intercepts were in the range 0.93–0.94, 0.94–0.99; and 2.97–20.07) existed between the two consecutive MODIS LST images. We evaluated the synthetic LST images qualitatively and found high visual agreements with the actual Landsat-8 LST images. In addition, we conducted quantitative evaluations of these synthetic images; and found strong agreements with the actual Landsat-8 LST images. For example, r2, root mean square error (RMSE), and absolute average difference (AAD)-values were in the ranges 084–0.90, 0.061–0.080, and 0.003–0.004, respectively. PMID:25730279

Detection flying aircraft from Landsat 8 OLI data

NASA Astrophysics Data System (ADS)

Zhao, F.; Xia, L.; Kylling, A.; Li, R. Q.; Shang, H.; Xu, Ming

2018-07-01

Monitoring flying aircraft from satellite data is important for evaluating the climate impact caused by the global aviation industry. However, due to the small size of aircraft and the complex surface types, it is almost impossible to identify aircraft from satellite data with moderate resolution, e.g. 30 m. In this study, the 1.38 μm water vapor absorption channel, often used for cirrus cloud or ash detection, is for the first time used to monitor flying aircraft from Landsat 8 data. The basic theory behind the detection of flying aircraft is that in the 1.38 μm channel most of the background reflectance between the ground and the aircraft is masked due to the strong water vapor absorption, while the signal of the flying aircraft will be attenuated less due to the low water vapor content between the satellite and the aircraft. A new composition of the Laplacian and Sobel operators for segmenting aircraft and other features were used to identify the flying aircraft. The Landsat 8 Operational Land Imager (OLI) 2.1 μm channel was used to make the method succeed under low vapor content. The accuracy assessment based on 65 Landsat 8 images indicated that the percentage of leakage is 3.18% and the percentage of false alarm is 0.532%.

Application of spectrometer cropscan MSR 16R and Landsat imagery for identification the spectral characteristics of land cover

NASA Astrophysics Data System (ADS)

Tampubolon, Togi; Abdullah, Khiruddin bin; San, Lim Hwee

2013-09-01

The spectral characteristics of land cover are basic references in classifying satellite image for geophysics analysis. It can be obtained from the measurements using spectrometer and satellite image processing. The aims of this study to investigate the spectral characteristics of land cover based on the results of measurement using Spectrometer Cropscan MSR 16R and Landsat satellite imagery. The area of study in this research is in Medan, (Deli Serdang, North Sumatera) Indonesia. The scope of this study is the basic survey from the measurements of spectral land cover which is covered several type of land such as a cultivated and managed terrestrial areas, natural and semi-natural, cultivated aquatic or regularly flooded areas, natural and semi-natural aquatic, artificial surfaces and associated areas, bare areas, artificial waterbodies and natural waterbodies. The measurement and verification were conducted using a spectrometer provided their spectral characteristics and Landsat imagery, respectively. The results of the spectral characteristics of land cover shows that each type of land cover have a unique characteristic. The correlation of spectral land cover based on spectrometer Cropscan MSR 16R and Landsat satellite image are above 90 %. However, the land cover of artificial waterbodiese have a correlation under 40 %. That is because the measurement of spectrometer Cropscan MSR 16R and acquisition of Landsat satellite imagery has a time different.

Spatial and temporal selectivity patterns of fires in Attika, Greece from 1984 to 2015 delineated from Landsat time series satellite images

NASA Astrophysics Data System (ADS)

Stamos, Zoi; Koutsias, Nikos

2017-04-01

The aim of this study is to assess spatial and temporalfire selectivity patterns in the region of Attica - Greece from 1984 to 2015. Our work is implemented in two distinct phases: the first consists of the accurate delineation of the fire perimeter using satellite remote sensing technology, and the second consists of the application of suitable GIS supported analyses to develop thematic layers that optimally summarised the spatial and temporal information of fire occurrence. Fire perimeters of wildland fires occurred within the time window 1984-2015 were delineated from freely available Landsat images from USGS and ESA sources.More than three thousands satellite images were processed in order to extract fire perimeters and create maps of fire frequency and fire return interval. In total one thousand and one hundred twenty fire perimeters were recorded during this thirty years' period. Fire perimeters within each year of fire occurrence were compared against the available to burn under complete random processes to identify selectivity patterns over (i) CORINE land use/land cover, (ii) fire frequency and (iii) time since last firemaps. For example, non- irrigated arable lands, complex cultivation patterns and discontinuous urban fabrics are negative related with fires, while coniferous forests, sclerophyllous vegetation and transitional woodlands seem to be preferable by the fires. Additionally, it seems that fires prefer their old burnings (two and three times burned) and also places with different patterns of time since last fire depending on the time needed by the type of vegetation to recover and thus to re-burn.

Satellite image based methods for fuels maps updating

NASA Astrophysics Data System (ADS)

Alonso-Benito, Alfonso; Hernandez-Leal, Pedro A.; Arbelo, Manuel; Gonzalez-Calvo, Alejandro; Moreno-Ruiz, Jose A.; Garcia-Lazaro, Jose R.

2016-10-01

Regular updating of fuels maps is important for forest fire management. Nevertheless complex and time consuming field work is usually necessary for this purpose, which prevents a more frequent update. That is why the assessment of the usefulness of satellite data and the development of remote sensing techniques that enable the automatic updating of these maps, is of vital interest. In this work, we have tested the use of the spectral bands of OLI (Operational Land Imager) sensor on board Landsat 8 satellite, for updating the fuels map of El Hierro Island (Spain). From previously digitized map, a set of 200 reference plots for different fuel types was created. A 50% of the plots were randomly used as a training set and the rest were considered for validation. Six supervised and 2 unsupervised classification methods were applied, considering two levels of detail. A first level with only 5 classes (Meadow, Brushwood, Undergrowth canopy cover >50%, Undergrowth canopy cover <15%, and Xeric formations), and the second one containing 19 fuel types. The level 1 classification methods yielded an overall accuracy ranging from 44% for Parellelepided to an 84% for Maximun Likelihood. Meanwhile, level 2 results showed at best, an unacceptable overall accuracy of 34%, which prevents the use of this data for such a detailed characterization. Anyway it has been demonstrated that in some conditions, images of medium spatial resolution, like Landsat 8-OLI, could be a valid tool for an automatic upgrade of fuels maps, minimizing costs and complementing traditional methodologies.

Concepts for on-board satellite image registration. Volume 2: IAS prototype performance evaluation standard definition. [NEEDS Information Adaptive System

NASA Technical Reports Server (NTRS)

Daluge, D. R.; Ruedger, W. H.

1981-01-01

Problems encountered in testing onboard signal processing hardware designed to achieve radiometric and geometric correction of satellite imaging data are considered. These include obtaining representative image and ancillary data for simulation and the transfer and storage of a large quantity of image data at very high speed. The high resolution, high speed preprocessing of LANDSAT-D imagery is considered.

Radiometric cross calibration of Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+)

USGS Publications Warehouse

Mishra, Nischal; Haque, Md. Obaidul; Leigh, Larry; Aaron, David; Helder, Dennis; Markham, Brian L

2014-01-01

This study evaluates the radiometric consistency between Landsat-8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) using cross calibration techniques. Two approaches are used, one based on cross calibration between the two sensors using simultaneous image pairs, acquired during an underfly event on 29–30 March 2013. The other approach is based on using time series of image statistics acquired by these two sensors over the Libya 4 pseudo invariant calibration site (PICS) (+28.55°N, +23.39°E). Analyses from these approaches show that the reflectance calibration of OLI is generally within ±3% of the ETM+ radiance calibration for all the reflective bands from visible to short wave infrared regions when the ChKur solar spectrum is used to convert the ETM+ radiance to reflectance. Similar results are obtained comparing the OLI radiance calibration directly with the ETM+ radiance calibration and the results in these two different physical units (radiance and reflectance) agree to within ±2% for all the analogous bands. These results will also be useful to tie all the Landsat heritage sensors from Landsat 1 MultiSpectral Scanner (MSS) through Landsat-8 OLI to a consistent radiometric scale.

Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree.

PubMed

Acharya, Tri Dev; Lee, Dong Ha; Yang, In Tae; Lee, Jae Kang

2016-07-12

Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size.

Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)

NASA Technical Reports Server (NTRS)

Masek, Jeffrey G.

2006-01-01

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 2200 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial continental disturbance products will be available by the middle of 2006.

a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images

NASA Astrophysics Data System (ADS)

Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei

2018-04-01

Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.

Retrieval of suspended sediment concentrations using Landsat-8 OLI satellite images in the Orinoco River (Venezuela)

NASA Astrophysics Data System (ADS)

Yepez, Santiago; Laraque, Alain; Martinez, Jean-Michel; De Sa, Jose; Carrera, Juan Manuel; Castellanos, Bartolo; Gallay, Marjorie; Lopez, Jose L.

2018-01-01

In this study, 81 Landsat-8 scenes acquired from 2013 to 2015 were used to estimate the suspended sediment concentration (SSC) in the Orinoco River at its main hydrological station at Ciudad Bolivar, Venezuela. This gauging station monitors an upstream area corresponding to 89% of the total catchment area where the mean discharge is of 33,000 m3·s-1. SSC spatial and temporal variabilities were analyzed in relation to the hydrological cycle and to local geomorphological characteristics of the river mainstream. Three types of atmospheric correction models were evaluated to correct the Landsat-8 images: DOS, FLAASH, and L8SR. Surface reflectance was compared with monthly water sampling to calibrate a SSC retrieval model using a bootstrapping resampling. A regression model based on surface reflectance at the Near-Infrared wavelengths showed the best performance: R2 = 0.92 (N = 27) for the whole range of SSC (18 to 203 mg·l-1) measured at this station during the studied period. The method offers a simple new approach to estimate the SSC along the lower Orinoco River and demonstrates the feasibility and reliability of remote sensing images to map the spatiotemporal variability in sediment transport over large rivers.

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

Perspective View with Landsat Overlay, San Jose, Costa Rica

NASA Technical Reports Server (NTRS)

2002-01-01

This perspective view shows the capital city of San Jose, Costa Rica, the gray area in the center of the image. The view is toward the northwest with the Pacific Ocean in the distance and shows a portion of the Meseta Central (Central Valley), home to about a third of Costa Rica's population.

Like much of Central America, Costa Rica is generally cloud covered, so very little satellite imagery is available. The ability of the Shuttle Radar Topography Mission (SRTM) instrument to penetrate clouds and make three-dimensional measurements will allow generation of the first complete high-resolution topographic map of the entire region. These data were used to generate the image.

This three-dimensional perspective view was generated using elevation data from SRTM and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated two times.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, S.D.

Elevation data used in this image was acquired by the SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between

Monitoring vegetation recovery in fire-affected areas using temporal profiles of spectral signal from time series MODIS and LANDSAT satellite images

NASA Astrophysics Data System (ADS)

Georgopoulou, Danai; Koutsias, Nikos

2015-04-01

Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when satellite remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series MODIS and LANDSAT satellite images can be used to characterize vegetation phenology and thus to be helpful for monitoring vegetation recovery in fire-affected areas. The aim of this study is to explore the vegetation recovery pattern of the catastrophic wildfires that occurred in Peloponnisos, southern Greece, in 2007. These fires caused the loss of 67 lives and were recognized as the most extreme natural disaster in the country's recent history. Satellite remote sensing data from MODIS and LANDSAT satellites in the period from 2000 to 2014 were acquired and processed to extract the temporal profiles of the spectral signal for selected areas within the fire-affected areas. This dataset and time period analyzed together with the time that these fires occurred gave the opportunity to create temporal profiles seven years before and seven years after the fire. The different scale of the data used gave us the chance to understand how vegetation phenology and therefore the recovery patterns are influenced by the spatial resolution of the satellite data used. Different metrics linked to key phenological events have been created and used to assess vegetation recovery in the fire-affected areas. Our analysis was focused in the main land cover types that were mostly affected by the 2007 wildland fires. Based on CORINE land-cover maps these were agricultural lands highly interspersed with large areas of natural vegetation followed by sclerophyllous vegetation, transitional woodland shrubs, complex cultivation patterns and olive groves. Apart of the use of the original spectral data we estimated and used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. In this study we

Landsat and SPOT data for oil exploration in North-Western China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nishidai, Takashi

1996-07-01

Satellite remote sensing technology has been employed by Japex to provide information related to oil exploration programs for many years. Since the beginning of the 1980`s, regional geological interpretation through to advanced studies using satellite imagery with high spectral and spatial resolutions (such as Landsat TM and SPOT HRV), have been carried out, for both exploration programs and for scientific research. Advanced techniques (including analysis of airborne hyper-multispectral imaging sensor data) as well as conventional photogeological techniques were used throughout these programs. The first program using remote sensing technology in China focused on the Tarim Basin, Xinjiang Uygur Autonomous Region,more » and was carried out using Landsat MSS data. Landsat MSS imagery allows us to gain useful preliminary geological information about an area of interest, prior to field studies. About 90 Landsat scenes cover the entire Xinjiang Uygru Autonomous Region, this allowed us to give comprehensive overviews of 3 hydrocarbon-bearing basins (Tarim, Junggar, and Turpan-Hami) in NW China. The overviews were based on the interpretations and assessments of the satellite imagery and on a synthesis of the most up-to-date accessible geological and geophysical data as well as some field works. Pairs of stereoscopic SPOT HRV images were used to generate digital elevation data with a 40 in grid cover for part of the Tarim Basin. Topographic contour maps, created from this digital elevation data, at scales of 1:250,000 and 1:100,000 with contour intervals of 100 m and 50 m, allowed us to make precise geological interpretation, and to carry out swift and efficient geological field work. Satellite imagery was also utilized to make medium scale to large scale image maps, not only to interpret geological features but also to support field workers and seismic survey field operations.« less

Least Square Approach for Estimating of Land Surface Temperature from LANDSAT-8 Satellite Data Using Radiative Transfer Equation

NASA Astrophysics Data System (ADS)

Jouybari-Moghaddam, Y.; Saradjian, M. R.; Forati, A. M.

2017-09-01

Land Surface Temperature (LST) is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE). However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11) and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI) and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE) is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

The Landsat Image Mosaic of Antarctica

NASA Astrophysics Data System (ADS)

Bindschadler, R.; Vornberger, P.; Fleming, A.; Fox, A.; Morin, P.

2008-12-01

The first-ever true-color, high-resolution digital mosaic of Antarctica has been produced from nearly 1100 Landsat-7 ETM+ images collected between 1999 and 2003. The Landsat Image Mosaic of Antarctica (LIMA) project was an early benchmark data set of the International Polar Year and represents a close and successful collaboration between NASA, USGS, the British Antarctic Survey and the National Science Foundation. The mosaic was successfully merged with lower resolution MODIS data south of Landsat coverage to produce a complete true-color data set of the entire continent. LIMA is being used as a platform for a variety of education and outreach activities. Central to this effort is the NASA website 'Faces of Antarctica' that offers the web visitor the opportunity to explore the data set and to learn how these data are used to support scientific research. Content is delivered through a set of mysteries designed to pique the user's interest and to motivate them to delve deeper into the website where there are various videos and scientific articles for downloading. Detailed lesson plans written by teachers are provided for classroom use and Java applets let the user track the motion of ice in sequential Landsat images. Web links take the user to other sites where they can roam over the imagery using standard pan and zoom functions, or search for any named feature in the Antarctic Geographic Names data base that returns to the user a centered true-color view of any named feature. LIMA also has appeared is a host of external presentations from museum exhibits, to postcards and large posters. It has attracted various value-added providers that increase LIMA's accessibility by allowing users to specify subsets of the very large data set for individual downloads. The ultimate goal of LIMA in the public and educational sector is to enable everyone to become more familiar with Antarctica.

Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance

USGS Publications Warehouse

Huang, Chengquan; Wylie, Bruce K.; Yang, Limin; Homer, Collin G.; Zylstra, G.

2002-01-01

A new tasselled cap transformation based on Landsat 7 at-satellite reflectance was developed. This transformation is most appropriate for regional applications where atmospheric correction is not feasible. The brightness, greenness and wetness of the derived transformation collectively explained over 97% of the spectral variance of the individual scenes used in this study.

IMPROVING THE ACCURACY OF HISTORIC SATELLITE IMAGE CLASSIFICATION BY COMBINING LOW-RESOLUTION MULTISPECTRAL DATA WITH HIGH-RESOLUTION PANCHROMATIC DATA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Getman, Daniel J

2008-01-01

Many attempts to observe changes in terrestrial systems over time would be significantly enhanced if it were possible to improve the accuracy of classifications of low-resolution historic satellite data. In an effort to examine improving the accuracy of historic satellite image classification by combining satellite and air photo data, two experiments were undertaken in which low-resolution multispectral data and high-resolution panchromatic data were combined and then classified using the ECHO spectral-spatial image classification algorithm and the Maximum Likelihood technique. The multispectral data consisted of 6 multispectral channels (30-meter pixel resolution) from Landsat 7. These data were augmented with panchromatic datamore » (15m pixel resolution) from Landsat 7 in the first experiment, and with a mosaic of digital aerial photography (1m pixel resolution) in the second. The addition of the Landsat 7 panchromatic data provided a significant improvement in the accuracy of classifications made using the ECHO algorithm. Although the inclusion of aerial photography provided an improvement in accuracy, this improvement was only statistically significant at a 40-60% level. These results suggest that once error levels associated with combining aerial photography and multispectral satellite data are reduced, this approach has the potential to significantly enhance the precision and accuracy of classifications made using historic remotely sensed data, as a way to extend the time range of efforts to track temporal changes in terrestrial systems.« less

Perspective view, Landsat overlay Oahu, Hawaii

NASA Technical Reports Server (NTRS)

2000-01-01

Honolulu, on the island of Oahu, is a large and growing urban area with limited space and water resources. This perspective view, combining a Landsat image with SRTM topography, shows how the topography controls the urban growth pattern, causes cloud formation, and directs the rainfall runoff pattern. Features of interest in this scene include downtown Honolulu (right), Honolulu Harbor (right), Pearl Harbor (center), and offshore reef patterns (foreground). The Koolau mountain range runs through the center of the image. On the north shore of the island are the Mokapu Peninsula and Kaneohe Bay (upper right). Clouds commonly hang above ridges and peaks of the Hawaiian Islands, and in this rendition appear draped directly on the mountains. The clouds are actually about 1000 meters (3300 feet) above sea level. High resolution topographic and image data allow ecologists and planners to assess the effects of urban development on the sensitive ecosystems in tropical regions.

This type of display adds the important dimension of elevation to the study of land use and environmental processes as observed in satellite images. The perspective view was created by draping a Landsat 7 satellite image over an SRTM elevation model. Topography is exaggerated about six times vertically. The Landsat 7 image was acquired on February 12, 2000, and was provided by the United States Geological Survey's Earth Resources Observations Systems (EROS)Data Center, Sioux Falls, South Dakota.

The Shuttle Radar Topography Mission (SRTM), launched on February 11, 2000, uses the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. The mission is designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, an additional C-band imaging antenna and improved tracking and navigation devices. The

Spectral Unmixing Analysis of Time Series Landsat 8 Images

NASA Astrophysics Data System (ADS)

Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

2018-05-01

Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging

NASA Astrophysics Data System (ADS)

Nag, S.; Li, A.

2016-12-01

Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now have the ability to slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard's TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This paper will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a LandSat-like sensor. Increasing the FOV three times reduces the need to four satellites, however adds image distortion and BRDF complexities to the observed reflectance. If narrow FOV sensors on a small satellite constellation were commanded using robust algorithms to slew their sensor dynamically, they would be able to coordinately cover the global landmass much faster without compensating for spatial resolution or BRDF effects. Our algorithm to optimize constellation satellite pointing is based on a dynamic programming approach under the constraints of orbital mechanics and existing attitude control systems for small satellites. As a case study for our algorithm, we minimize the time required to cover the 17000 Landsat images with maximum signal to noise ratio fall

Landsat View: Western Suburbs of Chicago, Illinois

NASA Image and Video Library

2017-12-08

Forty miles west of downtown Chicago, the Fox River meanders its way through what has become the westernmost reaches of metropolitan Chicago, where the sprawling metropolis meets the hinterlands. While Chicago itself has seen a seven percent population decline during the last decade, the population of its metropolitan region, "Chicagoland," has steadily increased. These two natural-color Landsat 5 images acquired a quarter-century apart (on May 2, 1985, and May 23, 2010), stand witness to the soaring growth of this region. Aurora, Illinois’ second largest city, is the silvery-green region to the left hugging the Fox River, just south of the I-88 (North is to the right in this image); Carpentersville is found on the rightmost side, north of the I-90. From 1985 to 2010 a development explosion can been seen as the browns of pasture lands give way to silvery-green suburban areas and large white-colored business districts spring up along and east of the river. A major expansion of Dupage Airport appears in the middle of the 2010 image, and the circular-shaped region north of the I-88 and east of the Fox River, visible on both images, is the Department of Energy’s Fermilab. ---- NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. In honor of Landsat’s 40th anniversary in July 2012, the USGS released the LandsatLook viewer – a quick, simple way to go forward and backward in time, pulling images of anywhere in the world out of the Landsat archive. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading

Rock type discrimination and structural analysis with LANDSAT and Seasat data: San Rafael swell, Utah

NASA Technical Reports Server (NTRS)

Stewart, H. E.; Blom, R.; Abrams, M.; Daily, M.

