The Experts below are selected from a list of 117051 Experts worldwide ranked by ideXlab platform
Peng Gong - One of the best experts on this subject based on the ideXlab platform.
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land cover mapping and data availability in critical terrestrial ecoregions a global perspective with Landsat thematic mapper and enhanced thematic mapper plus data
Biological Conservation, 2015Co-Authors: Peng Gong, Yichuan ShiAbstract:Abstract Land cover provides objective and multi scale information on the extent and conditions of habitats both currently and retrospectively. Over four decades since the launch of the first land-observation satellite – Landsat-1 in 1972, a tremendous number of earth observation images have been acquired and archived. Here we examined land cover mapping in 142 critical terrestrial ecoregions (identified by WWF Global 200) from three aspects: Landsat Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) data availability, literature and existing global land cover map. We found that: (1) the availability of Landsat TM/ETM+ for historical land-cover change analysis in those ecoregions is poor. Only 17 ecoregions and 38 ecoregions have sufficient number of seasonal images in the Landsat archive for change analysis at 10-year and 5-year intervals, respectively. (2) Only 26 of 142 ecoregions belong to research hotspots of land cover mapping based on a spatialized literature database. (3) From a 30 m global land cover map (which is FROM-GLC, Finer Resolution Observation and Monitoring – Global Land Cover), only 28 ecoregions have greater than 80% map accuracy while 36 ecoregions have poorer than 50% map accuracy. Our finding suggests a significant gap of observation and understanding of these critical ecoregions from space, and an urgent need to meet the requirement of the conservation science community, in order for land cover data to fulfil its potential to timely monitor the loss of biodiversity from space, improve our knowledge of the state of conservation, and inform better decision making.
Dennis L. Helder - One of the best experts on this subject based on the ideXlab platform.
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radiometric cross calibration of Landsat 8 operational land imager oli and Landsat 7 enhanced thematic mapper plus etm
Remote Sensing, 2014Co-Authors: Nischal Mishra, Md Obaidul Haque, David Aaron, Dennis L. Helder, Larry Leigh, Brian L. MarkhamAbstract: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.
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Radiometric Calibration of the Landsat MSS Sensor Series
IEEE Transactions on Geoscience and Remote Sensing, 2012Co-Authors: Dennis L. Helder, David Aaron, Sadhana Karki, Rajendra Bhatt, Esad Micijevic, Benjamin JasinskiAbstract:Multispectral remote sensing of the Earth using Landsat sensors was ushered on July 23, 1972, with the launch of Landsat-1. Following that success, four more Landsat satellites were launched, and each of these carried the Multispectral Scanner System (MSS). These five sensors provided the only consistent multispectral space-based imagery of the Earth's surface from 1972 to 1982. This work focuses on developing both a consistent and absolute radiometric calibration of this sensor system. Cross-calibration of the MSS was performed through the use of pseudoinvariant calibration sites (PICSs). Since these sites have been shown to be stable for long periods of time, changes in MSS observations of these sites were attributed to changes in the sensors themselves. In addition, simultaneous data collections were available for some MSS sensor pairs, and these were also used for cross-calibration. Results indicated substantial differences existed between instruments, up to 16%, and these were reduced to 5% or less across all MSS sensors and bands. Lastly, this paper takes the calibration through the final step and places the MSS sensors on an absolute radiometric scale. The methodology used to achieve this was based on simultaneous data collections by the Landsat-5 MSS and Thematic Mapper (TM) instruments. Through analysis of image data from a PICS location and through compensating for the spectral differences between the two instruments, the Landsat-5 MSS sensor was placed on an absolute radiometric scale based on the Landsat-5 TM sensor. Uncertainties associated with this calibration are considered to be less than 5%.
