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At least 253 records · Page 14Linked to original sources
USGS2005

Global Visualization (GloVis) Viewer

GloVis (http://glovis.usgs.gov) is a browse image-based search and order tool that can be used to quickly review the land remote sensing data inventories held at the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS). GloVis was funded by the AmericaView project to reduce the difficulty of identifying and acquiring data for user-defined study areas. Updated daily with the most recent satellite acquisitions, GloVis displays data in a mosaic, allowing users to select any area of interest worldwide and immediately view all available browse images for the following Landsat data sets: Multispectral Scanner (MSS), Multi-Resolution Land Characteristics (MRLC), Orthorectified, Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and ETM+ Scan Line Corrector-off (SLC-off). Other data sets include Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS), Aqua MODIS, and the Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion data.

Fact Sheet↗
USGS2013

Landsat surface reflectance quality assurance extraction (version 1.7)

The U.S. Geological Survey (USGS) Land Remote Sensing Program is developing an operational capability to produce Climate Data Records (CDRs) and Essential Climate Variables (ECVs) from the Landsat Archive to support a wide variety of science and resource management activities from regional to global scale. The USGS Earth Resources Observation and Science (EROS) Center is charged with prototyping systems and software to generate these high-level data products. Various USGS Geographic Science Centers are charged with particular ECV algorithm development and (or) selection as well as the evaluation and application demonstration of various USGS CDRs and ECVs. Because it is a foundation for many other ECVs, the first CDR in development is the Landsat Surface Reflectance Product (LSRP). The LSRP incorporates data quality information in a bit-packed structure that is not readily accessible without postprocessing services performed by the user. This document describes two general methods of LSRP quality-data extraction for use in image processing systems. Helpful hints for the installation and use of software originally developed for manipulation of Hierarchical Data Format (HDF) produced through the National Aeronautics and Space Administration (NASA) Earth Observing System are first provided for users who wish to extract quality data into separate HDF files. Next, steps follow to incorporate these extracted data into an image processing system. Finally, an alternative example is illustrated in which the data are extracted within a particular image processing system.

Techniques and Methods↗
USGS1998

North American landscape characterization project: The production of a continental scale three-decade Landsat data set

The North American Landscape Characterization (NALC) project is a component of the National Aeronautics and Space Administration (NASA) Landsat Pathfinder program. Pathfinder projects are focused on the investigation of global change utilizing current remote sensing technologies. The NALC project is a cooperative effort between the U. S. Environmental Protection Agency (EPA), the U.S. Geological Survey (USGS), and NASA to make Landsat data available to the widest possible user community for scientific research and general public interest. The NALC project is principally funded by the EPA Office of Research and Development and the USGS's Earth Resources Observation Systems (EROS) Data Center (EDC). The objectives of the NALC project are to produce standardized remote sensing data sets, develop standardized analysis methods, and derive standardized land cover change products for a large portion of the North American continent (the conterminous United States and Mexico) (Lunetta and Sturdevant, 1993). The standard product is the NALC “triplicate”;, consisting of co‐registered Landsat multispectral scanner data for the years 1973, 1986, and 1991 (plus or minus one year), plus co‐registered 3 arcsecond digital terrain elevation data. Processing began with the 1986 scene, which was precision corrected (with full terrain correction) to a 60 meter Universal Transverse Mercator base. Automated cross‐correlation procedures were used to co‐register the 1970's and 1990's data to the 1980's base, and independent verifications of registration quality were performed on all triplicate components. The pertinent metadata were compiled in a relational database, which includes WRS2 path/rows, scene ID's, image dates, solar azimuth and elevation, verification RMSE's, and the number of verification control points. NALC triplicate data sets are being used for a number of applications, including the analysis of urbanization patterns, dynamics of climatic fluctuations, deforestation studies, and vegetation classification and mapping. These data are being distributed through the Earth Observing System Data and Information System (EOSDIS) Information Management System (IMS) at a cost of $15(U.S.) for each triplicate.

Geocarto International↗
USGS2017

Landsat Science Team: 2017 Winter meeting summary

The winter meeting of the NASA-U.S. Geological Survey (USGS) Landsat Science Team (LST) was held January 10-12, 2017, at Boston University. LST co-chairs Tom Loveland [USGS’s Earth Resources Observation and Science Center (EROS)—Senior Scientist], Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Deputy Director, Earth Sciences Division], and Curtis Woodcock [Boston University—Professor and LST Co-Leader] welcomed the participants to the three-day meeting. The group immediately and enthusiastically recognized Woodcock’s receipt of the 2016 Pecora Award. Loveland summarized the primary meeting objectives to identify priorities for future Landsat measurements and to begin identifying next-generation Landsat products. He also discussed USGS’s plans to issue a request for proposals for membership on the 2018-2023 LST (i.e., the next five-year term). Irons stressed Landsat’s bipartisan support but cautioned against complacency when looking toward future capabilities. Meeting presentations are available at https://landsat.usgs.gov/landsat-science-teammeeting-jan-10-12-2017.