1980-01-01

Satellite synthetic aperture radar (SAR) images is evaluated in terms of its geologic applications. The benchmark to which the SAR images are compared is LANDSAT, used both for structural and lithologic interpretations.

Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images.

PubMed

Bustamante, Javier; Pacios, Fernando; Díaz-Delgado, Ricardo; Aragonés, David

2009-05-01

We have used Landsat-5 TM and Landsat-7 ETM+ images together with simultaneous ground-truth data at sample points in the Doñana marshes to predict water turbidity and depth from band reflectance using Generalized Additive Models. We have point samples for 12 different dates simultaneous with 7 Landsat-5 and 5 Landsat-7 overpasses. The best model for water turbidity in the marsh explained 38% of variance in ground-truth data and included as predictors band 3 (630-690 nm), band 5 (1550-1750 nm) and the ratio between bands 1 (450-520 nm) and 4 (760-900 nm). Water turbidity is easier to predict for water bodies like the Guadalquivir River and artificial ponds that are deep and not affected by bottom soil reflectance and aquatic vegetation. For the latter, a simple model using band 3 reflectance explains 78.6% of the variance. Water depth is easier to predict than turbidity. The best model for water depth in the marsh explains 78% of the variance and includes as predictors band 1, band 5, the ratio between band 2 (520-600 nm) and band 4, and bottom soil reflectance in band 4 in September, when the marsh is dry. The water turbidity and water depth models have been developed in order to reconstruct historical changes in Doñana wetlands during the last 30 years using the Landsat satellite images time series.

Use of LANDSAT 2 data technique to estimate silverleaf sunflower infestation

NASA Technical Reports Server (NTRS)

Richardson, A. J.; Escobar, D. E.; Gausman, H. W.; Everitt, J. H. (Principal Investigator)

1982-01-01

The feasibility of the technique using the Earth Resources Technology Satellite (LANDSAT-2) multispectral scanner (MSS) was tested; to distinguish silverleaf sunflowers (Helianthus argophyllus Torr. and Gray) from other plant species and to estimate the hectarage percent of its infestation. Sunflowers gave high mean digital counts in all four LANDSAT MSS bands that were manifested as a pinkish image response on the LANDSAT color composite imagery. Photo- and LANDSAT-estimated hectare percentages for silverleaf sunflower within a 23,467 ha study area were 9.1 and 9.5%, respectively. The geographic occurrence of sunflower areas on the line-printer recognition map was in good agreement with their known aerial photographic locations.

Overview of the Landsat-7 Mission

NASA Technical Reports Server (NTRS)

Williams, Darrel; Irons, James; Goward, Samuel N.; Masek, Jefery

1999-01-01

Landsat-7 is scheduled for launch on April 15 from the Western Test Range at Vandenberg Air Force Base, Calif., on a Delta-H expendable launch vehicle. The Landsat 7 satellite consists of a spacecraft bus being provided by Lockheed Martin Missiles and Space (Valley Forge, Pa.) and the Enhanced Thematic Mapper Plus instrument built by Raytheon (formerly Hughes) Santa Barbara Remote Sensing (Santa Barbara, Calif.). The instrument on board Landsat 7 is the Enhanced Thematic Mapper Plus (ETM+). ETM+ improves upon the previous Thematic Mapper (TM) instruments on Landsat's 4 and 5 (Fig. la and lb). It includes the previous 7 spectral bands measuring reflected solar radiation and emitted thermal emissions but, in addition, includes a new 15 in panchromatic (visible-near infrared) band. The spatial resolution of the thermal infrared band has also been improved to 60 m. Both the radiometric precision and accuracy of the sensor are also improved from the previous TM sensors. After being launched into a sun-synchronous polar orbit, the satellite will use on-board propulsion to adjust its orbit to a circular altitude of 438 miles (705 kilometers) crossing the equator at approximately 10 a.m. on its southward track. This orbit will place Landsat 7 along the same ground track as previous Landsat satellites. The orbit will be maintained with periodic adjustments for the life of the mission. A three-axis attitude control subsystem will stabilize the satellite and keep the instrument pointed toward the Earth to within 0.05 degrees. Later this year, plans call for the NASA Earth Observation System (EOS) Terra (AM-1) observatory and the experimental EO-1 mission to closely follow Landsat-7's orbit to support synergistic research and applications from this new suite of terrestrial sensor systems. Landsat is the United States' oldest land-surface observation satellite system, with satellites continuously operating since 1972. Although the program has scored numerous successes in

BOREAS RSS-7 Landsat TM LAI IMages of the SSA and NSA

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Chen, Jing; Cihlar, Josef

2000-01-01

The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team used Landsat Thematic Mapper (TM) images processed at CCRS to produce images of Leaf Area Index (LAI) for the BOREAS study areas. Two images acquired on 06-Jun and 09-Aug-1991 were used for the SSA, and one image acquired on 09-Jun-1994 was used for the NSA. The LAI images are based on ground measurements and Landsat TM Reduced Simple Ratio (RSR) images. The data are stored in binary image-format files.

Development of Global 30m Resolution Water Body Map with Permanent/Temporal Water Body Separation Using Satellite Acquired Images of Landsat GLS Datasets

NASA Astrophysics Data System (ADS)

Ikeshima, D.; Yamazaki, D.; Yoshikawa, S.; Kanae, S.

2015-12-01

The specification of worldwide water body distribution is important for discovering hydrological cycle. Global 3-second Water Body Map (G3WBM) is a global scale map, which indicates the distribution of water body in 90m resolutions (http://hydro.iis.u-tokyo.ac.jp/~yamadai/G3WBM/index.html). This dataset was mainly built to identify the width of river channels, which is one of major uncertainties of continental-scale river hydrodynamics models. To survey the true width of the river channel, this water body map distinguish Permanent Water Body from Temporary Water Body, which means separating river channel and flood plain. However, rivers with narrower width, which is a major case in usual river, could not be observed in this map. To overcome this problem, updating the algorithm of G3WBM and enhancing the resolutions to 30m is the goal of this research. Although this 30m-resolution water body map uses similar algorithm as G3WBM, there are many technical issues attributed to relatively high resolutions. Those are such as lack of same high-resolution digital elevation map, or contamination problem of sub-pixel scale object on satellite acquired image, or invisibility of well-vegetated water body such as swamp. To manage those issues, this research used more than 30,000 satellite images of Landsat Global Land Survey (GLS), and lately distributed topography data of Shuttle Rader Topography Mission (SRTM) 1 arc-second (30m) digital elevation map. Also the effect of aerosol, which would scatter the sun reflectance and disturb the acquired result image, was considered. Due to these revises, the global water body distribution was established in more precise resolution.

Cloud detection algorithm comparison and validation for operational Landsat data products

USGS Publications Warehouse

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate

On-Orbit ACDS Performance of the Landsat 7 Spacecraft

NASA Technical Reports Server (NTRS)

Sabelhaus, Phillip; Bolek, Joseph; Scott, Steve; Holmes, Eric; O'Donnell, James R., Jr.; Storey, James

2001-01-01

Landsat 7 is part of NASA's Earth Science Enterprise (ESE). The ESE is committed to developing an understanding of the total Earth system, the effects of natural and human-induced changes on the global environment, and how natural processes affect humans and how humans affect them. The Landsat 7 satellite consists of the spacecraft bus which was provided under a NASA contract with Lockheed Martin Missiles and Space in Philadelphia, PA, and the Enhanced Thematic Mapper-Plus (ETM+) instrument, procured under a NASA contract with Raytheon Santa Barbara Remote Sensing, in Santa Barbara, CA. The Landsat 7 Attitude Control and Determination System (ACDS) provides many essential functions for the operation of the spacecraft bus and for ETM+. The ACDS maintains the required attitude and orbit at the degree of accuracy necessary for power generation, command and telemetry, thermal balance, image acquisition, Gimbaled X-Band Antenna (GXA) pointing and data for image post-processing. Descriptions of the Landsat 7 mission and the ACDS modes and requirements are presented. A brief summary of significant events of the on-orbit initialization and validation period are provided. Finally, the Landsat 7 product generation system is described and the impact that the ACDS performance has on the ground based image processing system is explored.

Valuing geospatial information: Using the contingent valuation method to estimate the economic benefits of Landsat satellite imagery

USGS Publications Warehouse

Loomis, John; Koontz, Steve; Miller, Holly M.; Richardson, Leslie A.

2015-01-01

While the U.S. government does not charge for downloading Landsat images, the images have value to users. This paper demonstrates a method that can value Landsat and other imagery to users. A survey of downloaders of Landsat images found: (a) established US users have a mean value of $912 USD per scene; (b) new US users and users returning when imagery became free have a mean value of $367 USD per scene. Total US user benefits for the 2.38 million scenes downloaded is $1.8 billion USD. While these benefits indicate a high willingness-to-pay among many Landsat downloaders, it would be economically inefficient for the US government to charge for Landsat imagery. Charging a price of $100 USD a scene would result in an efficiency loss of $37.5 million a year. This economic information should be useful to policy-makers who must decide about the future of this and similar remote sensing programs.

OHIO RIVER WATER QUALITY ASSESSMENT USING LANDSAT-7 DATA

EPA Science Inventory

The objectives of this project were (1) to develop a universal index for measuring Turbidity and Chlorophyll-A from remote sensing data and (2) to correlate satellite image parameters from Landsat-7 data with field measurements of water quality for five parameters: Chlorophyll-A ...

Landsat and Thermal Infrared Imaging

NASA Technical Reports Server (NTRS)

Arvidson, Terry; Barsi, Julia; Jhabvala, Murzy; Reuter, Dennis

2012-01-01

The purpose of this chapter is to describe the collection of thermal images by Landsat sensors already on orbit and to introduce the new thermal sensor to be launched in 2013. The chapter describes the thematic mapper (TM) and enhanced thematic mapper plus (ETM+) sensors, the calibration of their thermal bands, and the design and prelaunch calibration of the new thermal infrared sensor (TIRS).

A Project to Map and Monitor Baldcypress Forests in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Sader, Steven; Smoot, James

2012-01-01

Cypress swamp forests of Louisiana offer many important ecological and economic benefits: wildlife habitat, forest products, storm buffers, water quality, and recreation. Such forests are also threatened by multiple factors: subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, hurricanes, insect and nutria damage, timber harvesting, and land use conversion. Unfortunately, there are many information gaps regarding the type, location, extent, and condition of these forests. Better more up to date swamp forest mapping products are needed to aid coastal forest conservation and restoration work (e.g., through the Coastal Forest Conservation Initiative or CFCI). In response, a collaborative project was initiated to develop, test and demonstrate cypress swamp forest mapping products, using NASA supported Landsat, ASTER, and MODIS satellite data. Research Objectives are: Develop, test, and demonstrate use of Landsat and ASTER data for computing new cypress forest classification products and Landsat, ASTER, and MODIS satellite data for detecting and monitoring swamp forest change

Comparison of Landsat MSS and merged MSS/RBV data for analysis of natural vegetation

NASA Technical Reports Server (NTRS)

Roller, N. E. G.; Cox, S.

1980-01-01

Improved resolution could make satellite remote sensing data more useful for surveys of natural vegetation. Although improved satellite/sensor systems appear to be several years away, one potential interim solution to the problem of achieving greater resolution without sacrificing spectral sensitivity is through the merging of Landsat RBV and MSS data. This paper describes the results of a study performed to obtain a preliminary evaluation of the usefulness of two types of products that can be made by merging Landsat RBV and MSS data. The products generated were a false color composite image and a computer recognition map. Of these two products, the false color composite image appears to be the most useful.

TESTS OF LOW-FREQUENCY GEOMETRIC DISTORTIONS IN LANDSAT 4 IMAGES.

USGS Publications Warehouse

Batson, R.M.; Borgeson, W.T.; ,

1985-01-01

Tests were performed to investigate the geometric characteristics of Landsat 4 images. The first set of tests was designed to determine the extent of image distortion caused by the physical process of writing the Landsat 4 images on film. The second was designed to characterize the geometric accuracies inherent in the digital images themselves. Test materials consisted of film images of test targets generated by the Laser Beam Recorders at Sioux Falls, the Optronics* Photowrite film writer at Goddard Space Flight Center, and digital image files of a strip 600 lines deep across the full width of band 5 of the Washington, D. C. Thematic Mapper scene. The tests were made by least-squares adjustment of an array of measured image points to a corresponding array of control points.

Forest Tree Species Distribution Mapping Using Landsat Satellite Imagery and Topographic Variables with the Maximum Entropy Method in Mongolia

NASA Astrophysics Data System (ADS)

Hao Chiang, Shou; Valdez, Miguel; Chen, Chi-Farn

2016-06-01

Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM) were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface reflectance coupled

Geological Mapping Uses Landsat 4-5TM Satellite Data in Manlai Soum of Omnogovi Aimag

NASA Astrophysics Data System (ADS)

Norovsuren, B.

2014-12-01

Author: Bayanmonkh N1, Undram.G1, Tsolmon.R2, Ariunzul.Ya1, Bayartungalag B31 Environmental Research Information and Study Center 2NUM-ITC-UNESCO Space Science and Remote Sensing International Laboratory, National University of Mongolia 3Geology and Hydrology School, Korea University KEY WORDS: geology, mineral resources, fracture, structure, lithologyABSTRACTGeologic map is the most important map for mining when it does exploration job. In Mongolia geological map completed by Russian geologists which is done by earlier technology. Those maps doesn't satisfy for present requirements. Thus we want to study improve geological map which includes fracture, structural map and lithology use Landsat TM4-5 satellite data. If we can produce a geological map from satellite data with more specification then geologist can explain or read mineralogy very easily. We searched all methodology and researches of every single element of geological mapping. Then we used 3 different remote sensing methodologies to produce structural and lithology and fracture map based on geographic information system's softwares. There can be found a visible lithology border improvement and understandable structural map and we found fracture of the Russian geological map has a lot of distortion. The result of research geologist can read mineralogy elements very easy and discovered 3 unfound important elements from satellite image.

The Landsat Data Continuity Mission Operational Land Imager: Pre-Launch Performance

NASA Technical Reports Server (NTRS)

Markham, Brian L.; Knight, Edward J.; Canova, Brent; Donley, Eric; Kvaran, Geir; Lee, Kenton

2011-01-01

The Operational Land Imager(OLI) will be the main instrument on Landsat-8 when it launches in 2012. OLI represents a generational change from heritage Landsat instruments in its design but must maintain data continuity with the 30+ year Landsat data archive. As a result, OLI has undergone a stringent calibration and characterization campaign to ensure its characteristics are understood and consistent with past instruments. This paper presents an overview of the OLI design, its major differences from previous Landsat instruments, and a summary of its expected performance.

Ground-based radiometric calibration of the Landsat 8 Operational Land Imager (OLI) using in situ techniques

NASA Astrophysics Data System (ADS)

Czapla-Myers, J.

2013-12-01

Landsat 8 was successfully launched from Vandenberg Air Force Base in California on 11 February 2013, and was placed into the orbit previously occupied by Landsat 5. Landsat 8 is the latest platform in the 40-year history of the Landsat series of satellites, and it contains two instruments that operate in the solar-reflective and the thermal infrared regimes. The Operational Land Imager (OLI) is a pushbroom sensor that contains eight multispectral bands ranging from 400-2300 nm, and one panchromatic band. The spatial resolution of the multispectral bands is 30 m, which is similar to previous Landsat sensors, and the panchromatic band has a 15-m spatial resolution, which is also similar to previous Landsat sensors. The 12-bit radiometric resolution of OLI improves upon the 8-bit resolution of the Enhanced Thematic Mapper Plus (ETM+) onboard Landsat 7. An important requirement for the Landsat program is the long-term radiometric continuity of its sensors. Ground-based vicarious techniques have been used for over 20 years to determine the absolute radiometric calibration of sensors that encompass a wide variety of spectral and spatial characteristics. This work presents the early radiometric calibration results of Landsat 8 OLI that were obtained using the traditional reflectance-based approach. University of Arizona personnel used five sites in Arizona, California, and Nevada to collect ground-based data. In addition, a unique set of in situ data were collected in March 2013, when Landsat 7 and Landsat 8 were observing the same site within minutes of each other. The tandem overfly schedule occurred while Landsat 8 was shifting to the WRS-2 orbital grid, and lasted only a few days. The ground-based data also include results obtained using the University of Arizona's Radiometric Calibration Test Site (RadCaTS), which is an automated suite of instruments located at Railroad Valley, Nevada. The results presented in this work include a comparison to the L1T at

Landsat multispectral sharpening using a sensor system model and panchromatic image

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2003-01-01

The thematic mapper (TM) sensor aboard Landsats 4, 5 and enhanced TM plus (ETM+) on Landsat 7 collect imagery at 30-m sample distance in six spectral bands. New with ETM+ is a 15-m panchromatic (P) band. With image sharpening techniques, this higher resolution P data, or as an alternative, the 10-m (or 5-m) P data of the SPOT satellite, can increase the spatial resolution of the multispectral (MS) data. Sharpening requires that the lower resolution MS image be coregistered and resampled to the P data before high spatial frequency information is transferred to the MS data. For visual interpretation and machine classification tasks, it is important that the sharpened data preserve the spectral characteristics of the original low resolution data. A technique was developed for sharpening (in this case, 3:1 spatial resolution enhancement) visible spectral band data, based on a model of the sensor system point spread function (PSF) in order to maintain spectral fidelity. It combines high-pass (HP) filter sharpening methods with iterative image restoration to reduce degradations caused by sensor-system-induced blurring and resembling. Also there is a spectral fidelity requirement: sharpened MS when filtered by the modeled degradations should reproduce the low resolution source MS. Quantitative evaluation of sharpening performance was made by using simulated low resolution data generated from digital color-IR aerial photography. In comparison to the HP-filter-based sharpening method, results for the technique in this paper with simulated data show improved spectral fidelity. Preliminary results with TM 30-m visible band data sharpened with simulated 10-m panchromatic data are promising but require further study.

Landsat-1 and Landsat-2 flight evaluation

NASA Technical Reports Server (NTRS)

1975-01-01

The flight performance of Landsat 1 and Landsat 2 is analyzed. Flight operations of the satellites are briefly summarized. Other topics discussed include: orbital parameters; power subsystem; attitude control subsystem; command/clock subsystem; telemetry subsystem; orbit adjust subsystem; magnetic moment compensating assembly; unified s-band/premodulation processor; electrical interface subsystem; thermal subsystem; narrowband tape recorders; wideband telemetry subsystem; attitude measurement sensor; wideband video tape recorders; return beam vidicon; multispectral scanner subsystem; and data collection subsystem.

Revisiting surface albedo changes over Greenland since 1980s using satellite data from GLASS, CLARA, MODIS, and Landsat

NASA Astrophysics Data System (ADS)

He, T.; Liang, S.; Zhang, Y.

2017-12-01

Massive melting events over Greenland have been observed over the past few decades. Accompanying the melting events are the surface albedo changes, which had temporal and spatial variations. Albedo changes over Greenland during the past few decades have been reported in previous studies with the help of satellite observations; however, magnitudes and timing in albedo trends differ greatly in those studies. This has limited our understanding of albedo change mechanisms over Greenland. In this study, we present an analysis of surface albedo change over Greenland since 1980s combining four satellite albedo datasets, namely MODIS, GLASS, CLARA, and Landsat. MODIS, GLASS, and CLARA albedo data are publicly available and Landsat albedos were derived in our earlier study trying to bridge the scale difference between coarse resolution data and ground measurements available from early 1980s. Inter-comparisons were made among the satellite albedos and against ground measurements. We have several new findings. First, trends in surface albedo change among the satellite albedo datasets generally agree with each other and with ground measurements. Second, all datasets showed negative albedo trends after 2000, but magnitudes differ greatly. Third, trends before 2000 from coarse resolution data are not significant but Landsat data observed positive albedo changes. Fourth, the turning point of albedo trend was found to be earlier than 2000. Those findings may bring new research topics on timing and magnitude, and an improved understanding mechanisms of the albedo changes over Greenland during the past few decades.

Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

NASA Technical Reports Server (NTRS)

Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

2012-01-01

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived

Specification and preliminary design of the CARTA system for satellite cartography

NASA Technical Reports Server (NTRS)

Machadoesilva, A. J. F. (Principal Investigator); Neto, G. C.; Serra, P. R. M.; Souza, R. C. M.; Mitsuo, Fernando Augusta, II

1984-01-01

Digital imagery acquired by satellite have inherent geometrical distortion due to sensor characteristics and to platform variations. In INPE a software system for geometric correction of LANDSAT MSS imagery is under development. Such connected imagery will be useful for map generation. Important examples are the generation of LANDSAT image-charts for the Amazon region and the possibility of integrating digital satellite imagery into a Geographic Information System.

Analysis of Relationship Between Urban Heat Island Effect and Land Use/cover Type Using Landsat 7 ETM+ and Landsat 8 Oli Images

NASA Astrophysics Data System (ADS)

Aslan, N.; Koc-San, D.

2016-06-01

The main objectives of this study are (i) to calculate Land Surface Temperature (LST) from Landsat imageries, (ii) to determine the UHI effects from Landsat 7 ETM+ (June 5, 2001) and Landsat 8 OLI (June 17, 2014) imageries, (iii) to examine the relationship between LST and different Land Use/Land Cover (LU/LC) types for the years 2001 and 2014. The study is implemented in the central districts of Antalya. Initially, the brightness temperatures are retrieved and the LST values are calculated from Landsat thermal images. Then, the LU/LC maps are created from Landsat pan-sharpened images using Random Forest (RF) classifier. Normalized Difference Vegetation Index (NDVI) image, ASTER Global Digital Elevation Model (GDEM) and DMSP_OLS nighttime lights data are used as auxiliary data during the classification procedure. Finally, UHI effect is determined and the LST values are compared with LU/LC classes. The overall accuracies of RF classification results were computed higher than 88 % for both Landsat images. During 13-year time interval, it was observed that the urban and industrial areas were increased significantly. Maximum LST values were detected for dry agriculture, urban, and bareland classes, while minimum LST values were detected for vegetation and irrigated agriculture classes. The UHI effect was computed as 5.6 °C for 2001 and 6.8 °C for 2014. The validity of the study results were assessed using MODIS/Terra LST and Emissivity data and it was found that there are high correlation between Landsat LST and MODIS LST data (r2 = 0.7 and r2 = 0.9 for 2001 and 2014, respectively).

Detecting Water Bodies in LANDSAT8 Oli Image Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, W.; He, G.; Long, T.; Ni, Y.

2018-04-01

Water body identifying is critical to climate change, water resources, ecosystem service and hydrological cycle. Multi-layer perceptron(MLP) is the popular and classic method under deep learning framework to detect target and classify image. Therefore, this study adopts this method to identify the water body of Landsat8. To compare the performance of classification, the maximum likelihood and water index are employed for each study area. The classification results are evaluated from accuracy indices and local comparison. Evaluation result shows that multi-layer perceptron(MLP) can achieve better performance than the other two methods. Moreover, the thin water also can be clearly identified by the multi-layer perceptron. The proposed method has the application potential in mapping global scale surface water with multi-source medium-high resolution satellite data.

Calibration of the Thermal Infrared Sensor on the Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Thome, K; Reuter, D.; Lunsford, D.; Montanaro, M.; Smith, J.; Tesfaye, Z.; Wenny, B.

2011-01-01

The Landsat series of satellites provides the longest running continuous data set of moderate-spatial-resolution imagery beginning with the launch of Landsat 1 in 1972 and continuing with the 1999 launch of Landsat 7 and current operation of Landsats 5 and 7. The Landsat Data Continuity Mission (LDCM) will continue this program into a fourth decade providing data that are keys to understanding changes in land-use changes and resource management. LDCM consists of a two-sensor platform comprised of the Operational Land Imager (OLI) and Thermal Infrared Sensors (TIRS). A description of the applications and design of the TIRS instrument is given as well as the plans for calibration and characterization. Included are early results from preflight calibration and a description of the inflight validation.

Feature Detection Systems Enhance Satellite Imagery

NASA Technical Reports Server (NTRS)

2009-01-01

In 1963, during the ninth orbit of the Faith 7 capsule, astronaut Gordon Cooper skipped his nap and took some photos of the Earth below using a Hasselblad camera. The sole flier on the Mercury-Atlas 9 mission, Cooper took 24 photos - never-before-seen images including the Tibetan plateau, the crinkled heights of the Himalayas, and the jagged coast of Burma. From his lofty perch over 100 miles above the Earth, Cooper noted villages, roads, rivers, and even, on occasion, individual houses. In 1965, encouraged by the effectiveness of NASA s orbital photography experiments during the Mercury and subsequent Gemini manned space flight missions, U.S. Geological Survey (USGS) director William Pecora put forward a plan for a remote sensing satellite program that would collect information about the planet never before attainable. By 1972, NASA had built and launched Landsat 1, the first in a series of Landsat sensors that have combined to provide the longest continuous collection of space-based Earth imagery. The archived Landsat data - 37 years worth and counting - has provided a vast library of information allowing not only the extensive mapping of Earth s surface but also the study of its environmental changes, from receding glaciers and tropical deforestation to urban growth and crop harvests. Developed and launched by NASA with data collection operated at various times by the Agency, the National Oceanic and Atmospheric Administration (NOAA), Earth Observation Satellite Company (EOSAT, a private sector partnership that became Space Imaging Corporation in 1996), and USGS, Landsat sensors have recorded flooding from Hurricane Katrina, the building boom in Dubai, and the extinction of the Aral Sea, offering scientists invaluable insights into the natural and manmade changes that shape the world. Of the seven Landsat sensors launched since 1972, Landsat 5 and Landsat 7 are still operational. Though both are in use well beyond their intended lifespans, the mid

Landsat—Earth observation satellites

USGS Publications Warehouse

,

2015-11-25

Since 1972, Landsat satellites have continuously acquired space-based images of the Earth’s land surface, providing data that serve as valuable resources for land use/land change research. The data are useful to a number of applications including forestry, agriculture, geology, regional planning, and education. Landsat is a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). NASA develops remote sensing instruments and the spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and data distribution. The result of this program is an unprecedented continuing record of natural and human-induced changes on the global landscape.

Landsat imagery: a unique resource

USGS Publications Warehouse

Miller, H.; Sexton, N.; Koontz, L.

2011-01-01

Landsat satellites provide high-quality, multi-spectral imagery of the surface of the Earth. These moderate-resolution, remotely sensed images are not just pictures, but contain many layers of data collected at different points along the visible and invisible light spectrum. These data can be manipulated to reveal what the Earth’s surface looks like, including what types of vegetation are present or how a natural disaster has impacted an area (Fig. 1).

Harmonic regression based multi-temporal cloud filtering algorithm for Landsat 8

NASA Astrophysics Data System (ADS)

Joshi, P.

2015-12-01

Landsat data archive though rich is seen to have missing dates and periods owing to the weather irregularities and inconsistent coverage. The satellite images are further subject to cloud cover effects resulting in erroneous analysis and observations of ground features. In earlier studies the change detection algorithm using statistical control charts on harmonic residuals of multi-temporal Landsat 5 data have been shown to detect few prominent remnant clouds [Brooks, Evan B., et al, 2014]. So, in this work we build on this harmonic regression approach to detect and filter clouds using a multi-temporal series of Landsat 8 images. Firstly, we compute the harmonic coefficients using the fitting models on annual training data. This time series of residuals is further subjected to Shewhart X-bar control charts which signal the deviations of cloud points from the fitted multi-temporal fourier curve. For the process with standard deviation σ we found the second and third order harmonic regression with a x-bar chart control limit [Lσ] ranging between [0.5σ < Lσ < σ] as most efficient in detecting clouds. By implementing second order harmonic regression with successive x-bar chart control limits of L and 0.5 L on the NDVI, NDSI and haze optimized transformation (HOT), and utilizing the seasonal physical properties of these parameters, we have designed a novel multi-temporal algorithm for filtering clouds from Landsat 8 images. The method is applied to Virginia and Alabama in Landsat8 UTM zones 17 and 16 respectively. Our algorithm efficiently filters all types of cloud cover with an overall accuracy greater than 90%. As a result of the multi-temporal operation and the ability to recreate the multi-temporal database of images using only the coefficients of the fourier regression, our algorithm is largely storage and time efficient. The results show a good potential for this multi-temporal approach for cloud detection as a timely and targeted solution for the Landsat 8

Use of dust storm observations on satellite images to identify areas vulnerable to severe wind erosion

USGS Publications Warehouse

Breed, C.S.; McCauley, J.F.

1986-01-01

Blowing dust is symptomatic of severe wind erosion and deterioration of soils in areas undergoing dessication and/or devegetation. Dust plumes on satellite images can commonly be traced to sources in marginally arable semiarid areas where protective lag gravels or vegetation have been removed and soils are dry, as demonstrated for the Portales Valley, New Mexico. Images from Landsat and manned orbiters such as Skylab and the Space Shuttle are useful for illustrating the regional relations of airborne dust plumes to source areas. Geostationary satellites such as GOES are useful in tracking the time-histories of episodic dust storms. These events sometimes go unrecognized by weather observers and are the precursors of long-term land degradation trends. In areas where soil maps and meteorological data are inadequate, satellite images provide a means for identifying problem areas where measures are needed to control or mitigate wind erosion. ?? 1986 D. Reidel Publishing Company.

Land surface temperature distribution and development for green open space in Medan city using imagery-based satellite Landsat 8

NASA Astrophysics Data System (ADS)

Sulistiyono, N.; Basyuni, M.; Slamet, B.

2018-03-01

Green open space (GOS) is one of the requirements where a city is comfortable to stay. GOS might reduce land surface temperature (LST) and air pollution. Medan is one of the biggest towns in Indonesia that experienced rapid development. However, the early development tends to neglect the GOS existence for the city. The objective of the study is to determine the distribution of land surface temperature and the relationship between the normalized difference vegetation index (NDVI) and the priority of GOS development in Medan City using imagery-based satellite Landsat 8. The method approached to correlate the distribution of land surface temperature derived from the value of digital number band 10 with the NDVI which was from the ratio of groups five and four on satellite images of Landsat 8. The results showed that the distribution of land surface temperature in the Medan City in 2016 ranged 20.57 - 33.83 °C. The relationship between the distribution of LST distribution with NDVI was reversed with a negative correlation of -0.543 (sig 0,000). The direction of GOS in Medan City is therefore developed on the allocation of LST and divided into three priority classes namely first priority class had 5,119.71 ha, the second priority consisted of 16,935.76 ha, and third priority of 6,118.50 ha.

Landsat Data Continuity Mission

USGS Publications Warehouse

,

2012-01-01

The Landsat Data Continuity Mission (LDCM) is a partnership formed between the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) to place the next Landsat satellite in orbit in January 2013. The Landsat era that began in 1972 will become a nearly 41-year global land record with the successful launch and operation of the LDCM. The LDCM will continue the acquisition, archiving, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The mission objectives of the LDCM are to (1) collect and archive medium resolution (30-meter spatial resolution) multispectral image data affording seasonal coverage of the global landmasses for a period of no less than 5 years; (2) ensure that LDCM data are sufficiently consistent with data from the earlier Landsat missions in terms of acquisition geometry, calibration, coverage characteristics, spectral characteristics, output product quality, and data availability to permit studies of landcover and land-use change over time; and (3) distribute LDCM data products to the general public on a nondiscriminatory basis at no cost to the user.

Landsat with SRTM Shaded Relief, Los Angeles and Vicinity from Space

NASA Technical Reports Server (NTRS)

2002-01-01

Los Angeles and vicinity seen from space, as viewed by the Landsat 7 satellite from an altitude of 437 miles on May 4, 2001. North is at the top. Topographic shading has been enhanced using an elevation data set acquired by the Space Shuttle Endeavour in February 2000. Downtown Los Angeles is just south of the image center, with L.A. and Long Beach harbors to the south, Santa Monica Bay to the west, San Fernando Valley to the northwest, San Gabriel Valley to the east, and Orange County to the southeast. The San Andreas fault forms the straight diagonal mountain front bordering the Mojave Desert at the top of the image. At full resolution, features on the ground as small as 15 meters (49 feet) across can be distinguished, including street patterns and large buildings, as well as boats and their wakes on the ocean. More than ten million people live within this scene.

This image was generated by first geographically matching the Landsat scene to a Shuttle Radar Topography Mission (SRTM) elevation model. A measure of topographic slope along a southeast-northwest trend was then calculated, such that southeast facing slopes appear bright and northwest facing slopes appear dark. This slope image was then added to the enhanced Landsat scene in order to intensify the appearance of topography. Topographic shading was subtle in the original Landsat scene due to the fairly high sun angle (63 degrees above the horizon) during the satellite overflight in late morning of a mid-Spring day.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and helps in analyzing the large and growing Landsat image archive, managed by the U.S. Geological Survey (USGS).

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the

Evaluation and comparison of the IRS-P6 and the landsat sensors

USGS Publications Warehouse

Chander, G.; Coan, M.J.; Scaramuzza, P.L.

2008-01-01

The Indian Remote Sensing Satellite (IRS-P6), also called ResourceSat-1, was launched in a polar sun-synchronous orbit on October 17, 2003. It carries three sensors: the highresolution Linear Imaging Self-Scanner (LISS-IV), the mediumresolution Linear Imaging Self-Scanner (LISS-III), and the Advanced Wide-Field Sensor (AWiFS). These three sensors provide images of different resolutions and coverage. To understand the absolute radiometric calibration accuracy of IRS-P6 AWiFS and LISS-III sensors, image pairs from these sensors were compared to images from the Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM Plus (ETM+) sensors. The approach involves calibration of surface observations based on image statistics from areas observed nearly simultaneously by the two sensors. This paper also evaluated the viability of data from these nextgeneration imagers for use in creating three National Land Cover Dataset (NLCD) products: land cover, percent tree canopy, and percent impervious surface. Individual products were consistent with previous studies but had slightly lower overall accuracies as compared to data from the Landsat sensors.

Interpretation of a Landsat image of an unusual flood phenomenon in Australia

USGS Publications Warehouse

Robinove, Charles J.

1978-01-01

A Landsat image of part of the flooded area of Cooper Creek, Queensland, Australia, in February 1974, shows large dark areas within the flooded valley. The dark areas are believed to be wet, but unflooded, areas of dark alluvial soil. These striking features, which have not previously been identified on Landsat images, must be properly interpreted so as not to confuse them with clear water.

Cape Town, South Africa, Anaglyph, Landsat Image over SRTM Elevation

NASA Technical Reports Server (NTRS)

2004-01-01

Cape Town and the Cape of Good Hope, South Africa, appear on the left (west) of this anaglyph view generated from a Landsat satellite image and elevation data from the Shuttle Radar Topography Mission (SRTM). The city center is located between Table Bay (upper left) and Table Mountain (just to the south), a 1,086-meter (3,563-foot) tall sandstone and granite natural landmark.

Cape Town enjoys a Mediterranean climate but must deal with the limited water supply characteristic of that climate. Until the 1890s the city relied upon streams and springs along the base of Table Mountain, then built a small reservoir atop Table Mountain to capture and store rainfall there (visible in this anaglyph when viewed at full resolution). Now the needs of a much larger population are met in part by much larger reservoirs such as seen well inland (upper right) at the Theewaterskloof Dam.

False Bay is the large bay to the southeast (lower right) of Cape Town, just around the Cape of Good Hope. It is one of the largest bays along the entire South African coast, but nearby Cape Town has its harbor at Table Bay. False Bay got its name because mariners approaching Cape Town from the east would see the prominent bay and falsely assume it to be the entrance to Cape Town harbor. Similarly, people often mistake the Cape of Good Hope as the southernmost point of Africa. But the southernmost point is actually Cape Agulhas, located just to the southeast (lower right) of this scene.

This anaglyph was created by draping a Landsat visible light image over an SRTM elevation model, and then generating two differing perspectives, one for each eye. When viewed through special glasses, the anaglyph is a vertically exaggerated view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard

Hydrographic charting from Landsat satellite - A comparison with aircraft imagery

NASA Technical Reports Server (NTRS)

Middleton, E. M.; Barker, J. L.

1976-01-01

The relative capabilities of two remote-sensing systems in measuring depth and, consequently, bottom contours in sandy-bottomed and sediment-laden coastal waters were determined quantitatively. The Multispectral Scanner (MSS), orbited on the Landsat-2 satellite, and the Ocean Color Scanner (OCS), flown on U-2 aircraft, were used for this evaluation. Analysis of imagery taken simultaneously indicates a potential for hydrographic charting of marine coastal and shallow shelf areas, even when water turbidity is a factor. Several of the eight optical channels examined on the OCS were found to be sensitive to depth or depth-related information. The greatest sensitivity was in OCS-4 (0.544 plus or minus 0.012 micron) from which contours corresponding to depths up to 12 m were determined. The sharpness of these contours and their spatial stability through time suggests that upwelling radiance is a measure of bottom reflectance and not of water turbidity. The two visible channels on Landsat's MSS were less sensitive in the discrimination of contours, with depths up to 8 m in the high-gain mode (3 X) determined in MSS-4 (0.5 to 0.6 micron).

Hydrographic charting from LANDSAT Satellite: A comparison with aircraft imagery

NASA Technical Reports Server (NTRS)

Middleton, E. M.; Barker, J. L.

1976-01-01

The relative capabilities of two remote-sensing systems in measuring depth and, consequently, bottom contours in sandy-bottomed and sediment-laden coastal waters were determined quantitatively. The multispectral scanner (MSS), orbited on the LANDSAT-2 Satellite, and the ocean color scanner (OCS), flown on U-2 aircraft, were used. Analysis of imagery taken simultaneously indicates a potential for hydrographic charting of marine coastal and shallow shelf areas, even when water turbidity is a factor. Several of the eight optical channels examined on the OCS were found to be sensitive to depth or depth-related information. The greatest sensitivity was in OCS-4(0.544 + or - 0.012 microns) from which contours corresponding to depths up to 12m were determined. The sharpness of these contours and their spatial stability through time suggests that upwelling radiance is a measure of bottom reflectance and not of water turbidity. The two visible channels on LANDSAT's MSS were less sensitive in the discrimination of contours, with depths up to 8m in the high-gain mode (3x) determined in MSS-4(0.5 to 0.6 microns).

Perspective View with Landsat Overlay, Sacramento, Calif.

NASA Technical Reports Server (NTRS)

2002-01-01

California's state capitol, Sacramento, can be seen clustered along the American and Sacramento Rivers in this computer-generated perspective viewed from the west. Folsom Lake is in the center and the Sierra Nevada is above, with the edge of Lake Tahoe just visible at top center.

This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced color Landsat 5satellite image. Topographic expression is exaggerated two times.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR)that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise, Washington, D.C.

Size: scale varies in this perspective image Location: 38.6 deg. North lat., 121.3 deg. West lon. Orientation: looking east Image Data: Landsat Bands 3, 2, 1 as red, green, blue, respectively Original Data Resolution: SRTM 1 arcsecond (30 meters or 98 feet), Thematic Mapper 1 arcsecond (30 meters or 98 feet) Date Acquired: February 2000 (SRTM)

An Overview of the Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Irons, James R.; Dwyer, John L.

2010-01-01

The advent of the Landsat Data Continuity Mission (LDCM), currently with a launch readiness date of December, 2012, will see evolutionary changes in the Landsat data products available from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The USGS initiated a revolution in 2009 when EROS began distributing Landsat data products at no cost to requestors in contrast to the past practice of charging the cost of fulfilling a request; that is, charging $600 per Landsat scene. To implement this drastic change, EROS terminated data processing options for requestors and began to produce all data products using a consistent processing recipe. EROS plans to continue this practice for the LDCM and will required new algorithms to process data from the LDCM sensors. All previous Landsat satellites flew multispectral scanners to collect image data of the global land surface. Additionally, Landsats 4, 5, and 7 flew sensors that acquired imagery for both reflective spectral bands and a single thermal band. In contrast, the LDCM will carry two pushbroom sensors; the Operational Land Imager (OLI) for reflective spectral bands and the Thermal InfraRed Sensor (TIRS) for two thermal bands. EROS is developing the ground data processing system that will both calibrate and correct the data from the thousands of detectors employed by the pushbroom sensors and that will also combine the data from the two sensors to create a single data product with registered data for all of the OLI and TIRS bands.

Satellite image collection optimization

NASA Astrophysics Data System (ADS)

Martin, William

2002-09-01

Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.

Results of 17 Independent Geopositional Accuracy Assessments of Earth Satellite Corporation's GeoCover Landsat Thematic Mapper Imagery. Geopositional Accuracy Validation of Orthorectified Landsat TM Imagery: Northeast Asia

NASA Technical Reports Server (NTRS)

Smith, Charles M.