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free access to Landsat imagery
Science, 2008Co-Authors: Curtis E Woodcock, Eileen H. Helmer, Robert Bindschadler, A. S. Belward, Warren B Cohen, Martha C Anderson, Richard G Allen, Samuel N. Goward, Dennis L. Helder, Ramakrishna R. NemaniAbstract:![Figure][1] Free image. This Landsat 5 image of the southeastern corner of the Black Sea is part of the general U.S. archive that will be accessible for free under the new USGS policy. CREDIT: BOSTON UNIVERSITY CENTER FOR REMOTE SENSING We are entering a new era in the Landsat Program, the oldest and most venerable of our Earth-observing satellite programs. With little fanfare, the U.S. Geological Survey (USGS) has begun providing imagery for free over the Internet. Throughout the history of the Landsat Program, the cost and access to imagery has always limited our ability to study our planet and the way it is changing. Beginning with a pilot program to provide “Web-enabled” access to Landsat 7 images of the United States that were collected between 2003 and this year, the USGS now plans to provide top-quality image products for free upon request for the entire U.S. archive, including over 2 million images back to Landsat 1 (1972) [for details and schedules, see ([1][2])]. The release by NASA and the USGS in January 2008 of a new Landsat Data Distribution Policy ([2][3]) was a key step to this goal. Free imagery will enable reconstruction of the history of Earth's surface back to 1972, chronicling both anthropogenic and natural changes during a time when our population doubled and the impacts of climate change became noticeable. The Landsat Science Team: 1. 1.[↵][4]USGS Technical Announcement ([http://Landsat.usgs.gov/images/squares/USGS\_Landsat\_Imagery_Release.pdf][5]). 2. 2.[↵][6]Landsat Missions ([http://ldcm.usgs.gov/pdf/Landsat\_Data\_Policy.pdf][7]). [1]: pending:yes [2]: #ref-1 [3]: #ref-2 [4]: #xref-ref-1-1 "View reference 1. in text" [5]: http://Landsat.usgs.gov/images/squares/USGS_Landsat_Imagery_Release.pdf [6]: #xref-ref-2-1 "View reference 2. in text" [7]: http://ldcm.usgs.gov/pdf/Landsat_Data_Policy.pdf
Brian L. Markham - One of the best experts on this subject based on the ideXlab platform.
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radiometric cross calibration of Landsat 8 operational land imager oli and Landsat 7 enhanced thematic mapper plus etm
Remote Sensing, 2014Co-Authors: Nischal Mishra, Md Obaidul Haque, David Aaron, Dennis L. Helder, Larry Leigh, Brian L. MarkhamAbstract: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.
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radiometric calibration of Landsat
Photogrammetric Engineering and Remote Sensing, 1997Co-Authors: John L Barker, Philip N Slater, Brian L. Markham, Kurtis J. Thome, Stuart F. BiggarAbstract:The radiometric calibration of the sensors on the Landsat se- ries of satellites is a contributing factor to the success of the Landsat data set. The calibration of these sensors has relied on the preflight laboratory work as well as on inflight tech- niques using on-board calibrators and vicarious techniques. Descriptions of these methods and systems are presented. Results of the on-board calibrators and reflectance-based, ground reference calibrations of Landsat 5 Thematic Mapper are presented that indicate the absolute radiometric calibra- tion of bands 1 to 4 should have an uncertainty of less than 5.0 percent. Bands 5 and 7 have slightly higher uncertainties, but should be less than 10 percent. The results also show that the on-board calibrators are of higher precision than the vicarious calibration but that the vicarious calibration results should have higher accuracy. Introduction The Landsat series of satellites provides the longest running continuous data set of high spatial-resolution imagery dating back to the launch of Landsat 1 in 1972. Part of the success of the Landsat program has been the ability to understand the radiometric properties of the sensors. This understanding has been due to the combination of prelaunch and post- launch efforts using laboratory, on-board, and vicarious cali- bration methods. The radiometric calibration of these systems helps characterize the operation of the sensors, but more importantly, the calibration allows the full Landsat data set to be used in a quantitative sense. A brief overview of the Landsat systems is given here, but the reader is directed to Engel and Weinstein (1983), Lansing and Cline (1975), Markham and Barker (1987), and Slater (1980) for detailed descriptions. The Landsat series of satellites can be viewed in two distinct parts. The first in- cludes Landsats 1, 2, and 3 that carried two sensor systems: the return beam vidicon (RBV) and the Multispectral Scanner (MSS) system. The RBv camera systems on Landsats 1 and 2 were multispectral with three cameras, while the system on Landsat 3 used only two cameras in a panchromatic mode. Landsats 1, 2, and 3 operated in a glg-krn, sun-synchronous orbit with an 18-day repeat cycle. The second phase of Land- sat includes Landsats 4 and 5. These platforms omitted the RBV cameras but still carried the Mss. These two platforms also carried the Thematic Mapper (TM), and their orbits were lowered to 705 krn with a 16-day repeat cycle. The MSS is a 6-bit, whiskbroom sensor with six detectors for each of its four bands. These bands are centered roughly at 0.55, 0.65, 0.75, and 0.85 pm (the MSS on Landsat 3 also had a fifth band between 10.4 and 12.6 pm). Bands 1 to 3 use photomultiplier tubes, while band 4 uses photodiodes. The MSS only collects data in one scan direction, and there is no compensation in the scan for the forward motion of the platform. At the end of every other scan, a rotating shutter and mirror assembly allows light from a calibration lamp to reach the detectors. The TM is also a whiskbroom system but it scans in both the forward and backward cross-track directions, and it cor- rects for the forward motion of the platform. In addition, the TM has 8-bit radiometric resolution and seven bands. Bands 1 to 5 and 7 each have 16 detectors with center wavelengths of roughly 0.49, 0.56, 0.66, 0.83, 1.67, and 2.24 Fm. Band 6 has four detectors and is centered around 11.5 pm. Bands 1 to 4 use silicon-based detectors, bands 5 and 7 use indium antimonide detectors, and band 6 uses mercury-cadmium-tel- luride detectors. Bands 5, 6, and 7 are part of the cold-focal plane that is cooled to 85°K through the use of a radiative cooler. The TM has an on-board calibration system composed of a shutter that oscillates rather than rotates and allows cali- bration data to be collected at the end of each scan. A great deal of research was done during the early days
David Aaron - One of the best experts on this subject based on the ideXlab platform.