The Earth Observer↗
USGS2013

Applications of spectral band adjustment factors (SBAF) for cross-calibration

To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earth's surface acquired from multiple spaceborne imaging sensors. However, an integrated global observation framework requires an understanding of how land surface processes are seen differently by various sensors. This is particularly true for sensors acquiring data in spectral bands whose relative spectral responses (RSRs) are not similar and thus may produce different results while observing the same target. The intrinsic offsets between two sensors caused by RSR mismatches can be compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of the two sensors. The motivation of this work comes from the need to compensate the spectral response differences of multispectral sensors in order to provide a more accurate cross-calibration between the sensors. In this paper, radiometric cross-calibration of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors was performed using near-simultaneous observations over the Libya 4 pseudoinvariant calibration site in the visible and near-infrared spectral range. The RSR differences of the analogous ETM+ and MODIS spectral bands provide the opportunity to explore, understand, quantify, and compensate for the measurement differences between these two sensors. The cross-calibration was initially performed by comparing the top-of-atmosphere (TOA) reflectances between the two sensors over their lifetimes. The average percent differences in the long-term trends ranged from $-$5% to $+$6%. The RSR compensated ETM+ TOA reflectance (ETM+$^{ast}$) measurements were then found to agree with MODIS TOA reflectance to within 5% for all bands when Earth Observing-1 Hy- erion hyperspectral data were used to produce the SBAFs. These differences were later reduced to within 1% for all bands (except band 2) by using Environmental Satellite Scanning Imaging Absorption Spectrometer for Atmospheric Cartography hyperspectral data to produce the SBAFs.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2025

ECCOE Landsat quarterly Calibration and Validation report—Quarter 4, 2024

Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The Earth Resources Observation and Science Cal/Val Center of Excellence Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level. This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 4 (October–December) of 2024. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov .

Open-File Report↗
USGS2025

System characterization report on the Environmental Mapping and Analysis Program (EnMAP)

This report addresses system characterization of the Environmental Mapping and Analysis Program hyperspectral sensor by the DLR (German Aerospace Center, ground segment project management), GFZ (Deutsches Geoforschungszentrum, science lead) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the EnMAP hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), and radiometric performances of the EnMAP hyperspectral sensor. Results of these analyses indicate that the Environmental Mapping and Analysis Program has a band-to-band geometric performance in the range of −0.135 to 0.15 pixel, geometric performance relative to the Operational Land Imager in the range of −27.716 meters (−0.92 pixel) to 32.892 meters (1.09 pixels) offset in comparison to Landsat 8 Operational Land Imager, offset of a radiometric comparison in the range of −0.012 to 0.020, slope of a radiometric comparison in the range of 0.947 to 1.031.

Open-File Report↗
USGS2022

System characterization report on PRecursore IperSpettrale della Missione Applicativa (PRISMA)

Executive Summary This report addresses system characterization of the Italian Space Agency’s PRecursore IperSpettrale della Missione Applicativa (PRISMA) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (band to band and image to image), radiometric, and spatial performances. Results of these analyses indicate that PRISMA has a band-to-band geometric performance in the range of −0.046 to 0.040 pixel; an image-to-image geometric performance (relative to the Landsat 8 Operational Land Imager) in the range of −60.791 meters (m; −2.03 pixels) to 299.541 m (9.98 pixels); a radiometric performance in the range of −0.037 to −0.001 in offset and 1.026 to 1.274 in slope; and a spatial performance with a relative edge response in the range of 0.56 to 0.63, full width at half maximum in the range of 1.84 to 1.97 pixels, and a modulation transfer function at a Nyquist frequency in the range of 0.054 to 0.096. Regarding fairly large geometric accuracy, the following explanation is provided to help the reader. The geometric accuracy required for PRISMA is a 200-m circular error at 90 percent (CE90) without ground control points (GCPs), a 15-m CE90 using GCPs is documented in the PRISMA mission overview (Agenzia Spaziale Italiana, 2021). The PRISMA images used for the current system characterization were georeferenced without using any GCPs; thus, the 200-m geometric accuracy requirement is applied. Beginning in 2022, a worldwide GCP database will be used in the PRISMA product processing chain, which will improve georeferencing accuracy to meet the 15-m CE90 requirement.

Open-File Report↗
USGS2024

System characterization report on the Earth Surface Mineral Dust Source Investigation (EMIT) sensor

Executive Summary This report addresses system characterization of the Earth Surface Mineral Dust Source Investigation (EMIT) sensor, an imaging spectrometer developed by the National Aeronautics and Space Administration. This report is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior) and radiometric performances. Results of these analyses indicate that the EMIT sensor has a band-to-band geometric performance in the range of −0.355 to 0.210 pixel with a few exceptions of shortwave infrared channels. Geometric offset relative to the Landsat 8 Operational Land Imager ranged from −15.966 meters (−0.266 pixel) to 43.844 meters (0.731 pixel). Offset of a radiometric comparison ranged from −0.016 to 0.025, and slope of a radiometric comparison ranged from 0.837 to 0.985. EMIT agreed with Radiometric Calibration Network measurements within 5 percent across most of the spectral channels.