2003-01-01

This report provides results of an independent assessment of the geopositional accuracy of the Earth Satellite (EarthSat) Corporation's GeoCover, Orthorectified Landsat Thematic Mapper (TM) imagery over Northeast Asia. This imagery was purchased through NASA's Earth Science Enterprise (ESE) Scientific Data Purchase (SDP) program.

Perspective View with Landsat Overlay, Mount Shasta, Calif.

NASA Technical Reports Server (NTRS)

2002-01-01

The volcanic nature of Mount Shasta is clearly evident in this computer-generated perspective viewed from the northwest. At over 4,300 meters (14,000 feet), Mount Shasta is California's tallest volcano and part of the Cascade chain of volcanoes extending south from Washington. The twin summits of Shasta and Shastina tower over a lava flow on the flank of the volcano. Cutting across the lava flow is the bright line of a railroad. The bright area at the right edge is the town of Weed.

This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 5 satellite image. Colors are from Landsat bands 3, 2, and 1 as red, green and blue, respectively. Topographic expression is exaggerated two times.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive.

The Landsat Thematic Mapper image used here came from an online mosaic of Landsat images for the continental United States (http://mapus.jpl.nasa.gov), a part of NASA's Digital Earth effort.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space

Historical Landsat data comparisons: illustrations of the Earth's changing surface

USGS Publications Warehouse

,

1995-01-01

The U.S. Geological Survey's (USGS) EROS Data Center (EDC) has managed the Landsat data archive for more than two decades. This archive provides a rich collection of information about the Earth's land surface. Major changes to the surface of the planet can be detected, measured, and analyzed using Landsat data. The effects of desertification, deforestation, pollution, cataclysmic volcanic activity, and other natural and anthropogenic events can be examined using data acquired from the Landsat series of Earth-observing satellites. The information obtainable from the historical and current Landsat data play a key role in studying surface changes through time. This document provides an overview of the Landsat program and illustrates the application of the data to monitor changes occurring on the surface of the Earth. To reveal changes that have taken place within the past 20 years, pairs and triplicates of images were constructed from the Landsat multispectral scanner (MSS) and thematic mapper (TM) sensors. Landsat MSS data provide a historical record of the Earth's land surface from the early 1970's to the early 1990's. Landsat TM data provide land surface information from the early 1980's to the present.

Improvement in absolute calibration accuracy of Landsat-5 TM with Landsat-7 ETM+ data

USGS Publications Warehouse

Chander, G.; Markham, B.L.; Micijevic, E.; Teillet, P.M.; Helder, D.L.; ,

2005-01-01

The ability to detect and quantify changes in the Earth's environment depends on satellites sensors that can provide calibrated, consistent measurements of Earth's surface features through time. A critical step in this process is to put image data from subsequent generations of sensors onto a common radiometric scale. To evaluate Landsat-5 (L5) Thematic Mapper's (TM) utility in this role, image pairs from the L5 TM and Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors were compared. This approach involves comparison of surface observations based on image statistics from large common areas observed eight days apart by the two sensors. The results indicate a significant improvement in the consistency of L5 TM data with respect to L7 ETM+ data, achieved using a revised Look-Up-Table (LUT) procedure as opposed to the historical Internal Calibrator (IC) procedure previously used in the L5 TM product generation system. The average percent difference in reflectance estimates obtained from the L5 TM agree with those from the L7 ETM+ in the Visible and Near Infrared (VNIR) bands to within four percent and in the Short Wave Infrared (SWIR) bands to within six percent.

Geometric accuracy of LANDSAT-4 MSS image data

NASA Technical Reports Server (NTRS)

Welch, R.; Usery, E. L.

1983-01-01

Analyses of the LANDSAT-4 MSS image data of North Georgia provided by the EDC in CCT-p formats reveal that errors of approximately + or - 30 m in the raw data can be reduced to about + or - 55 m based on rectification procedures involving the use of 20 to 30 well-distributed GCPs and 2nd or 3rd degree polynomial equations. Higher order polynomials do not appear to improve the rectification accuracy. A subscene area of 256 x 256 pixels was rectified with a 1st degree polynomial to yield an RMSE sub xy value of + or - 40 m, indicating that USGS 1:24,000 scale quadrangle-sized areas of LANDSAT-4 data can be fitted to a map base with relatively few control points and simple equations. The errors in the rectification process are caused by the spatial resolution of the MSS data, by errors in the maps and GCP digitizing process, and by displacements caused by terrain relief. Overall, due to the improved pointing and attitude control of the spacecraft, the geometric quality of the LANDSAT-4 MSS data appears much improved over that of LANDSATS -1, -2 and -3.

Application of Geostatistical Simulation to Enhance Satellite Image Products

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David

2004-01-01

With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

SRTM Stereo Pair with Landsat Overlay: Miquelon and Saint Pierre Islands

NASA Technical Reports Server (NTRS)

2000-01-01

This stereoscopic satellite image shows Miquelon and Saint Pierre Islands, located south of Newfoundland, Canada. These islands are a self-governing territory of France. A 'tombolo' (sand bar) unites Grande Miquelon to the north and Petite Miquelon to the south. Saint Pierre Island, located to the lower right, includes a harbor, an airport, and a small town. Glaciers once covered these islands and the direction of glacial flow is evident in the topography as striations and shoreline trends running from the upper right to the lower left. The darkest image features are freshwater lakes that fill glacially carved depressions and saltwater lagoons that are bordered by barrier beaches. The lakes and the lagoons are fairly calm waters and reflect less sunlight than do the wave covered and sediment laden nearshore ocean currents.

This stereoscopic image was generated by draping a Landsat satellite image over a preliminary Shuttle Radar Topography Mission (SRTM)elevation model. Two differing perspectives were then calculated, one for each eye. They can be seen in 3-D by viewing the left image with the right eye and the right image with the left eye (cross-eyed viewing), or by downloading and printing the image pair and viewing them with a stereoscope. When stereoscopically merged, the result is a vertically exaggerated view of the Earth's surface in its full three dimensions.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM project by the United States Geological Survey, Earth Resources Observation Systems (EROS) DataCenter, Sioux Falls, South Dakota.

The elevation data used in this image was acquired by SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar

Earthshots: Satellite images of environmental change – Shanghai, China

USGS Publications Warehouse

Adamson, Thomas

2015-01-01

Much of Shanghai’s growth has been in satellite developments. The Landsat imagery makes this clear as the smaller populated areas outside of Shanghai expand and then are absorbed by the urban expansion.

SRTM Anaglyph with Landsat Overlay: Miquelon and Saint Pierre Islands

NASA Technical Reports Server (NTRS)

2000-01-01

This anaglyph satellite image shows Miquelon and Saint Pierre Islands, located south of Newfoundland, Canada. These islands are a self-governing territory of France. A 'tombolo' (sand bar) unites Grande Miquelon to the north and Petite Miquelon to the south. Saint Pierre Island, located to the lower right, includes a harbor, an airport, and a small town. Glaciers once covered these islands and the direction of glacial flow is evident in the topography as striations and shoreline trends running from the upper right to the lower left. The darkest image features are freshwater lakes that fill glacially carved depressions and saltwater lagoons that are bordered by barrier beaches. The lakes and the lagoons are fairly calm waters and reflect less sunlight than do the wave covered and sediment laden nearshore ocean currents.

The stereoscopic effect was created by first draping a Landsat satellite image over preliminary digital elevation data from the Shuttle Radar Topography Mission (SRTM), and then generating two differing perspectives, one for each eye. When viewed through special glasses, the result is a vertically exaggerated view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM project by the United States Geological Survey, Earth Resources Observation Systems (EROS) DataCenter, Sioux Falls, South Dakota.

The elevation data used in this image was acquired by SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR

Using satellite data in map design and production

USGS Publications Warehouse

Hutchinson, John A.

2002-01-01

Satellite image maps have been produced by the U.S. Geological Survey (USGS) since shortly after the launch of the first Landsat satellite in 1972. Over the years, the use of image data to design and produce maps has developed from a manual and photographic process to one that incorporates geographic information systems, desktop publishing, and digital prepress techniques. At the same time, the content of most image-based maps produced by the USGS has shifted from raw image data to land cover or other information layers derived from satellite imagery, often portrayed in combination with shaded relief.

Use of Semivariances for Studies of Landsat TM Image Textural Properties of Loblolly Pine Forests

Treesearch

Jarek Zawadzki; Chris J. Cieszewski; Roger C. Lowe; Michael Zasada

2005-01-01

We evaluate the applicability of Landsat TM imagery for analyzing textural information of pine forest images by exploring the spatial correlation between pixels measured by semivariances and cross-semivariances calculated from transects of the Landsat TM images. Then, we explore differences in semivariances associated with images of young, middle-aged, and old, and...

Mapping the Distribution and Biomass of Emergent Aquatic Plants in the Sacramento-San Joaquin River Delta of California Using Landsat Imagery Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2015-01-01

This study evaluated the cost-effective and timely use of Landsat imagery to map and monitor emergent aquatic plant biomass and to filter satellite image products for the most probable locations of water hyacinth coverage in the Delta based on field observations collected immediately after satellite image acquisition.

Landsat Data Continuity Mission

USGS Publications Warehouse

,

2007-01-01

The Landsat Data Continuity Mission (LDCM) is a partnership between the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) to place the next Landsat satellite in orbit by late 2012. The Landsat era that began in 1972 will become a nearly 45-year global land record with the successful launch and operation of the LDCM. The LDCM will continue the acquisition, archival, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The mission objectives of the LDCM are to (1) collect and archive medium resolution (circa 30-m spatial resolution) multispectral image data affording seasonal coverage of the global landmasses for a period of no less than 5 years; (2) ensure that LDCM data are sufficiently consistent with data from the earlier Landsat missions, in terms of acquisition geometry, calibration, coverage characteristics, spectral characteristics, output product quality, and data availability to permit studies of land-cover and land-use change over time; and (3) distribute LDCM data products to the general public on a nondiscriminatory basis and at a price no greater than the incremental cost of fulfilling a user request. Distribution of LDCM data over the Internet at no cost to the user is currently planned.

Automated Agricultural Field Extraction from Multi-temporal Web Enabled Landsat Data

NASA Astrophysics Data System (ADS)

Yan, L.; Roy, D. P.

2012-12-01

Agriculture has caused significant anthropogenic surface change. In many regions agricultural field sizes may be increasing to maximize yields and reduce costs resulting in decreased landscape spatial complexity and increased homogenization of land uses with potential for significant biogeochemical and ecological effects. To date, studies of the incidence, drivers and impacts of changing field sizes have not been undertaken over large areas because of computational constraints and because consistently processed appropriate resolution data have not been available or affordable. The Landsat series of satellites provides near-global coverage, long term, and appropriate spatial resolution (30m) satellite data to document changing field sizes. The recent free availability of all the Landsat data in the U.S. Landsat archive now provides the opportunity to study field size changes in a global and consistent way. Commercial software can be used to extract fields from Landsat data but are inappropriate for large area application because they require considerable human interaction. This paper presents research to develop and validate an automated computational Geographic Object Based Image Analysis methodology to extract agricultural fields and derive field sizes from Web Enabled Landsat Data (WELD) (http://weld.cr.usgs.gov/). WELD weekly products (30m reflectance and brightness temperature) are classified into Satellite Image Automatic Mapper™ (SIAM™) spectral categories and an edge intensity map and a map of the probability of each pixel being agricultural are derived from five years of 52 weeks of WELD and corresponding SIAM™ data. These data are fused to derive candidate agriculture field segments using a variational region-based geometric active contour model. Geometry-based algorithms are used to decompose connected segments belonging to multiple fields into coherent isolated field objects with a divide and conquer strategy to detect and merge partial circle

United States forest disturbance trends observed with landsat time series

Treesearch

Jeffrey G. Masek; Samuel N. Goward; Robert E. Kennedy; Warren B. Cohen; Gretchen G. Moisen; Karen Schleweiss; Chengquan Huang

2013-01-01

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing US land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest...

Improving the precision of dynamic forest parameter estimates using Landsat

Treesearch

Evan B. Brooks; John W. Coulston; Randolph H. Wynne; Valerie A. Thomas

2016-01-01

The use of satellite-derived classification maps to improve post-stratified forest parameter estimates is wellestablished.When reducing the variance of post-stratification estimates for forest change parameters such as forestgrowth, it is logical to use a change-related strata map. At the stand level, a time series of Landsat images is

Landsat 6 contract signed

NASA Astrophysics Data System (ADS)

Maggs, William Ward

A new agreement provides $220 million for development and construction of the Landsat 6 remote sensing satellite and its ground systems. The contract, signed on March 31, 1988, by the Department of Commerce (DOC) and the Earth Observation Satellite (EOSAT) Company of Lanham, Md., came just days after approval of DOC's Landsat commercialization plan by subcommittees of the House and Senate appropriations committees.The Landsat 6 spacecraft is due to be launched into orbit on a Titan II rocket in June 1991 from Vandenburg Air Force Base, Calif. The satellite will carry an Enhanced Thematic Mapper (ETM) sensor, an instrument sensitive to electromagnetic radiation in seven ranges or bands of wavelengths. The satellite's payload will also include the Sea Wide Field Sensor (Sea-WiFS), designed to provide information on sea surface temperature and ocean color. The sensor is being developed in a cooperative effort by EOSAT and the National Aeronautics and Space Administration (NASA). A less certain passenger is a proposed 5-m resolution, three-band sensor sensitive to visible light. EOSAT is trying to find both private financing for the device and potential buyers of the high-resolution imagery that it could produce. The company has been actively courting U.S. television networks, which have in the past used imagery from the European Système Probatoire d'Observation de la Terre (SPOT) satellite for news coverage.

An integrated software system for geometric correction of LANDSAT MSS imagery

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Esilva, A. J. F. M.; Camara-Neto, G.; Serra, P. R. M.; Desousa, R. C. M.; Mitsuo, Fernando Augusta, II

1984-01-01

A system for geometrically correcting LANDSAT MSS imagery includes all phases of processing, from receiving a raw computer compatible tape (CCT) to the generation of a corrected CCT (or UTM mosaic). The system comprises modules for: (1) control of the processing flow; (2) calculation of satellite ephemeris and attitude parameters, (3) generation of uncorrected files from raw CCT data; (4) creation, management and maintenance of a ground control point library; (5) determination of the image correction equations, using attitude and ephemeris parameters and existing ground control points; (6) generation of corrected LANDSAT file, using the equations determined beforehand; (7) union of LANDSAT scenes to produce and UTM mosaic; and (8) generation of output tape, in super-structure format.

Perspective View with Landsat Overlay, Mount Shasta, Calif.

NASA Technical Reports Server (NTRS)

2002-01-01

At more than 4,300 meters (14,000 feet ), Mount Shasta is California's tallest volcano and part of the Cascade chain of volcanoes extending south from Washington. This computer-generated perspective viewed from the west also includes Shastina, a slightly smaller volcanic cone left of Shasta's summit and Black Butte, another volcano in the right foreground.

This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced color Landsat 5satellite image. Topographic expression is exaggerated two times.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR)that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise,Washington, D.C.

Size: scale varies in this perspective image Location: 41.4 deg. North lat., 122.3 deg. West lon. Orientation: looking east Image Data: Landsat Bands 3,2,1 as red, green, blue, respectively Original Data Resolution: SRTM 1 arcsecond (30 meters or 98 feet), Thematic Mapper 1 arcsecond

Landsat-1 and Landsat-2 evaluation report, 23 January 1975 to 23 April 1975

NASA Technical Reports Server (NTRS)

1975-01-01

A description of the work accomplished with the Landsat-1 and Landsat-2 satellites during the period 23 Jan. - 23 Apr. 1975 was presented. The following information was given for each satellite: operational summary, orbital parameters, power subsystem, attitude control subsystem, command/clock subsystem, telemetry subsystem, orbit adjust subsystem, magnetic moment compensating assembly, unified S-band/premodulation processor, electrical interface subsystem, thermal subsystem, narrowband tape recorders, wideband telemetry subsystem, attitude measurement sensor, wideband video tape recorders, return beam vidicon, multispectral scanner subsystem, and data collection subsystem.

Application of LANDSAT-2 data to the implementation and enforcement of the Pennsylvania Surface Mining Conservation and Reclamation Act

NASA Technical Reports Server (NTRS)

Russell, O. R. (Principal Investigator); Nichols, D. A.; Anderson, R.

1977-01-01

The author has identified the following significant results. Evaluation of LANDSAT imagery indicates severe limitations in its utility for surface mine land studies. Image stripping resulting from unequal detector response on satellite degrades the image quality to the extent that images of scales larger than 1:125,000 are of limited value for manual interpretation. Computer processing of LANDSAT data to improve image quality is essential; the removal of scanline stripping and enhancement of mine land reflectance data combined with color composite printing permits useful photographic enlargements to approximately 1:60,000.

Developing consistent time series landsat data products

USDA-ARS?s Scientific Manuscript database

The Landsat series satellite has provided earth observation data record continuously since early 1970s. There are increasing demands on having a consistent time series of Landsat data products. In this presentation, I will summarize the work supported by the USGS Landsat Science Team project from 20...

Landsat surface reflectance data

USGS Publications Warehouse

,

2015-01-01

Landsat satellite data have been produced, archived, and distributed by the U.S. Geological Survey since 1972. Users rely on these data for historical study of land surface change and require consistent radiometric data processed to the highest science standards. In support of the guidelines established through the Global Climate Observing System, the U.S. Geological Survey has embarked on production of higher-level Landsat data products to support land surface change studies. One such product is Landsat surface reflectance.

Assessing North American Forest Disturbance from the Landsat Archive

NASA Technical Reports Server (NTRS)

Masek, Jeffrey G.; Wolfe, Robert; Hall, Forrest; Cohen, Warren; Kennedy, Robert; Powell, Scott; Goward, Samuel; Huang, Chengquan; Healey, Sean; Moisen, Gretchen

2007-01-01

Forest disturbances are thought to play a major role in controlling land-atmosphere fluxes of carbon. Under the auspices of the North American Carbon Program, the LEDAPS (Landsat Ecosystem Disturbance Adaptive Processing System) and NACP-FIA projects have been analyzing the Landsat satellite record to assess rates of forest disturbance across North America. In the LEDAPS project, wall-to-wall Landsat imagery for the period 1975-2000 has been converted to surface reflectance and analyzed for decadal losses (disturbance) or gains (regrowth) in biomass using a spectral "disturbance index". The NACP-FIA project relies on a geographic sample of dense Landsat image time series, allowing both disturbance rates and recovery trends to be characterized. Preliminary results for the 1990's indicate high rates of harvest within the southeastern US, Eastern Canada, and the Pacific Northwest, with spatially averaged (approx.50x50 km) turnover periods as low as 25-40 years. Lower rates of disturbance are found in the Rockies and Northeastern US.

Suppression of vegetation in LANDSAT ETM+ remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael

2010-05-01

value and scaling all pixels at each vegetation index level by an amount that shifts the curve to the target digital number (DN). The main drawback of their algorithm is severe distortions of the DN values of non-vegetated areas, a suggested solution is masking outliers such as cloud, water, etc. We therefore extend this algorithm by masking non-vegetated areas. Our algorithm comprises the following three steps: (1) masking of barren or sparsely vegetated areas using a threshold based on a vegetation index that is calculated after atmosphere correction (dark pixel correction and ACTOR were compared) in order to conserve their original spectral information through the subsequent processing; (2) applying Crippen and Blom's forced invariance algorithm to suppress the spectral response of vegetation only in vegetated areas; and (3) combining the processed vegetated areas with the masked barren or sparsely vegetated areas followed by histogram equalization to eliminate the differences in color-scales between these two types of areas, and enhance the integrated image. The output images of both study areas showed significant improvement over the original images in terms of suppression of vegetation reflectance and enhancement of the underlying geological information. The processed images show clear banding, probably associated with lithological variations in the underlying rock formations. The colors of non-vegetated pixels are distorted in the unmasked results but in the same location the pixels in the masked results show regions of higher contrast. We conclude that the algorithm offers an effective way to enhance geological information in LANDSAT TM/ETM+ images of terrains with significant vegetation cover. It is also suitable to other multispectral satellite data have bands in similar wavelength regions. In addition, an application of this method to hyperspectral data may be possible as long as it can provide the vegetation band ratios.

Imaging Spectroscopy Enables Novel Applications and Continuity with the Landsat Record to Sustain Legacy Applications: An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Landsat 8 OLI Case Study

NASA Astrophysics Data System (ADS)

Stavros, E. N.; Seidel, F.; Cable, M. L.; Green, R. O.; Freeman, A.