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radiometric cross calibration of Landsat 8 operational land imager oli and Landsat 7 enhanced thematic mapper plus etm
Remote Sensing, 2014Co-Authors: Nischal Mishra, Md Obaidul Haque, David Aaron, Dennis L. Helder, Larry Leigh, Brian L. MarkhamAbstract: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.
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Radiometric Calibration of the Landsat MSS Sensor Series
IEEE Transactions on Geoscience and Remote Sensing, 2012Co-Authors: Dennis L. Helder, David Aaron, Sadhana Karki, Rajendra Bhatt, Esad Micijevic, Benjamin JasinskiAbstract:Multispectral remote sensing of the Earth using Landsat sensors was ushered on July 23, 1972, with the launch of Landsat-1. Following that success, four more Landsat satellites were launched, and each of these carried the Multispectral Scanner System (MSS). These five sensors provided the only consistent multispectral space-based imagery of the Earth's surface from 1972 to 1982. This work focuses on developing both a consistent and absolute radiometric calibration of this sensor system. Cross-calibration of the MSS was performed through the use of pseudoinvariant calibration sites (PICSs). Since these sites have been shown to be stable for long periods of time, changes in MSS observations of these sites were attributed to changes in the sensors themselves. In addition, simultaneous data collections were available for some MSS sensor pairs, and these were also used for cross-calibration. Results indicated substantial differences existed between instruments, up to 16%, and these were reduced to 5% or less across all MSS sensors and bands. Lastly, this paper takes the calibration through the final step and places the MSS sensors on an absolute radiometric scale. The methodology used to achieve this was based on simultaneous data collections by the Landsat-5 MSS and Thematic Mapper (TM) instruments. Through analysis of image data from a PICS location and through compensating for the spectral differences between the two instruments, the Landsat-5 MSS sensor was placed on an absolute radiometric scale based on the Landsat-5 TM sensor. Uncertainties associated with this calibration are considered to be less than 5%.
Yichuan Shi - One of the best experts on this subject based on the ideXlab platform.
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land cover mapping and data availability in critical terrestrial ecoregions a global perspective with Landsat thematic mapper and enhanced thematic mapper plus data
Biological Conservation, 2015Co-Authors: Peng Gong, Yichuan ShiAbstract:Abstract Land cover provides objective and multi scale information on the extent and conditions of habitats both currently and retrospectively. Over four decades since the launch of the first land-observation satellite – Landsat-1 in 1972, a tremendous number of earth observation images have been acquired and archived. Here we examined land cover mapping in 142 critical terrestrial ecoregions (identified by WWF Global 200) from three aspects: Landsat Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) data availability, literature and existing global land cover map. We found that: (1) the availability of Landsat TM/ETM+ for historical land-cover change analysis in those ecoregions is poor. Only 17 ecoregions and 38 ecoregions have sufficient number of seasonal images in the Landsat archive for change analysis at 10-year and 5-year intervals, respectively. (2) Only 26 of 142 ecoregions belong to research hotspots of land cover mapping based on a spatialized literature database. (3) From a 30 m global land cover map (which is FROM-GLC, Finer Resolution Observation and Monitoring – Global Land Cover), only 28 ecoregions have greater than 80% map accuracy while 36 ecoregions have poorer than 50% map accuracy. Our finding suggests a significant gap of observation and understanding of these critical ecoregions from space, and an urgent need to meet the requirement of the conservation science community, in order for land cover data to fulfil its potential to timely monitor the loss of biodiversity from space, improve our knowledge of the state of conservation, and inform better decision making.