2017-12-01

While, imaging spectrometers offer additional information that provide value added products for applications that are otherwise underserved, there is need to demonstrate their ability to augment the multi-spectral (e.g., Landsat) optical record by both providing more frequent temporal revisit and lengthening the existing record. Here we test the hypothesis that imaging spectroscopic optical data is compatible with multi-spectral data to within ±5% radiometric accuracy, as desirable to continue the long-term Landsat data record. We use a coincident Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) flight with over-passing Operational Land Imager (OLI) data on Landsat 8 to document a procedure for simulating OLI multi-spectral bands from AVIRIS, evaluate influencing factors on the observed radiance, and assess AVIRIS radiometric accuracy compared to OLI. The procedure for simulating OLI data includes spectral convolution, accounting for atmospheric effects introduced by different sensor altitude and viewing geometries, and spatial resampling. After accounting for these influences, we expect the remaining differences between the simulated and the real OLI data result from differences in sensor calibration, surface bi-directional reflectance, from the different viewing geometries, and spatial sampling. The median radiometric percent difference for each band in the data used range from 0.6% to 8.3%. After bias-correction to minimize potential calibration discrepancies, we find no more than 1.2% radiometric percent difference for any OLI band. This analysis therefore successfully demonstrates that imaging spectrometer data can not only address novel applications, but also contribute to the Landsat-type or other multi-spectral data records to sustain legacy applications.

Characterization of Landsat-7 to Landsat-8 Reflective Wavelength and Normalized Difference Vegetation Index Continuity

NASA Technical Reports Server (NTRS)

Roy, D. P.; Kovalskyy, V.; Zhang, H. K.; Vermote, E. F.; Yan, L.; Kumar, S. S.; Egorov, A.

2016-01-01

At over 40 years, the Landsat satellites provide the longest temporal record of space-based land surface observations, and the successful 2013 launch of the Landsat-8 is continuing this legacy. Ideally, the Landsat data record should be consistent over the Landsat sensor series. The Landsat-8 Operational Land Imager (OLI) has improved calibration, signal to noise characteristics, higher 12-bit radiometric resolution, and spectrally narrower wavebands than the previous Landsat-7 Enhanced Thematic Mapper (ETM+). Reflective wavelength differences between the two Landsat sensors depend also on the surface reflectance and atmospheric state which are difficult to model comprehensively. The orbit and sensing geometries of the Landsat- 8 OLI and Landsat-7 ETM+ provide swath edge overlapping paths sensed only one day apart. The overlap regions are sensed in alternating backscatter and forward scattering orientations so Landsat bi-directional reflectance effects are evident but approximately balanced between the two sensors when large amounts of time series data are considered. Taking advantage of this configuration a total of 59 million 30m corresponding sensor observations extracted from 6,317 Landsat-7 ETM+ and Landsat-8 OLI images acquired over three winter and three summer months for all the conterminous United States (CONUS) are compared. Results considering different stages of cloud and saturation filtering, and filtering to reduce one day surface state differences, demonstrate the importance of appropriate per-pixel data screening. Top of atmosphere (TOA) and atmospherically corrected surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared bands, and derived normalized difference vegetation index (NDVI), are compared and their differences quantified. On average the OLI TOA reflectance is greater than the ETM+ TOA reflectance for all bands, with greatest differences in the near-infrared (NIR) and the shortwave infrared bands

Evaluation of SIR-A (Shuttle Imaging Radar) images from the Tres Marias region (Minas Gerais State, Brazil) using derived spatial features and registration with MSS-LANDSAT images

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Kux, H. J. H.; Dutra, L. V.

1984-01-01

Two image processing experiments are described using a MSS-LANDSAT scene from the Tres Marias region and a shuttle Imaging Radar SIR-A image digitized by a vidicon scanner. In the first experiment the study area is analyzed using the original and preprocessed SIR-A image data. The following thematic classes are obtained: (1) water, (2) dense savanna vegetation, (3) sparse savanna vegetation, (4) reforestation areas and (5) bare soil areas. In the second experiment, the SIR-A image was registered together with MSS-LANDSAT bands five, six, and seven. The same five classes mentioned above are obtained. These results are compared with those obtained using solely MSS-LANDSAT data. The spatial information as well as coregistered SIR-A and MSS-LANDSAT data can increase the separability between classes, as compared to the use of raw SIR-A data solely.

Determining the area of influence of depression cone in the vicinity of lignite mine by means of triangle method and LANDSAT TM/ETM+ satellite images.

PubMed

Zawadzki, Jarosław; Przeździecki, Karol; Miatkowski, Zygmunt

2016-01-15

Problems with lowering of water table are common all over the world. Intensive pumping of water from aquifers for consumption, irrigation, industrial or mining purposes often causes groundwater depletion and results in the formation of cone of depression. This can severely decrease water pressure, even over vast areas, and can create severe problems such as degradation of agriculture or natural environment sometimes depriving people and animals of water supply. In this paper, the authors present a method for determining the area of influence of a groundwater depression cone resulting from prolonged drainage, by means of satellite images in optical, near infrared and thermal infrared bands from TM sensor (Thematic Mapper) and ETM+ sensor (Enhanced Thematic Mapper +) placed on Landsat 5 and Landsat 7 satellites. The research area was Szczercowska Valley (Pol. Kotlina Szczercowska), Central Poland, located within a range of influence of a groundwater drainage system of the lignite coal mine in Belchatow. It is the biggest lignite coal mine in Poland and one of the largest in Europe exerting an enormous impact on the environment. The main method of satellite data analysis for determining soil moisture, was the so-called triangle method. This method, based on TVDI (Temperature Vegetation Dryness Index) was supported by additional spatial analysis including ordinary kriging used in order to combine fragmentary information obtained from areas covered by meadows. The results obtained are encouraging and confirm the usefulness of the triangle method not only for soil moisture determination but also for assessment of the temporal and spatial changes in the area influenced by the groundwater depression cone. The range of impact of the groundwater depression cone determined by means of above-described remote sensing analysis shows good agreement with that determined by ground measurements. The developed satellite method is much faster and cheaper than in-situ measurements

Landsat data availability from the EROS Data Center and status of future plans

USGS Publications Warehouse

Pohl, Russell A.; Metz, G.G.

1977-01-01

The Department of Interior's EROS Data Center, managed by the U.S. Geological Survey, was established in 1972, in Sioux Falls, South Dakota, to serve as a principal dissemination facility for Landsat and other remotely Sensed data. Through the middle of 1977, the Center has supplied approximately 1.7 million copies of images from the more than 5 million images of the Earth's surface archived at the Center. Landsat accounted for half of these images plus approximately 5,800 computer-compatible tapes of Landsat data were also supplied to users. New methods for processing data products to make them more useful are being developed, and new accession aids for determining data availability are being placed in operation. The Center also provides assistance and training to resource specialists and land managers in the use of Landsat and other remotely sensed data. A Data Analysis Laboratory is operated at the Center to provide both digital and analog multispectral/multitemporal image analysis capabilities in support of the training and assistance programs. In addition to conventionally processed data products, radiometrically enhanced Landsat imagery are now available from the Center in limited quantities. In mid-1978, the Center will convert to an all-digital processing system for Landsat data that will provide improved products for user analysis in production quantities. The Department of Interior and NASA are currently studying concepts that use communication satellites to relay Landsat data between U.S. ground stations, Goddard Space Flight Center and the EROS Data Center which would improve the timeliness of data availability. The Data Center also works closely with the remote sensing programs and Landsat data receiving and processing facilities being developed in foreign countries.

Satellite Image Mosaic Engine

NASA Technical Reports Server (NTRS)

Plesea, Lucian

2006-01-01

A computer program automatically builds large, full-resolution mosaics of multispectral images of Earth landmasses from images acquired by Landsat 7, complete with matching of colors and blending between adjacent scenes. While the code has been used extensively for Landsat, it could also be used for other data sources. A single mosaic of as many as 8,000 scenes, represented by more than 5 terabytes of data and the largest set produced in this work, demonstrated what the code could do to provide global coverage. The program first statistically analyzes input images to determine areas of coverage and data-value distributions. It then transforms the input images from their original universal transverse Mercator coordinates to other geographical coordinates, with scaling. It applies a first-order polynomial brightness correction to each band in each scene. It uses a data-mask image for selecting data and blending of input scenes. Under control by a user, the program can be made to operate on small parts of the output image space, with check-point and restart capabilities. The program runs on SGI IRIX computers. It is capable of parallel processing using shared-memory code, large memories, and tens of central processing units. It can retrieve input data and store output data at locations remote from the processors on which it is executed.

Nyiragongo Volcano, Congo, Map View with Lava, Landsat / ASTER / SRTM

NASA Technical Reports Server (NTRS)

2002-01-01

The Nyiragongo volcano in the Congo erupted on January 17, 2002, and subsequently sent streams of lava into the city of Goma on the north shore of Lake Kivu. More than 100 people were killed, more than 12,000 homes were destroyed, and hundreds of thousands were forced to flee the broader community of nearly half a million people. This Landsat satellite image shows the volcano (right of center), the city of Goma, and surrounding terrain. Image data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite were used to supply a partial map of the recent lava flows (red overlay), including a complete mapping of their intrusion into Goma as of January 28, 2002. Lava is also apparent within the volcanic crater and at a few other locations. Thick (but broken) cloud cover during the ASTER image acquisition prevented a complete mapping of the lava distribution, but future image acquisitions should complete the mapping.

Goma has a light pink speckled appearance along the shore of Lake Kivu. The city airport parallels, and is just right (east) of, the larger lava flow. Nyiragongo peaks at about 3,470 meters (11,380 feet) elevation and reaches almost exactly 2,000 meters (6,560 feet) above Lake Kivu. The shorter but much broader Nyamuragira volcano appears in the upper left.

Goma, Lake Kivu, Nyiragongo, Nyamuragira and other nearby volcanoes sit within the East African Rift Valley, a zone where tectonic processes are cracking, stretching, and lowering the Earth's crust. Volcanic activity is common here, and older but geologically recent lava flows (magenta in this depiction) are particularly apparent on the flanks of the Nyamuragira volcano.

The Landsat image used here was acquired on December 11, 2001, about a month before the eruption, and shows an unusually cloud-free view of this tropical terrain. Minor clouds and their shadows were digitally removed to clarify the view and topographic shading derived from the SRTM

Monitoring of suspended sediment variation using Landsat and MODIS in the Saemangeum coastal area of Korea.

PubMed

Min, Jee-Eun; Ryu, Joo-Hyung; Lee, Seok; Son, Seunghyun

2012-02-01

Suspended sediment concentration (SS) is an important indicator of marine environmental changes due to natural causes such as tides, tidal currents, and river discharges, as well as human activities such as construction in coastal regions. In the Saemangeum area on the west coast of Korea, construction of a huge tidal dyke for land reclamation has strongly influenced the coastal environment. This study used remotely sensed data to analyze the SS changes in coastal waters caused by the dyke construction. Landsat and MODIS satellite images were used for the spatial analysis of finer patterns and for the detailed temporal analysis, respectively. Forty Landsat scenes and 105 monthly composite MODIS images observed during 1985-2010 were employed, and four field campaigns (from 2005 to 2006) were performed to verify the image-derived SS. The results of the satellite data analyses showed that the seawater was clear before the dyke construction, with SS values lower than 20 g/m(3). These values increased continuously as the dyke construction progressed. The maximum SS values appeared just before completion of the fourth dyke. Values decreased to below 5 g/m(3) after dyke construction. These changes indicated tidal current modification. Some eddies and plumes were observed in the images generated from Landsat data. Landsat and MODIS can reveal that coastal water turbidity was greatly reduced after completion of the construction. Copyright © 2011 Elsevier Ltd. All rights reserved.

Salish Kootenai College Student Internship With the Landsat Data Continuity Mission: A Student's Perspective

NASA Astrophysics Data System (ADS)

Fisher, R.

2004-12-01

Hello my name is Richard D. Fisher. I was very fortunate to be picked to travel to Washington DC in July 2004, to complete a five week internship at NASA. My internship project is located on the Flathead Reservation and the area is called the Jocko-Spring Creek. My project was to complete land cover classification and land cover change detection. In order for me to accomplish my goals I had to learn how to use two new computer programs, MultiSpec and ENVI (Environment for Viewing Images) for remote sensing processing. Computer use does not come easy to me because, I lack the training most people take for granted. However, I did not let this lack of training get me down. The first step was to acquire two Landsat images. The first image was from the Landsat 7, landsat satellite in 1999 and the other was from the Landsat 5 satellite in 1987. The path row for my study area is 41-27. Once the images were acquired I had to combine the different color bands to make one image and perform a blue band correction. The blue band correction takes the blue haze out of the images making them clearer. The visible bands are blue, green, red and three bands of infrared. Once these color bands are together you can change the color of the image to help you look for different features, because each different color band will show you something different. After I put the images together I used ENVI to do the land cover classifications. The next step was to subset my project area to a smaller size. I cut both images in exactly the same coordinates. With help from my NASA mentor scientist, Rich Irish from the Landsat Data Continuity Mission, and I used photo shop Adobe PhotoShop to do the subsetting of both images. We were able to then link the two images together using ENVI software. After that I started to analyze the different pixels and their colors. I classified each image starting with the areas I knew from the fieldwork. After the classifications on both images were complete and I

Downscaling of Seasonal Landsat-8 and MODIS Land Surface Temperature (LST) in Kolkata, India

NASA Astrophysics Data System (ADS)

Garg, R. D.; Guha, S.; Mondal, A.; Lakshmi, V.; Kundu, S.

2017-12-01

The quality of life of urban people is affected by urban heat environment. The urban heat studies can be carried out using remotely sensed thermal infrared imagery for retrieving Land Surface Temperature (LST). Currently, high spatial resolution (<200 m) thermal images are limited and their temporal resolution is low (e.g., 17 days of Landsat-8). Coarse spatial resolution (1000 m) and high temporal resolution (daily) thermal images of MODIS (Moderate Resolution Imaging Spectroradiometer) are frequently available. The present study is to downscale spatially coarser resolution of the thermal image to fine resolution thermal image using regression based downscaling technique. This method is based on the relationship between (LST) and vegetation indices (e.g., Normalized Difference Vegetation Index or NDVI) over a heterogeneous landscape. The Kolkata metropolitan city, which experiences a tropical wet-and-dry type of climate has been selected for the study. This study applied different seasonal open source satellite images viz., Landsat-8 and Terra MODIS. The Landsat-8 images are aggregated at 960 m resolution and downscaled into 480, 240 120 and 60 m. Optical and thermal resolution of Landsat-8 and MODIS are 30 m and 60 m; 250 m and 1000 m respectively. The homogeneous land cover areas have shown better accuracy than heterogeneous land cover areas. The downscaling method plays a crucial role while the spatial resolution of thermal band renders it unable for advanced study. Key words: Land Surface Temperature (LST), Downscale, MODIS, Landsat, Kolkata

Landsat 3 return beam vidicon response artifacts

USGS Publications Warehouse

,; Clark, B.

1981-01-01

The return beam vidicon (RBV) sensing systems employed aboard Landsats 1, 2, and 3 have all been similar in that they have utilized vidicon tube cameras. These are not mirror-sweep scanning devices such as the multispectral scanner (MSS) sensors that have also been carried aboard the Landsat satellites. The vidicons operate more like common television cameras, using an electron gun to read images from a photoconductive faceplate.In the case of Landsats 1 and 2, the RBV system consisted of three such vidicons which collected remote sensing data in three distinct spectral bands. Landsat 3, however, utilizes just two vidicon cameras, both of which sense data in a single broad band. The Landsat 3 RBV system additionally has a unique configuration. As arranged, the two cameras can be shuttered alternately, twice each, in the same time it takes for one MSS scene to be acquired. This shuttering sequence results in four RBV "subscenes" for every MSS scene acquired, similar to the four quadrants of a square. See Figure 1. Each subscene represents a ground area of approximately 98 by 98 km. The subscenes are designated A, B, C, and D, for the northwest, northeast, southwest, and southeast quarters of the full scene, respectively. RBV data products are normally ordered, reproduced, and sold on a subscene basis and are in general referred to in this way. Each exposure from the RBV camera system presents an image which is 98 km on a side. When these analog video data are subsequently converted to digital form, the picture element, or pixel, that results is 19 m on a side with an effective resolution element of 30 m. This pixel size is substantially smaller than that obtainable in MSS images (the MSS has an effective resolution element of 73.4 m), and, when RBV images are compared to equivalent MSS images, better resolution in the RBV data is clearly evident. It is for this reason that the RBV system can be a valuable tool for remote sensing of earth resources.Until recently

Imager-to-Radiometer In-flight Cross Calibration: RSP Radiometric Comparison with Airborne and Satellite Sensors

NASA Technical Reports Server (NTRS)

McCorkel, Joel; Cairns, Brian; Wasilewski, Andrzej

2016-01-01

This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP), which takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.

Downscaling of Aircraft-, Landsat-, and MODIS-based Land Surface Temperature Images with Support Vector Machines

NASA Astrophysics Data System (ADS)

Ha, W.; Gowda, P. H.; Oommen, T.; Howell, T. A.; Hernandez, J. E.

2010-12-01

High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at several spectral bandwidths including visible, near-infrared (NIR), shortwave-infrared, and thermal-infrared (TIR). The TIR images usually have coarser spatial resolutions than those from non-thermal infrared bands. Due to this technical constraint of the satellite sensors on these platforms, image downscaling has been proposed in the field of ET remote sensing. This paper explores the potential of the Support Vector Machines (SVM) to perform downscaling of LST images derived from aircraft (4 m spatial resolution), TM (120 m), and MODIS (1000 m) using normalized difference vegetation index images derived from simultaneously acquired high resolution visible and NIR data (1 m for aircraft, 30 m for TM, and 250 m for MODIS). The SVM is a new generation machine learning algorithm that has found a wide application in the field of pattern recognition and time series analysis. The SVM would be ideally suited for downscaling problems due to its generalization ability in capturing non-linear regression relationship between the predictand and the multiple predictors. Remote sensing data acquired over the Texas High Plains during the 2008 summer growing season will be used in this study. Accuracy assessment of the downscaled 1, 30, and 250 m LST images will be made by comparing them with LST data measured with infrared thermometers at a small spatial scale, upscaled 30 m aircraft-based LST images, and upscaled 250 m TM-based LST images, respectively.

Study a Relation Between the Lascar Volcano Microseimicity and Changes in the Local System of Lineaments, Obtained Using the Landsat 8 Images.

NASA Astrophysics Data System (ADS)

Arellano-Baeza, A. A.; Soto-Pinto, C. A.

2014-12-01

Over the last decades strong efforts have been made to apply new spaceborn technologies to the study of volcanic activity. Recent studies have shown that the high resolution satellite images can be very useful for tracking of evolution of the stress patterns related to the volcanic activity. It can be done by observing the changes in density and orientation of lineaments extracted from satellite images. A lineament is generally defined as a straight or a somewhat curved feature in the landscape visible in a satellite image as an aligned sequence of pixels of a contrasting intensity compared to the background. The system of lineaments extracted from the satellite images is not identical to the geological lineaments which are usually determined by land-based surveys, nevertheless, it generally reflects the structure of the faults and fractures in the Earth's crust. For this study the lineaments were detected using the ADALGEO software, based on the Hough transform (Soto-Pinto et al, 2013). A temporal sequence of the Landsat 8 multispectral images of the Lascar volcano, located in the North of Chile, was used to study changes in lineament configuration during 2013-2014. It was found that, the number and orientation of lineaments is affected by microseimicity. In particular, it was found that often the density of lineaments decreases with the intensity of microseisms, which could be related to the volcano inflation.

Officials mark Landsat fortieth anniversary with look toward the future

NASA Astrophysics Data System (ADS)

Showstack, Randy

2012-07-01

With the first Landsat satellite having launched 40 years ago and the Landsat Data Continuity Mission (LDCM) on track to launch from Vandenberg Air Force Base, Calif., on 11 February 2013, officials from several U.S. federal science agencies took stock of some of the accomplishments of Landsat (the world's longest running Earth-observing satellite program), announced new tools for scientists working with Landsat data, and discussed some of the challenges facing the program during a 23 July briefing at the Newseum in Washington, D. C.

Spatial and spectral simulation of LANDSAT images of agricultural areas

NASA Technical Reports Server (NTRS)

Pont, W. F., Jr. (Principal Investigator)

1982-01-01

A LANDSAT scene simulation capability was developed to study the effects of small fields and misregistration on LANDSAT-based crop proportion estimation procedures. The simulation employs a pattern of ground polygons each with a crop ID, planting date, and scale factor. Historical greenness/brightness crop development profiles generate the mean signal values for each polygon. Historical within-field covariances add texture to pixels in each polygon. The planting dates and scale factors create between-field/within-crop variation. Between field and crop variation is achieved by the above and crop profile differences. The LANDSAT point spread function is used to add correlation between nearby pixels. The next effect of the point spread function is to blur the image. Mixed pixels and misregistration are also simulated.

Satellite Images and Aerial Photographs of the Effects of Hurricanes Katrina and Rita on Coastal Louisiana

USGS Publications Warehouse

Barras, John A.

2007-01-01

Introduction Hurricane Katrina made landfall on the eastern coastline of Louisiana on August 29, 2005; Hurricane Rita made landfall on the western coastline of Louisiana on September 24, 2005. Comparison of Landsat Thematic Mapper (TM) satellite imagery acquired before and after the landfalls of Katrina and Rita and classified to identify land and water demonstrated that water area increased by 217 mi2 (562 km2) in coastal Louisiana as a result of the storms. Approximately 82 mi2 (212 km2) of new water areas were in areas primarily impacted by Hurricane Katrina (Mississippi River Delta basin, Breton Sound basin, Pontchartrain basin, and Pearl River basin), whereas 99 mi2 (256 km2) were in areas primarily impacted by Hurricane Rita (Calcasieu/Sabine basin, Mermentau basin, Teche/Vermilion basin, Atchafalaya basin, and Terrebonne basin). Barataria basin contained new water areas caused by both hurricanes, resulting in some 18 mi2 (46.6 km2) of new water areas. The fresh marsh and intermediate marsh communities' land areas decreased by 122 mi2 (316 km2) and 90 mi2 (233.1 km2), respectively, and the brackish marsh and saline marsh communities' land areas decreased by 33 mi2 (85.5 km2) and 28 mi2 (72.5 km2), respectively. These new water areas represent land losses caused by direct removal of wetlands. They also indicate transitory changes in water area caused by remnant flooding, removal of aquatic vegetation, scouring of marsh vegetation, and water-level variation attributed to normal tidal and meteorological variation between satellite images. Permanent losses cannot be estimated until several growing seasons have passed and the transitory impacts of the hurricanes are minimized. The purpose of this study was to provide preliminary information on water area changes in coastal Louisiana acquired shortly after the landfalls of both hurricanes (detectable with Landsat TM imagery) and to serve as a regional baseline for monitoring posthurricane wetland recovery. The land

The Landsat Data Continuity Mission Operational Land Imager: Radiometric Performance

NASA Technical Reports Server (NTRS)

Markham, Brian; Dabney, Philip; Pedelty, Jeffrey

2011-01-01

The Operational Land Imager (OLI) is one of two instruments to fly on the Landsat Data Continuity Mission (LDCM), which is scheduled to launch in December 2012 to become the 8th in the series of Landsat satellites. The OLI images in the solar reflective part of the spectrum, with bands similar to bands 1-5, 7 and the panchromatic band on the Landsat-7 ETM+ instrument. In addition, it has a 20 nm bandpass spectral band at 443 nm for coastal and aerosol studies and a 30 nm band at 1375 nm to aid in cirrus cloud detection. Like ETM+, spatial resolution is 30 m in the all but the panchromatic band, which is 15 meters. OLI is a pushbroom radiometer with approximately 6000 detectors per 30 meter band as opposed to the 16 detectors per band on the whiskbroom ETM+. Data are quantized to 12 bits on OLI as opposed to 8 bits on ETM+ to take advantage of the improved signal to noise ratio provided by the pushbroom design. The saturation radiances are higher on OLI than ETM+ to effectively eliminate saturation issues over bright Earth targets. OLI includes dual solar diffusers for on-orbit absolute and relative (detector to detector) radiometric calibration. Additionally, OLI has 3 sets of on-board lamps that illuminate the OLI focal plane through the full optical system, providing additional checks on the OLI's response[l]. OLI has been designed and built by Ball Aerospace & Technology Corp. (BATC) and is currently undergoing testing and calibration in preparation for delivery in Spring 2011. Final pre-launch performance results should be available in time for presentation at the conference. Preliminary results will be presented below. These results are based on the performance of the Engineering Development Unit (EDU) that was radiometrically tested at the integrated instrument level in 2010 and assembly level measurements made on the flight unit. Signal-to-Noise (SNR) performance: One of the advantages of a pushbroom system is the increased dwell time of the detectors

Use of high-resolution satellite images for detection of geological structures related to Central Andes geothermal field, Chile.

NASA Astrophysics Data System (ADS)

Benavides-Rivas, C. L.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.

2014-12-01

Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT 8 satellite have been used to delineate the geological structures related to the potential geothermal reservoirs located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique, using the ADALGEO software, developed by [Soto et al., 2013]. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields. A lineament is generally defined as a straight or slightly curved feature in the landscape visible satellite image as an aligned sequence of pixel intensity contrast compared to the background. The system features extracted from satellite images is not identical to the geological lineaments that are generally determined by ground surveys, however, generally reflects the structure of faults and fractures in the crust. A temporal sequence of eight Landsat multispectral images of Central Andes geothermal field, located in VI region de Chile, was used to study changes in the configuration of the lineaments during 2011. The presence of minerals with silicification, epidotization, and albitization, which are typical for geothrmal reservoirs, was also identified, using their spectral characteristics, and subsequently corroborated in the field. Both lineament analysis and spectral analysis gave similar location of the reservoir, which increases reliability of the results.

Landsat 4 and 5 status and results from Thematic Mapper data analyses

NASA Technical Reports Server (NTRS)

Salomonson, V. V.

1984-01-01

Landsat-1, 2, and 3 have functioned successfully well beyond their design lifetimes of one year and provided a very sizable collection of data. On July 16, 1982 with the successful launch of Landsat-4, a second generation of Landsat satellites was introduced. Landsat-4 continues to make available the observational services which had been provided by the Multispectral Scanner (MSS) on Landsats 1-3. In addition, the new satellite is provided with an improved observational capability which is based on a utilization of the Thematic Mapper (TM). The system status (March 1984) of Landsat-4 is considered along with an evaluation of the MSS, and a description of the design and performance of the TM. Attention is also given to the satellite Landsat-5, which was launched successfully on March 1, 1984, taking into account design modifications leading to improved performance and some scenes provided by the new spacecraft.

LANDSAT data preprocessing

NASA Technical Reports Server (NTRS)

Austin, W. W.

1983-01-01

The effect on LANDSAT data of a Sun angle correction, an intersatellite LANDSAT-2 and LANDSAT-3 data range adjustment, and the atmospheric correction algorithm was evaluated. Fourteen 1978 crop year LACIE sites were used as the site data set. The preprocessing techniques were applied to multispectral scanner channel data and transformed data were plotted and used to analyze the effectiveness of the preprocessing techniques. Ratio transformations effectively reduce the need for preprocessing techniques to be applied directly to the data. Subtractive transformations are more sensitive to Sun angle and atmospheric corrections than ratios. Preprocessing techniques, other than those applied at the Goddard Space Flight Center, should only be applied as an option of the user. While performed on LANDSAT data the study results are also applicable to meteorological satellite data.

Regional forest land cover characterisation using medium spatial resolution satellite data

USGS Publications Warehouse

Huang, Chengquan; Homer, Collin G.; Yang, Limin; Wulder, Michael A.; Franklin, Steven E.

2003-01-01

Increasing demands on forest resources require comprehensive, consistent and up-to-date information on those resources at spatial scales appropriate for management decision-making and for scientific analysis. While such information can be derived using coarse spatial resolution satellite data (e.g. Tucker et al. 1984; Zhu and Evans 1994; Cihlar et al. 1996; Cihlar et al., Chapter 12), many regional applications require more spatial and thematic details than can be derived by using coarse resolution imagery. High spatial resolution satellite data such as IKONOS and Quick Bird images (Aplin et al. 1997), though usable for deriving detailed forest information (Culvenor, Chapter 9), are currently not feasible for wall-to-wall regional applications because of extremely high data cost, huge data volume, and lack of contiguous coverage over large areas. Forest studies over large areas have often been accomplished using data acquired by intermediate spatial resolution sensor systems, including the Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) of Landsat, the High Resolution Visible (HRV) of the Systeme Pour l'Observation de la Terre (SPOT), and the Linear Image Self-Scanner (LISS) of the Indian Remote Sensing satellite. These sensor systems are more appropriate for regional applications because they can routinely produce spatially contiguous data over large areas at relatively low cost, and can be used to derive a host of forest attributes (e.g. Cohen et al. 1995; Kimes et al. 1999; Cohen et al. 2001; Huang et al. 2001; Sugumaran 2001). Of the above intermediate spatial resolution satellites, Landsat is perhaps the most widely used in various types of land remote sensing applications, in part because it has provided more extensive spatial and temporal coverage of the globe than any other intermediate resolution satellite. Spatially contiguous Landsat data have been developed for many regions of the globe (e.g. Lunetta and

LANDSAT image studies as applied to petroleum exploration in Kenya

NASA Technical Reports Server (NTRS)

Miller, J. B.

1975-01-01

The Chevron-Kenya oil license, acquired in 1972, covers an area at the north end of the Lamu Embayment. Immediately after acquisition, a photogeologic study of the area was made followed by a short field inspection. An interpretation of LANDSAT-1 images as a separate attempt to improve geological knowledge was completed. The method used in the image study, the multispectral characteristics of rock units and terrain, and the observed anomalous features as seen in the LANDSAT imagery are described. It was found that the study helped to define the relationship of the Lamu Embayment and its internal structure with surrounding regional features, such as the East Africa rifting, the Rudolf Trough, the Bur Acaba structural ridge, and the Ogaden Basin.

Perspective View with Landsat Overlay, Palm Springs, Calif.

NASA Technical Reports Server (NTRS)

2002-01-01

The city of Palm Springs nestles at the base of Mount San Jacinto in this computer-generated perspective viewed from the east. The many golf courses in the area show up as irregular green areas while the two prominent lines passing through the middle of the image are Interstate 10 and the adjacent railroad tracks. The San Andreas Fault passes through the middle of the sandy Indio Hills in the foreground.

This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced color Landsat 5satellite image. Topographic expression is exaggerated two times.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR)that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise,Washington, D.C.

Size: scale varies in this perspective image Location: 33.8 deg. North lat., 116.3 deg. West lon. Orientation: looking west Image Data: Landsat Bands 3, 2, 1 as red, green, blue, respectively Original Data Resolution: SRTM 1 arcsecond

Landsat real-time processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, E.L.

A novel method for performing real-time acquisition and processing Landsat/EROS data covers all aspects including radiometric and geometric corrections of multispectral scanner or return-beam vidicon inputs, image enhancement, statistical analysis, feature extraction, and classification. Radiometric transformations include bias/gain adjustment, noise suppression, calibration, scan angle compensation, and illumination compensation, including topography and atmospheric effects. Correction or compensation for geometric distortion includes sensor-related distortions, such as centering, skew, size, scan nonlinearity, radial symmetry, and tangential symmetry. Also included are object image-related distortions such as aspect angle (altitude), scale distortion (altitude), terrain relief, and earth curvature. Ephemeral corrections are also applied to compensatemore » for satellite forward movement, earth rotation, altitude variations, satellite vibration, and mirror scan velocity. Image enhancement includes high-pass, low-pass, and Laplacian mask filtering and data restoration for intermittent losses. Resource classification is provided by statistical analysis including histograms, correlational analysis, matrix manipulations, and determination of spectral responses. Feature extraction includes spatial frequency analysis, which is used in parallel discriminant functions in each array processor for rapid determination. The technique uses integrated parallel array processors that decimate the tasks concurrently under supervision of a control processor. The operator-machine interface is optimized for programming ease and graphics image windowing.« less

Landsat TM image maps of the Shirase and Siple Coast ice streams, West Antarctica

USGS Publications Warehouse

Ferrigno, Jane G.; Mullins, Jerry L.; Stapleton, Jo Anne; Bindschadler, Robert; Scambos, Ted A.; Bellisime, Lynda B.; Bowell, Jo-Ann; Acosta, Alex V.

1994-01-01

Fifteen 1: 250000 and one 1: 1000 000 scale Landsat Thematic Mapper (TM) image mosaic maps are currently being produced of the West Antarctic ice streams on the Shirase and Siple Coasts. Landsat TM images were acquired between 1984 and 1990 in an area bounded approximately by 78°-82.5°S and 120°- 160° W. Landsat TM bands 2, 3 and 4 were combined to produce a single band, thereby maximizing data content and improving the signal-to-noise ratio. The summed single band was processed with a combination of high- and low-pass filters to remove longitudinal striping and normalize solar elevation-angle effects. The images were mosaicked and transformed to a Lambert conformal conic projection using a cubic-convolution algorithm. The projection transformation was controled with ten weighted geodetic ground-control points and internal image-to-image pass points with annotation of major glaciological features. The image maps are being published in two formats: conventional printed map sheets and on a CD-ROM.

Los Alamos Fires From Landsat 7

NASA Technical Reports Server (NTRS)

2002-01-01

On May 9, 2000, the Landsat 7 satellite acquired an image of the area around Los Alamos, New Mexico. The Landsat 7 satellite acquired this image from 427 miles in space through its sensor called the Enhanced Thematic Mapper Plus (ETM+). Evident within the imagery is a view of the ongoing Cerro Grande fire near the town of Los Alamos and the Los Alamos National Laboratory. Combining the high-resolution (30 meters per pixel in this scene) imaging capacity of ETM+ with its multi-spectral capabilities allows scientists to penetrate the smoke plume and see the structure of the fire on the surface. Notice the high-level of detail in the infrared image (bottom), in which burn scars are clearly distinguished from the hotter smoldering and flaming parts of the fire. Within this image pair several features are clearly visible, including the Cerro Grande fire and smoke plume, the town of Los Alamos, the Los Alamos National Laboratory and associated property, and Cerro Grande peak. Combining ETM+ channels 7, 4, and 2 (one visible and two infrared channels) results in a false color image where vegetation appears as bright to dark green (bottom image). Forested areas are generally dark green while herbaceous vegetation is light green. Rangeland or more open areas appear pink to light purple. Areas with extensive pavement or urban development appear light blue or white to purple. Less densely-developed residential areas appear light green and golf courses are very bright green. The areas recently burned appear black. Dark red to bright red patches, or linear features within the burned area, are the hottest and possibly actively burning areas of the fire. The fire is spreading downslope and the front of the fire is readily detectable about 2 kilometers to the west and south of Los Alamos. Combining ETM+ channels 3, 2, and 1 provides a true-color image of the greater Los Alamos region (top image). Vegetation is generally dark to medium green. Forested areas are very dark green

Analysis of LANDSAT-4 TM Data for Lithologic and Image Mapping Purpose

NASA Technical Reports Server (NTRS)

Podwysocki, M. H.; Salisbury, J. W.; Bender, L. V.; Jones, O. D.; Mimms, D. L.

1984-01-01

Lithologic mapping techniques using the near infrared bands of the Thematic Mapper onboard the LANDSAT 4 satellite are investigated. These methods are coupled with digital masking to test the capability of mapping geologic materials. Data are examined under medium to low Sun angle illumination conditions to determine the detection limits of materials with absorption features. Several detection anomalies are observed and explained.

Perspective View with Landsat Overlay, San Diego, Calif.

NASA Technical Reports Server (NTRS)

2002-01-01

The influence of topography on the growth of the city of San Diego is seen clearly in this computer-generated perspective viewed from the south. The Peninsular Ranges to the east of the city have channeled development of the cities of La Mesa and El Cajon, above the center. San Diego itself clusters around the bay enclosed by Point Loma and Coronado Island. In the mountains to the right, Lower Otay Lake and Sweetwater Reservoir are the dark patches.

This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced color Landsat 5satellite image. Topographic expression is exaggerated two times.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR)that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise, Washington, D.C.

Size: scale varies in this perspective image Location: 32.6 deg. North lat., 117.1 deg. West lon. Orientation: looking north Image Data: Landsat Bands 3, 2, 1 as red, green, blue

Perspective View with Landsat Overlay, Los Angeles Basin

NASA Technical Reports Server (NTRS)

2002-01-01

Most of Los Angeles is visible in this computer-generated north-northeast perspective viewed from above the Pacific Ocean. In the foreground the hilly Palos Verdes peninsula lies to the left of the harbor at Long Beach, and in the middle distance the various communities that comprise the greater Los Angeles area appear as shades of grey and white. In the distance the San Gabriel Mountains rise up to separate the basin from the Mojave Desert, which can be seen near the top of the image.

This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced color Landsat 5satellite image mosaic. Topographic expression is exaggerated one and one-half times.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR)that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise, Washington, D.C.

Size: View width 70 kilometers (42 miles), View distance 160 kilometers(100 miles) Location: 34.0 deg. North lat., 118.2 deg. West

Shade images of forested areas obtained from LANDSAT MSS data

NASA Technical Reports Server (NTRS)

Shimabukuro, Yosio Edemir; Smith, James A.

1989-01-01

The pixel size in the present day Remote Sensing systems is large enough to include different types of land cover. Depending upon the target area, several components may be present within the pixel. In forested areas, generally, three main components are present: tree canopy, soil (understory), and shadow. The objective is to generate a shade (shadow) image of forested areas from multispectral measurements of LANDSAT MSS (Multispectral Scanner) data by implementing a linear mixing model, where shadow is considered as one of the primary components in a pixel. The shade images are related to the observed variation in forest structure, i.e., the proportion of inferred shadow in a pixel is related to different forest ages, forest types, and tree crown cover. The Constrained Least Squares (CLS) method is used to generate shade images for forest of eucalyptus and vegetation of cerrado using LANDSAT MSS imagery over Itapeva study area in Brazil. The resulted shade images may explain the difference on ages for forest of eucalyptus and the difference on three crown cover for vegetation of cerrado.

Forested land cover classification on the Cumberland Plateau, Jackson County, Alabama: a comparison of Landsat ETM+ and SPOT5 images

Treesearch

Yong Wang; Shanta Parajuli; Callie Schweitzer; Glendon Smalley; Dawn Lemke; Wubishet Tadesse; Xiongwen Chen

2010-01-01

Forest cover classifications focus on the overall growth form (physiognomy) of the community, dominant vegetation, and species composition of the existing forest. Accurately classifying the forest cover type is important for forest inventory and silviculture. We compared classification accuracy based on Landsat Enhanced Thematic Mapper Plus (Landsat ETM+) and Satellite...

Landsat-8 Operational Land Imager (OLI) radiometric performance on-orbit

USGS Publications Warehouse

Morfitt, Ron; Barsi, Julia A.; Levy, Raviv; Markham, Brian L.; Micijevic, Esad; Ong, Lawrence; Scaramuzza, Pat; Vanderwerff, Kelly

2015-01-01

Expectations of the Operational Land Imager (OLI) radiometric performance onboard Landsat-8 have been met or exceeded. The calibration activities that occurred prior to launch provided calibration parameters that enabled ground processing to produce imagery that met most requirements when data were transmitted to the ground. Since launch, calibration updates have improved the image quality even more, so that all requirements are met. These updates range from detector gain coefficients to reduce striping and banding to alignment parameters to improve the geometric accuracy. This paper concentrates on the on-orbit radiometric performance of the OLI, excepting the radiometric calibration performance. Topics discussed in this paper include: signal-to-noise ratios that are an order of magnitude higher than previous Landsat missions; radiometric uniformity that shows little residual banding and striping, and continues to improve; a dynamic range that limits saturation to extremely high radiance levels; extremely stable detectors; slight nonlinearity that is corrected in ground processing; detectors that are stable and 100% operable; and few image artifacts.

Status of the Landsat thematic mapper and multispectral scanner archive conversion system

USGS Publications Warehouse

Werner, Darla J.

1993-01-01

The U.S. Geological Survey's EROS Data Center (EDC) manages the National Satellite Land Remote Sensing Data Archive. This archive includes Landsat thematic mapper (TM) multispectral scanner (MSS) data acquired since 1972. The Landsat archive is an important resource to global change research. To ensure long-term availability of Landsat data from the archive, the EDC specified requirements for a Thematic Mapper and Multispectral Scanner Archive Conversion System (TMACS) that would preserve the data by transcribing it to a more durable medium. In addition to media conversion, hardware and software was installed at EDC in July 1992. In December 1992, the EDC began converting Landsat MSS data from high-density, open reel instrumentation tapes to digital cassette tapes. Almost 320,000 MSS images acquired since 1979 and more than 200,000 TM images acquired since 1982 will be converted to the new medium during the next 3 years. During the media conversion process, several high-density tapes have exhibited severe binder degradation. Even though these tapes have been stored in environmentally controlled conditions, hydrolysis has occurred, resulting in "sticky oxide shed". Using a thermostatically controlled oven built at EDC, tape "baking" has been 100 percent successful and actually improves the quality of some images.

Combining airborne laser scanning and Landsat data for statistical modeling of soil carbon and tree biomass in Tanzanian Miombo woodlands.

PubMed

Egberth, Mikael; Nyberg, Gert; Næsset, Erik; Gobakken, Terje; Mauya, Ernest; Malimbwi, Rogers; Katani, Josiah; Chamuya, Nurudin; Bulenga, George; Olsson, Håkan

2017-12-01

Soil carbon and biomass depletion can be used to identify and quantify degraded soils, and by using remote sensing, there is potential to map soil conditions over large areas. Landsat 8 Operational Land Imager satellite data and airborne laser scanning data were evaluated separately and in combination for modeling soil organic carbon, above ground tree biomass and below ground tree biomass. The test site is situated in the Liwale district in southeastern Tanzania and is dominated by Miombo woodlands. Tree data from 15 m radius field-surveyed plots and samples of soil carbon down to a depth of 30 cm were used as reference data for tree biomass and soil carbon estimations. Cross-validated plot level error (RMSE) for predicting soil organic carbon was 28% using only Landsat 8, 26% using laser only, and 23% for the combination of the two. The plot level error for above ground tree biomass was 66% when using only Landsat 8, 50% for laser and 49% for the combination of Landsat 8 and laser data. Results for below ground tree biomass were similar to above ground biomass. Additionally it was found that an early dry season satellite image was preferable for modelling biomass while images from later in the dry season were better for modelling soil carbon. The results show that laser data is superior to Landsat 8 when predicting both soil carbon and biomass above and below ground in landscapes dominated by Miombo woodlands. Furthermore, the combination of laser data and Landsat data were marginally better than using laser data only.

Using Landsat Thematic Mapper and SPOT Satellite Imagery to inventory wetland plants of the Coeur d'Alene Floodplain

Treesearch

F. M. Roberts; P. E. Gessler

2000-01-01

Landsat Thematic Mapper (TM) and SPOT Satellite Imagery were used to map wetland plant species in thc Coeur d'Alene floodplain in northern Idaho. This paper discusses the methodology used to create a wetland plant species map for the floodplain. Species mapped included common cattail (Typha latifolia); water horse-tail (Equisetum...

An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Sader, Steve; Smoot, James

2012-01-01

This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, satellite, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. MODIS-based change products were applied to view and assess insect-induced swamp forest defoliation. MODIS, Landsat, and ASTER satellite data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.

Richat Structure, Mauritania, Perspective View, Landsat Image over SRTM Elevation

NASA Technical Reports Server (NTRS)

2004-01-01

This prominent circular feature, known as the Richat Structure, in the Sahara desert of Mauritania is often noted by astronauts because it forms a conspicuous 50-kilometer-wide (30-mile-wide) bull's-eye on the otherwise rather featureless expanse of the desert. Initially mistaken for a possible impact crater, it is now known to be an eroded circular anticline (structural dome) of layered sedimentary rocks.

Extensive sand dunes occur in this region and the interaction of bedrock topography, wind, and moving sand is evident in this scene. Note especially how the dune field ends abruptly short of the cliffs at the far right as wind from the northeast (lower right) apparently funnels around the cliff point, sweeping clean areas near the base of the cliff. Note also the small isolated peak within the dune field. That peak captures some sand on its windward side, but mostly deflects the wind and sand around its sides, creating a sand-barren streak that continues far downwind.

This view was generated from a Landsat satellite image draped over an elevation model produced by the Shuttle Radar Topography Mission (SRTM). The view uses a 6-times vertical exaggeration to greatly enhance topographic expression. For vertical scale, note that the height of the mesa ridge in the back center of the view is about 285 meters (about 935 feet) tall. Colors of the scene were enhanced by use of a combination of visible and infrared bands, which helps to differentiate bedrock (browns), sand (yellow, some white), minor vegetation in drainage channels (green), and salty sediments (bluish whites). Some shading of the elevation model was included to further highlight the topographic features.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR

Landsat Data Continuity Mission - Launch Fever

NASA Technical Reports Server (NTRS)

Irons, James R.; Loveland, Thomas R.; Markham, Brian L.; Masek, Jeffrey G.; Cook, Bruce; Dwyer, John L.

2012-01-01

The year 2013 will be an exciting period for those that study the Earth land surface from space, particularly those that observe and characterize land cover, land use, and the change of cover and use over time. Two new satellite observatories will be launched next year that will enhance capabilities for observing the global land surface. The United States plans to launch the Landsat Data Continuity Mission (LDCM) in January. That event will be followed later in the year by the European Space Agency (ESA) launch of the first Sentinel 2 satellite. Considered together, the two satellites will increase the frequency of opportunities for viewing the land surface at a scale where human impact and influence can be differentiated from natural change. Data from the two satellites will provide images for similar spectral bands and for comparable spatial resolutions with rigorous attention to calibration that will facilitate cross comparisons. This presentation will provide an overview of the LDCM satellite system and report its readiness for the January launch.

Applications notice for participation in the LANDSAT-D image data quality analysis program

NASA Technical Reports Server (NTRS)

1981-01-01

The applications notice for the LANDSAT 4 image data quality analysis program is presented. The objectives of the program are to qualify LANDSAT 4 sensor and systems performance from a user applications point of view, and to identify any malfunctions that may impact data applications. Guidelines for preparing proposals and background information are provided.

Ten Years of Vegetation Change in Northern California Marshlands Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2013-01-01

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway.

Spatial Data Exploring by Satellite Image Distributed Processing

NASA Astrophysics Data System (ADS)

Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.

2012-04-01

Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands

Nyiragongo volcano, Congo, Perspective View with Lava SRTM / ASTER / Landsat

NASA Technical Reports Server (NTRS)

2002-01-01

The Nyiragongo volcano in the Congo erupted on January 17, 2002, and subsequently sent streams of lava into the city of Goma on the north shore of Lake Kivu. More than 100 people were killed, more than 12,000 homes were destroyed, and hundreds of thousands were forced to flee the broader community of nearly half a million people. This computer-generated visualization combines a Landsat satellite image and an elevation model from the Shuttle Radar Topography Mission (SRTM) to provide a view of both the volcano and the city of Goma, looking slightly east of north. Additionally, image data from the Advanced Spaceborne Thermal Emission and reflection Radiometer (ASTER) on NASA's Terra satellite were used to supply a partial map of the recent lava flows (red), including a complete mapping of their intrusion into Goma as of January 28, 2002. Lava is also apparent within the volcanic crater and at a few other locations. Thick (but broken) cloud cover during the ASTER image acquisition prevented a complete mapping of the lava distribution, but future image acquisitions should complete the mapping.

Nyiragongo is the steep volcano on the right, Lake Kivu is in the foreground, and the city of Goma has a light pink speckled appearance along the shoreline. Nyiragongo peaks at about 3,470 meters (11,380 feet) elevation and reaches almost exactly 2,000 meters (6,560 feet) above Lake Kivu. The shorter but broader Nyamuragira volcano appears in the left background. Topographic expression has been exaggerated vertically by a factor of 1.5 for this visualization.

Goma, Lake Kivu, Nyiragongo, Nyamuragira and other nearby volcanoes sit within the East African Rift Valley, a zone where tectonic processes are cracking, stretching, and lowering the Earth's crust. Volcanic activity is common here, and older but geologically recent lava flows (magenta in this depiction) are particularly apparent on the flanks of the Nyamuragira volcano.

The Landsat image used here was acquired

The Use of False Color Landsat Imagery with a Fifth Grade Class.

ERIC Educational Resources Information Center

Harnapp, Vern R.

Fifth grade students can become familiar with images of earth generated by space sensor Landsat satellites which sense nearly all surfaces of the earth once every 18 days. Two false color composites in which different colors represent various geographic formations were obtained for the northern Ohio region where the students live. The class had no…

A one year Landsat 8 conterminous United States study of spatial and temporal patterns of cirrus and non-cirrus clouds and implications for the long term Landsat archive.

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Roy, D. P.

2014-12-01

The successful February 2013 launch of the Landsat 8 satellite is continuing the 40+ year legacy of the Landsat mission. The payload includes the Operational Land Imager (OLI) that has a new 1370 mm band designed to monitor cirrus clouds and the Thermal Infrared Sensor (TIRS) that together provide 30m low, medium and high confidence cloud detections and 30m low and high confidence cirrus cloud detections. A year of Landsat 8 data over the Conterminous United States (CONUS), composed of 11,296 acquisitions, was analyzed comparing the spatial and temporal incidence of these cloud and cirrus states. This revealed (i) 36.5% of observations were detected with high confidence cloud with spatio-temporal patterns similar to those observed by previous Landsat 7 cloud analyses, (ii) 29.2% were high confidence cirrus, (iii) 20.9% were both high confidence cloud and high confidence cirrus, (iv) 8.3% were detected as high confidence cirrus but not as high confidence cloud. The results illustrate the value of the cirrus band for improved Landsat 8 terrestrial monitoring but imply that the historical CONUS Landsat archive has a similar 8% of undetected cirrus contaminated pixels. The implications for long term Landsat time series records, including the global Web Enabled Landsat Data (WELD) product record, are discussed.

An automated approach to mapping corn from Landsat imagery

USGS Publications Warehouse

Maxwell, S.K.; Nuckols, J.R.; Ward, M.H.; Hoffer, R.M.

2004-01-01

Most land cover maps generated from Landsat imagery involve classification of a wide variety of land cover types, whereas some studies may only need spatial information on a single cover type. For example, we required a map of corn in order to estimate exposure to agricultural chemicals for an environmental epidemiology study. Traditional classification techniques, which require the collection and processing of costly ground reference data, were not feasible for our application because of the large number of images to be analyzed. We present a new method that has the potential to automate the classification of corn from Landsat satellite imagery, resulting in a more timely product for applications covering large geographical regions. Our approach uses readily available agricultural areal estimates to enable automation of the classification process resulting in a map identifying land cover as ‘highly likely corn,’ ‘likely corn’ or ‘unlikely corn.’ To demonstrate the feasibility of this approach, we produced a map consisting of the three corn likelihood classes using a Landsat image in south central Nebraska. Overall classification accuracy of the map was 92.2% when compared to ground reference data.

Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico.

PubMed

Jarchow, Christopher J; Didan, Kamel; Barreto-Muñoz, Armando; Nagler, Pamela L; Glenn, Edward P

2018-05-13

The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000⁻2011), 8 (2013⁻2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013⁻2016) to MODIS EVI (2000⁻2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R² = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R² = 0.27) and riparian vegetation (R² = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R² = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area.

MUNSELL COLOR ANALYSIS OF LANDSAT COLOR-RATIO-COMPOSITE IMAGES OF LIMONITIC AREAS IN SOUTHWEST NEW MEXICO.

USGS Publications Warehouse

Kruse, Fred A.

1984-01-01

Green areas on Landsat 4/5 - 4/6 - 6/7 (red - blue - green) color-ratio-composite (CRC) images represent limonite on the ground. Color variation on such images was analyzed to determine the causes of the color differences within and between the green areas. Digital transformation of the CRC data into the modified cylindrical Munsell color coordinates - hue, value, and saturation - was used to correlate image color characteristics with properties of surficial materials. The amount of limonite visible to the sensor is the primary cause of color differences in green areas on the CRCs. Vegetation density is a secondary cause of color variation of green areas on Landsat CRC images. Digital color analysis of Landsat CRC images can be used to map unknown areas. Color variations of green pixels allows discrimination among limonitic bedrock, nonlimonitic bedrock, nonlimonitic alluvium, and limonitic alluvium.

Some aspects of geological information contained in LANDSAT images

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Liu, C. C.; Vitorello, I.; Meneses, P. R.

1980-01-01

The characteristics of MSS images and methods of interpretation are analyzed from a geological point of view. The supportive role of LANDSAT data are illustrated in several examples of surface expressions of geological features, such as synclines and anticlines, spectral characteristics of lithologic units, and circular impact structures.

Image restoration techniques as applied to Landsat MSS and TM data

USGS Publications Warehouse

Meyer, David

1987-01-01

Two factors are primarily responsible for the loss of image sharpness in processing digital Landsat images. The first factor is inherent in the data because the sensor's optics and electronics, along with other sensor elements, blur and smear the data. Digital image restoration can be used to reduce this degradation. The second factor, which further degrades by blurring or aliasing, is the resampling performed during geometric correction. An image restoration procedure, when used in place of typical resampled techniques, reduces sensor degradation without introducing the artifacts associated with resampling. The EROS Data Center (EDC) has implemented the restoration proceed for Landsat multispectral scanner (MSS) and thematic mapper (TM) data. This capability, developed at the University of Arizona by Dr. Robert Schowengerdt and Lynette Wood, combines restoration and resampling in a single step to produce geometrically corrected MSS and TM imagery. As with resampling, restoration demands a tradeoff be made between aliasing, which occurs when attempting to extract maximum sharpness from an image, and blurring, which reduces the aliasing problem but sacrifices image sharpness. The restoration procedure used at EDC minimizes these artifacts by being adaptive, tailoring the tradeoff to be optimal for individual images.

LANDSAT (MSS): Image demographic estimations

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Foresti, C.

1977-01-01

The author has identified the following significant results. Two sets of urban test sites, one with 35 cities and one with 70 cities, were selected in the State, Sao Paulo. A high degree of colinearity (0.96) was found between urban and areal measurements taken from aerial photographs and LANDSAT MSS imagery. High coefficients were observed when census data were regressed against aerial information (0.95) and LANDSAT data (0.92). The validity of population estimations was tested by regressing three urban variables, against three classes of cities. Results supported the effectiveness of LANDSAT to estimate large city populations with diminishing effectiveness as urban areas decrease in size.

The users, uses, and value of Landsat and other moderate-resolution satellite imagery in the United States-Executive report

USGS Publications Warehouse

Miller, Holly M.; Sexton, Natalie R.; Koontz, Lynne; Loomis, John; Koontz, Stephen R.; Hermans, Caroline

2011-01-01

Moderate-resolution imagery (MRI), such as that provided by the Landsat satellites, provides unique spatial information for use by many people both within and outside of the United States (U.S.). However, exactly who these users are, how they use the imagery, and the value and benefits derived from the information are, to a large extent, unknown. To explore these issues, social scientists at the USGS Fort Collins Science Center conducted a study of U.S.-based MRI users from 2008 through 2010 in two parts: 1) a user identification and 2) a user survey. The objectives for this study were to: 1) identify and classify U.S.-based users of this imagery; 2) better understand how and why MRI, and specifically Landsat, is being used; and 3) qualitatively and quantitatively measure the value and societal benefits of MRI (focusing on Landsat specifically). The results of the survey revealed that respondents from multiple sectors use Landsat imagery in many different ways, as demonstrated by the breadth of project locations and scales, as well as application areas. The value of Landsat imagery to these users was demonstrated by the high importance placed on the imagery, the numerous benefits received from projects using Landsat imagery, the negative impacts if Landsat imagery was no longer available, and the substantial willingness to pay for replacement imagery in the event of a data gap. The survey collected information from users who are both part of and apart from the known user community. The diversity of the sample delivered results that provide a baseline of knowledge about the users, uses, and value of Landsat imagery. While the results supply a wealth of information on their own, they can also be built upon through further research to generate a more complete picture of the population of Landsat users as a whole.

Non-parametric analysis of LANDSAT maps using neural nets and parallel computers

NASA Technical Reports Server (NTRS)

Salu, Yehuda; Tilton, James

1991-01-01

Nearest neighbor approaches and a new neural network, the Binary Diamond, are used for the classification of images of ground pixels obtained by LANDSAT satellite. The performances are evaluated by comparing classifications of a scene in the vicinity of Washington DC. The problem of optimal selection of categories is addressed as a step in the classification process.

Radiometric Cross-calibration of KOMPSAT-3A with Landsat-8

NASA Astrophysics Data System (ADS)

Shin, D. Y.; Ahn, H. Y.; Lee, S. G.; Choi, C. U.; Kim, J. S.

2016-06-01

In this study, Cross calibration was conducted at the Libya 4 PICS site on 2015 using Landsat-8 and KOMPSAT-3A. Ideally a cross calibration should be calculated for each individual scene pair because on any given date the TOA spectral profile is influenced by sun and satellite view geometry and the atmospheric conditions. However, using the near-simultaneous images minimizes this effect because the sensors are viewing the same atmosphere. For the cross calibration, the calibration coefficient was calculated by comparing the at sensor spectral radiance for the same location calculated using the Landsat-8 calibration parameters in metadata and the DN of KOMPSAT-3A for the regions of interest (ROI). Cross calibration can be conducted because the satellite sensors used for overpass have a similar bandwidth. However, not all satellites have the same color filter transmittance and sensor reactivity, even though the purpose is to observe the visible bands. Therefore, the differences in the RSR should be corrected. For the cross-calibration, a calibration coefficient was calculated using the TOA radiance and KOMPSAT-3 DN of the Landsat-8 OLI overpassed at the Libya 4 Site, As a result, the accuracy of the calibration coefficient at the site was assumed to be ± 1.0%. In terms of the results, the radiometric calibration coefficients suggested here are thought to be useful for maintaining the optical quality of the KOMPSAT-3A.

A technique for the reduction of banding in Landsat Thematic Mapper Images

USGS Publications Warehouse

Helder, Dennis L.; Quirk, Bruce K.; Hood, Joy J.

1992-01-01

The radiometric difference between forward and reverse scans in Landsat thematic mapper (TM) images, referred to as "banding," can create problems when enhancing the image for interpretation or when performing quantitative studies. Recent research has led to the development of a method that reduces the banding in Landsat TM data sets. It involves passing a one-dimensional spatial kernel over the data set. This kernel is developed from the statistics of the banding pattern and is based on the Wiener filter. It has been implemented on both a DOS-based microcomputer and several UNIX-based computer systems. The algorithm has successfully reduced the banding in several test data sets.

Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

NASA Astrophysics Data System (ADS)

Clark, M. L.; Kilham, N. E.

2015-12-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

Monitoring Springs in the Mojave Desert Using Landsat Time Series Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2018-01-01

The purpose of this study, based on Landsat satellite data was to characterize variations and trends over 30 consecutive years (1985-2016) in perennial vegetation green cover at over 400 confirmed Mojave Desert spring locations. These springs were surveyed between in 2015 and 2016 on lands managed in California by the U.S. Bureau of Land Management (BLM) and on several land trusts within the Barstow, Needles, and Ridgecrest BLM Field Offices. The normalized difference vegetation index (NDVI) from July Landsat images was computed at each spring location and a trend model was first fit to the multi-year NDVI time series using least squares linear regression.Â

A legislator's guide to LANDSAT

NASA Technical Reports Server (NTRS)

1982-01-01

The LANDSAT satellite is an effective tool in meeting the natural resources data requirements of state and federal legislation. The availability of data from the satellite is beginning to have an impact on state legislature activities. An overview of the history, operation, and data analysis techniques, is presented as well as a discussion of the advantages and limitations of this method of remote sensing. Applications are discussed in the areas of (1) land resource planning and management; (2) coastal zone management; (3) agriculture; (4) forestry; (5) routing and siting; (6) environmental monitoring; and (7) geological exploration. National and state sources from which information about LANDSAT technology is available are listed.

Detection of surface temperature from LANDSAT-7/ETM+

NASA Astrophysics Data System (ADS)

Suga, Y.; Ogawa, H.; Ohno, K.; Yamada, K.

2003-12-01

Hiroshima Institute of Technology (HIT) in Japan has established a LANDSAT-7 Ground Station in cooperation with NASDA for receiving and processing the ETM+ data on March 15 th, 2000 in Japan. The authors performed a verification study on the surface temperature derived from thermal infrared band image data of LANDSAT 7/Enhanced Thematic Mapper Plus (ETM+) for the estimation of temperatures around Hiroshima city and bay area in the western part of Japan as a test site. As to the thermal infrared band, the approximate functions for converting the spectral radiance into the surface temperature are estimated by considering both typical surface temperatures measured by the simultaneous field survey with the satellite observation and the spectral radiance observed by ETM+ band 6 (10.40-12.50μm), and then the estimation of the surface temperature distribution around the test site was examined.In this study, the authors estimated the surface temperature distribution equivalent to the land cover categories around the test site for establishing a guideline of surface temperature detection by LANDSAT7/ETM+ data. As the result of comparison of the truth data and the estimated surface temperature, the correlation coefficients of the approximate function referred to the truth data are from 0.9821 to 0.9994, and the differences are observed from +0.7 to -1.5°C in summer, from +0.4 to -0.9 *C in autumn, from -1.6 to -3.4°C in winter and from +0.5 to -0.5C in spring season respectively. It is clearly found that the estimation of surface temperature based on the approximate functions for converting the spectral radiance into the surface temperature referred to the truth data is improved over the directly estimated surface temperature obtained from satellite data. Finally, the successive seasonal change of surface temperature distribution pattern of the test site is precisely detected with the temperature legend of 0 to 80'C derived from LANDSAT-7/ETM+ band 6 image data for the

Perspective View with Landsat Overlay, San Francisco Bay Area, Calif.

NASA Technical Reports Server (NTRS)

2002-01-01

The cities of San Francisco and the East Bay are highlighted in this computer-generated perspective viewed from west of the Golden Gate. San Francisco occupies the peninsula jutting into the picture from the right. Golden Gate Park is the long rectangle near its left end and the Presidiois the green area at its tip, from which Golden Gate Bridge crosses to Marin. Treasure Island is the bright spot above San Francisco and Alcatraz Island is the small smudge below and to the left. Across the bay from San Francisco lie Berkeley (left) and Oakland (right). Mount Diablo, a landmark visible for many miles, rises in the distance at the upper right.

This three-dimensional perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 5 satellite image. Colors are from Landsat bands 3, 2, and 1 as red, green and blue, respectively. Topographic expression is exaggerated two times.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive.

The Landsat Thematic Mapper image used here came from an on-line mosaic of Landsat images for the continental United States (http://mapus.jpl.nasa.gov), a part of NASA's Digital Earth effort.

Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation

Landsat commercialization

NASA Astrophysics Data System (ADS)

Richman, Barbara T.

1984-04-01

The House of Representatives will soon vote on a bill that outlines steps to commercialize the land remote-sensing system. The bill follows attempts last year to commercialize both the land and meteorological remote sensing satellite systems. Meanwhile, the National Oceanic and Atmospheric Administration (NOAA) has received bids from seven private companies interested in operating Landsat. The bids resulted from a request for proposals issued by the agency earlier this year. Commercialization of the meteorological satellite system was blocked in November.

Determining the Suitability of Different Digital Elevation Models and Satellite Images for Fancy Maps. An Example of Cyprus

NASA Astrophysics Data System (ADS)

Drachal, J.; Kawel, A. K.

2016-06-01

The article describes the possibility of developing an overall map of the selected area on the basis of publicly available data. Such a map would take the form designed by the author with the colors that meets his expectations and a content, which he considers to be appropriate. Among the data available it was considered the use of satellite images of the terrain in real colors and, in the form of shaded relief, digital terrain models with different resolutions of the terrain mesh. Specifically the considered data were: MODIS, Landsat 8, GTOPO-30, SRTM-30, SRTM-1, SRTM-3, ASTER. For the test area the island of Cyprus was chosen because of the importance in tourism, a relatively small area and a clearly defined boundary. In the paper there are shown and discussed various options of the Cyprus terrain image obtained synthetically from variants of Modis, Landsat and digital elevation models of different resolutions.

Landsat image registration for agricultural applications

NASA Technical Reports Server (NTRS)

Wolfe, R. H., Jr.; Juday, R. D.; Wacker, A. G.; Kaneko, T.

1982-01-01

An image registration system has been developed at the NASA Johnson Space Center (JSC) to spatially align multi-temporal Landsat acquisitions for use in agriculture and forestry research. Working in conjunction with the Master Data Processor (MDP) at the Goddard Space Flight Center, it functionally replaces the long-standing LACIE Registration Processor as JSC's data supplier. The system represents an expansion of the techniques developed for the MDP and LACIE Registration Processor, and it utilizes the experience gained in an IBM/JSC effort evaluating the performance of the latter. These techniques are discussed in detail. Several tests were developed to evaluate the registration performance of the system. The results indicate that 1/15-pixel accuracy (about 4m for Landsat MSS) is achievable in ideal circumstances, sub-pixel accuracy (often to 0.2 pixel or better) was attained on a representative set of U.S. acquisitions, and a success rate commensurate with the LACIE Registration Processor was realized. The system has been employed in a production mode on U.S. and foreign data, and a performance similar to the earlier tests has been noted.

Bora Bora, Tahaa, and Raiatea, French Polynesia, Landsat and SIR-C Images Compared to SRTM Shaded

NASA Technical Reports Server (NTRS)

2005-01-01

Bora Bora, Tahaa, and Raiatea (top to bottom) are Polynesian Islands about 220 kilometers (135 miles) west-northwest of Tahiti in the South Pacific. Each of the islands is surrounded by a coral reef and its associated islets ('motus') that enclose a lagoon. Actually, as seen here, Tahaa and Raiatea are close enough together to share a common lagoon and reef. These islands are volcanic in origin and were built up from the sea floor by lava extrusions millions of years ago. None is now active, and all are deeply eroded.

This display compares three differing 'views from space' of these islands. On the left, an image from the Landsat 7 satellite shows the islands as they might have appeared to an astronaut in orbit in 1999 (but a little sharper and with atmospheric haze suppressed). In the middle is an image created from data gathered by the third-generation Shuttle Imaging Radar (SIR-C), flown in 1994. On the right is a graphic illustrating elevation data gathered by the Shuttle Radar Topography Mission (SRTM) in 2000.

Each of these images shows very different information as compared to the other two. Landsat sees clouds, which are almost always above these islands, blocking the view of the terrain. It also readily sees through shallow water down to the reefs. SIR-C sees the waves and other effects of winds upon the ocean surface. It does not look through water to see the reefs, but it clearly separates land and water. It also provides a bolder (but distorted) view of the islands' topographic patterns. With the ability of radar to see through clouds and provision of its own illumination, the SIR-C view is not limited by clouds nor their shadows.

SRTM was designed to provide new information that is missing in the Landsat and SIR-C views. Specifically, SRTM created the world's first near-global, detailed elevation model. Natural topographic shading in Landsat imagery and radar topographic shadowing of SIR-C give some evidence of the shape of the

Anaglyph, Landsat overlay Honolulu, Hawaii

NASA Technical Reports Server (NTRS)

2000-01-01

Honolulu, on the island of Oahu, is a large and growing urban area with limited space and water resources. This anaglyph, combining a Landsat image with SRTM topography, shows how the topography controls the urban growth pattern, causes cloud formation, and directs the rainfall runoff pattern. Red/blue glasses are required to see the 3-D effect. Features of interest in this scene include Diamond Head (an extinct volcano on the right side of the image), Waikiki Beach (just left of Diamond Head), the Punchbowl National Cemetary (another extinct volcano, left of center), downtown Honolulu and Honolulu harbor (lower left of center), and offshore reef patterns. The slopes of the Koolau mountain range are seen in the upper half of the image. Clouds commonly hang above ridges and peaks of the Hawaiian Islands, and in this rendition appear draped directly on the mountains. The clouds are actually about 1000 meters (3300 feet) above sea level. High resolution topographic and image data allow ecologists and planners to assess the effects of urban development on the sensitive ecosystems in tropical regions.

This anaglyph was generated using topographic data from the Shuttle Radar Topography Mission, combined with a Landsat 7 satellite image collected coincident with the SRTM mission. The topography data are used to create two differing perspectives of a single image, one perspective for each eye. Each point in the image is shifted slightly, depending on its elevation. When viewed through special glasses, the result is a vertically exaggerated view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter. The United States Geological Survey's Earth Resources Observations Systems (EROS) DataCenter, Sioux Falls, South Dakota, provided the Landsat data.

The Shuttle Radar Topography Mission (SRTM), launched on February 11, 2000, uses the same radar instrument that comprised the

Forest cover of North America in the 1970s mapped using Landsat MSS data

NASA Astrophysics Data System (ADS)

Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

2015-12-01

The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at < 100-m resolution using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). These "Landsat-class" sensors offer precise calibration, but they provide observations only over the past three decades—a relatively short period for delineating the long-term changes of forests. Starting in 1971, the Multispectral Scanner (MSS) was the first generation of sensors aboard the Landsat satellites. MSS thus provides a unique resource to extend observations by at least a decade longer in history than records based on Landsat TM and ETM+. Leveraging more recent Landsat-based forest-cover products developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing

Evaluation of Daily Evapotranspiration Over Orchards Using METRIC Approach and Landsat Satellite Observations

NASA Astrophysics Data System (ADS)

He, R.; Jin, Y.; Daniele, Z.; Kandelous, M. M.; Kent, E. R.

2016-12-01

The pistachio and almond acreage in California has been rapidly growing in the past 10 years, raising concerns about competition for limited water resources in California. A robust and cost-effective mapping of crop water use, mostly evapotranspiration (ET), by orchards, is needed for improved farm-level irrigation management and regional water planning. METRIC™, a satellite-based surface energy balance approach, has been widely used to map field-scale crop ET, mostly over row crops. We here aim to apply METRIC with Landsat satellite observations over California's orchards and evaluate the ET estimates by comparing with field measurements in South San Joaquin Valley, California. Reference ET of grass (ETo) from California Irrigation Management Information system (CIMIS) stations was used to estimate daily ET of commercial almond and pistachio orchards. Our comparisons showed that METRIC-Landsat ET daily estimates agreed well with ET measured by the eddy covariance and surface renewal stations, with a RMSE of 1.25 and a correlation coefficient of 0.84 for the pistachio orchard. A slight high bias of satellite based ET estimates was found for both pistachio and almond orchards. We also found time series of NDVI was highly correlated with ET temporal dynamics within each field, but the correlation was reduced to 0.56 when all fields were pooled together. Net radiation, however, remained highly correlated with ET across all the fields. The METRIC ET was able to distinguish the differences in ET among salt- and non-salt affected pistachio orchards, e.g., mean daily ET during growing season in salt-affected orchards was lower than that of non-salt affected one by 0.87 mm/day. The remote sensing based ET estimate will support a variety of state and local interests in water use and management, for both planning and regulatory/compliance purposes, and provide the farmers observation-based guidance for site-specific and time-sensitive irrigation management.

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

NASA Astrophysics Data System (ADS)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

Nyiragongo volcano, Congo, Pre-eruption Perspective View, SRTM / Landsat

NASA Technical Reports Server (NTRS)

2002-01-01

The Nyiragongo volcano in the Congo erupted on January 17, 2002, and subsequently sent streams of lava into the city of Goma on the north shore of Lake Kivu. More than 100 people were killed, more than 12000 homes were destroyed, and hundreds of thousands were forced to flee the broader community of nearly half a million people. This computer generated visualization combines a Landsat satellite image and an elevation model from the Shuttle Radar Topography Mission (SRTM) to provide a view of both the volcano and the city of Goma, looking slightly east of north.

Nyiragongo is the steep volcano on the right, Lake Kivu is in the foreground, and the city of Goma has a light pink speckled appearance along the shoreline. Nyiragongo peaks at about 3470 meters (11,380 feet) elevation and reaches almost exactly 2000 meters (6560 feet) above Lake Kivu. The shorter but broader Nyamuragira volcano appears in the left background. Topographic expression has been exaggerated vertically by a factor of 1.5 for this visualization.

Goma, Lake Kivu, Nyiragongo, Nyamuragira and other nearby volcanoes sit within the East African Rift Valley, a zone where tectonic processes are cracking, stretching, and lowering the Earth's crust. Volcanic activity is common here, and older but geologically recent lava flows (magenta in this depiction) are particularly apparent on the flanks of the Nyamuragira volcano.

The Landsat image used here was acquired on December 11, 2001, about a month before the eruption, and shows an unusually cloud-free view of this tropical terrain. Minor clouds and their shadows were digitally removed to clarify the view, topographic shading derived from the SRTM elevation model was added to the Landsat image, and a false sky was added.

Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and substantially helps in analyzing the large and growing

Geosynchronous Meteorological Satellite Data Seminar

NASA Technical Reports Server (NTRS)

1976-01-01

A seminar was organized by NASA to acquaint the meteorological community with data now available, and data scheduled to be available in the future, from geosynchronous meteorological satellites. The twenty-four papers were presented in three half-day sessions in addition to tours of the Image Display and LANDSAT Processing Facilities during the afternoon of the second day.

Investigation on changes in complex vegetation coverage using multi-temporal landsat data of Western Black Sea region--a case study.

PubMed

Coban, Huseyin Oguz; Koc, Ayhan; Eker, Mehmet

2010-01-01

Previous studies have been able to successfully detect changes in gently-sloping forested areas with low-diversity and homogeneous vegetation cover using medium-resolution satellite data such as landsat. The aim of the present study is to examine the capacity of multi-temporal landsat data to identify changes in forested areas with mixed vegetation and generally located on steep slopes or non-uniform topography landsat thematic mapper (TM) and landsat enhanced thematic mapperplus (ETM+) data for the years 1987-2000 was used to detect changes within a 19,500 ha forested area in the Western Black sea region of Turkey. The data comply with the forest cover type maps previously created for forest management plans of the research area. The methods used to detect changes were: post-classification comparison, image differencing, image rationing and NDVI (Normalized Difference Vegetation Index) differencing methods. Following the supervised classification process, error matrices were used to evaluate the accuracy of classified images obtained. The overall accuracy has been calculated as 87.59% for 1987 image and as 91.81% for 2000 image. General kappa statistics have been calculated as 0.8543 and 0.9038 for 1987 and 2000, respectively. The changes identified via the post-classification comparison method were compared with other change detetion methods. Maximum coherence was found to be 74.95% at 4/3 band rate. The NDVI difference and 3rd band difference methods achieved the same coherence with slight variations. The results suggest that landsat satellite data accurately conveys the temporal changes which occur on steeply-sloping forested areas with a mixed structure, providing a limited amount of detail but with a high level of accuracy. Moreover it has been decided that the post-classification comparison method can meet the needs of forestry activities better than other methods as it provides information about the direction of these changes.

Mapping the invasive species, Chinese tallow, with EO1 satellite Hyperion hyperspectral image data and relating tallow occurrences to a classified Landsat Thematic Mapper land cover map

USGS Publications Warehouse

Ramsey, Elijah W.; Rangoonwala, A.; Nelson, G.; Ehrlich, R.

2005-01-01

Our objective was to provide a realistic and accurate representation of the spatial distribution of Chinese tallow (Triadica sebifera) in the Earth Observing 1 (EO1) Hyperion hyperspectral image coverage by using methods designed and tested in previous studies. We transformed, corrected, and normalized Hyperion reflectance image data into composition images with a subpixel extraction model. Composition images were related to green vegetation, senescent foliage and senescing cypress-tupelo forest, senescing Chinese tallow with red leaves ('red tallow'), and a composition image that only corresponded slightly to yellowing vegetation. These statistical and visual comparisons confirmed a successful portrayal of landscape features at the time of the Hyperion image collection. These landscape features were amalgamated in the Landsat Thematic Mapper (TM) pixel, thereby preventing the detection of Chinese tallow occurrences in the Landsat TM classification. With the occurrence in percentage of red tallow (as a surrogate for Chinese tallow) per pixel mapped, we were able to link dominant land covers generated with Landsat TM image data to Chinese tallow occurrences as a first step toward determining the sensitivity and susceptibility of various land covers to tallow establishment. Results suggested that the highest occurrences and widest distribution of red tallow were (1) apparent in disturbed or more open canopy woody wetland deciduous forests (including cypress-tupelo forests), upland woody land evergreen forests (dominantly pines and seedling plantations), and upland woody land deciduous and mixed forests; (2) scattered throughout the fallow fields or located along fence rows separating active and non-active cultivated and grazing fields, (3) found along levees lining the ubiquitous canals within the marsh and on the cheniers near the coastline; and (4) present within the coastal marsh located on the numerous topographic highs. ?? 2005 US Government.

Cross calibration of GF-1 satellite wide field of view sensor with Landsat 8 OLI and HJ-1A HSI

NASA Astrophysics Data System (ADS)

Liu, Li; Gao, Hailiang; Pan, Zhiqiang; Gu, Xingfa; Han, Qijin; Zhang, Xuewen

2018-01-01

This paper focuses on cross calibrating the GaoFen (GF-1) satellite wide field of view (WFV) sensor using the Landsat 8 Operational Land Imager (OLI) and HuanJing-1A (HJ-1A) hyperspectral imager (HSI) as reference sensors. Two methods are proposed to calculate the spectral band adjustment factor (SBAF). One is based on the HJ-1A HSI image and the other is based on ground-measured reflectance. However, the HSI image and ground-measured reflectance were measured at different dates, as the WFV and OLI imagers passed overhead. Three groups of regions of interest (ROIs) were chosen for cross calibration, based on different selection criteria. Cross-calibration gains with nonzero and zero offsets were both calculated. The results confirmed that the gains with zero offset were better, as they were more consistent over different groups of ROIs and SBAF calculation methods. The uncertainty of this cross calibration was analyzed, and the influence of SBAF was calculated based on different HSI images and ground reflectance spectra. The results showed that the uncertainty of SBAF was <3% for bands 1 to 3. Two other large uncertainties in this cross calibration were variation of atmosphere and low ground reflectance.

CONTINUOUS CALIBRATION IMPROVEMENT: LANDSAT 5 THROUGH LANDSAT 8

PubMed Central

Mishra, Nischal; Helder, Dennis; Barsi, Julia; Markham, Brian

2018-01-01

Launched in February 2013, the Operational Land Imager (OLI) on-board Landsat 8 continues to perform exceedingly well and provides high science quality data globally. Several design enhancements have been made in the OLI instrument relative to prior Landsat instruments: pushbroom imaging which provides substantially improved Signal-to-Noise Ratio (SNR), spectral bandpasses refinement to avoid atmospheric absorption features, 12 bit data resolution to provide a larger dynamic range that limits the saturation level, a set of well-designed onboard calibrators to monitor the stability of the sensor. Some of these changes such as refinements in spectral bandpasses compared to earlier Landsats and well-designed on-board calibrator have a direct impact on the improved radiometric calibration performance of the instrument from both the stability of the response and the ability to track the changes. The on-board calibrator lamps and diffusers indicate that the instrument drift is generally less than 0.1% per year across the bands. The refined bandpasses of the OLI indicate that temporal uncertainty of better than 0.5% is possible when the instrument is trended over vicarious targets such as Pseudo Invariant Calibration Sites (PICS), a level of precision that was never achieved with the earlier Landsat instruments. The stability measurements indicated by on-board calibrators and PICS agree much better compared to the earlier Landsats, which is very encouraging and bodes well for the future Landsat missions too. PMID:29449747

Perspective View, Landsat Overlay, Salalah, Oman, Southern Arabian Peninsula

NASA Technical Reports Server (NTRS)

2000-01-01

This perspective view includes the city of Salalah, the second largest city in Oman. The city is located on the broad, generally bright coastal plain and includes areas of green irrigated crops. This view was generated from a Landsat image draped over a preliminary elevation model produced by the Shuttle Radar Topography Mission (SRTM). The edges of the dataset are to the upper right, left, and lower left. The Arabian Sea (lower right) is represented by the blue false-colored area. Vertical exaggeration of topography is 3X.

This scene illustrates how topography determines local climate and, in turn, where people live. The Arabian Peninsula is very arid. However, the steep escarpment of the Qara Mountains wrings moisture from the summer monsoons allowing for growth of natural vegetation (green along the mountain fronts and in the canyons), and soil development (dark brown areas), as well as cultural development of the coastal plain. The monsoons also provide moisture for Frankincense trees growing on the desert (north) side of the mountains. In ancient times, incense derived from the sap of the Frankincense tree was the basis for an extremely lucrative trade.

Landsat satellites have provided visible light and infrared images of the Earth continuously since 1972. SRTM topographic data match the 30-meter (99-foot)spatial resolution of most Landsat images and provide a valuable complement for studying the historic and growing Landsat data archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM project by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center,Sioux Falls, South Dakota.

Elevation data used in this image was acquired by SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar(SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was

SRTM Perspective View with Landsat Overlay: Santa Barbara, California

NASA Technical Reports Server (NTRS)

2001-01-01

Santa Barbara, California, is often called 'America's Riviera.' It enjoys a Mediterranean climate, a mountain backdrop, and a long and varied coastline. This perspective view of the Santa Barbara region was generated using data from the Shuttle Radar Topography Mission (SRTM) and an enhanced Landsat satellite image. The view is toward the northeast, from the Goleta Valley in the foreground to a snow-capped Mount Abel (elevation 2526 m or 8286 feet) along the skyline. The coast here generally faces south. Consequently, Fall and Winter sunrises occur over the ocean, which is unusual for the U.S. west coast. The Santa Barbara 'back country' is very rugged and largely remains as undeveloped wilderness and an important watershed for local communities. Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data match the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. For visualization purposes, topographic heights displayed in this image are exaggerated two times. Colors approximate natural colors.

The elevation data used in this image was acquired by SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of Earth's land surface.

To collect the 3-D SRTM data, engineers added a mast 60 meters (about 200-feet) long, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between the NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense, and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif, for NASA's Earth Science Enterprise,Washington, D.C. JPL

Land use change detection based on multi-date imagery from different satellite sensor systems

NASA Technical Reports Server (NTRS)

Stow, Douglas A.; Collins, Doretta; Mckinsey, David

1990-01-01

An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.