Open-File Report↗
USGS2026

System characterization report on Tanager

Executive Summary This report addresses the system characterization of the Tanager satellite hyperspectral sensor created by Planet Labs PBC and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the Tanager hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. This report summarizes the sensor performance of the Tanager based on the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence system characterization process. In summary, we determined that the Tanager exhibits a band- to- band geometric error ranging from −0.074 to 0.097 pixel. Compared to the Landsat Operational Land Imager, geometric offsets ranged from −5.980 meters (−0.20 pixel) to 11.348 meters (0.40 pixel). Radiometric comparisons showed offsets between −0.004 and 0.056 with slopes from 0.830 to 1.066. Spectral shifts are found between 0.65 and 0.75 nanometers. Finally, spatial performance evaluation yielded a point spread function full width at half maximum of 1.27 to 1.75 pixels, a relative edge response of 0.802 to 0.651, and a modulation transfer function at Nyquist of 0.488 to 0.253.

Open-File Report↗
USGS2026

Landsat 8–9 geometric and radiometric calibration and characterization

The U.S. Geological Survey Earth Resources Observation and Science Cal/Val (Calibration and Validation) Center of Excellence is a global leader in improving the accuracy, precision, and quality of remote-sensing data. Calibration is the process of quantitatively defining a system’s response to known and controlled signal inputs. Validation is the process of assessing, by independent means, the quality of the calibrated data products derived from system outputs. The Landsat Cal/Val team, comanaged by the Earth Resources Observation and Science Cal/Val Center of Excellence and the National Aeronautics and Space Administration Landsat Science Project, continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level, ensuring its reliability for scientific research. Landsat data quality is often referred to as the “gold standard” and gives other civil and commercial satellite programs a trusted reference point for measuring their own data quality. The Landsat program started more than 50 years ago. Since then, Landsat missions have gone through multiple technological advances, which, together with improved calibration and validation techniques, have led to higher data quality over time. The Cal/Val team also maintains consistency in data calibration across the multiple generations of sensors, which is vital to many scientists for time-series analysis.

Fact Sheet↗
USGS2021

System characterization report on the WorldView-3 Imager

Executive Summary This report addresses system characterization of the Maxar WorldView-3 satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2020. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. WorldView-3 is a high-resolution multispectral satellite launched in 2014 by Maxar Technologies on an Atlas V launch vehicle from Vandenberg Air Force Base in California for Earth resources monitoring. WorldView-3 provides substantial technical improvements to previous WorldView satellites, including spectral bands, ground sample distance, and swath. The WorldView-3 satellite was designed and built by Lockheed Martin for Maxar Technologies using the BCP–5000 bus with the WorldView-3 Imager and the Clouds, Aerosols, Vapors, Ice, and Snow sensor. The high-resolution WorldView-3 Imager is the main instrument, and the Clouds, Aerosols, Vapors, Ice, and Snow sensor provides additional data on obscurants and other atmospheric effects used in data production. More information on Maxar WorldView satellites and sensors is available within the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.maxar.com/ . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that WorldView-3 has a range of interior geometric performance of −0.09 (−0.07 pixel) to 0.24 meter (0.19 pixel) in band-to-band registration; an exterior geometric performance in the range of a −21.10- (−2.11 pixels) to 28.23-meter (2.82 pixels) offset in comparison to Sentinel-2; a radiometric performance in the range of −0.121 to 1.420 (offset and slope); and a spatial performance in the range of 1.2 to 1.7 pixels at full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.093 to 0.185.

Open-File Report↗
USGS2018

An overview of USGS-NASA Landsat Science activities during 2018

Two meetings of the U.S. Geological Survey (USGS)-NASA Landsat Science Team (LST) took place in 2018. The USGS Earth Resources Observation and Science (EROS) Center hosted the winter meeting, which took place February 21-22 in Sioux Falls, SD. The University of Colorado-Boulder hosted the summer meeting, which was held August 8-10 in Boulder, CO.

The Earth Observer↗
USGS2017

Effect of NOAA satellite orbital drift on AVHRR-derived phenological metrics

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, −14, −16, −17, −18, and −19). Each NOAA satellite experienced orbital drift during its duty period, which influenced the AVHRR reflectance measurements. To understand the effect of the orbital drift on the AVHRR-derived RSP dataset, we analyzed the impact of solar zenith angle (SZA) on the RSP metrics in the conterminous United States (CONUS). The AVHRR weekly composites were used to calculate the growing-season median SZA at the pixel level for each year from 1989 to 2014. The results showed that the SZA increased towards the end of each NOAA satellite mission with the highest increasing rate occurring during NOAA-11 (1989–1994) and NOAA-14 (1995–2000) missions. The growing-season median SZA values (44°–60°) in 1992, 1993, 1994, 1999, and 2000 were substantially higher than those in other years (28°–40°). The high SZA in those years caused negative trends in the SZA time series, that were statistically significant (at α = 0.05 level) in 76.9% of the CONUS area. A pixel-based temporal correlation analysis showed that the phenological metrics and SZA were significantly correlated (at α = 0.05 level) in 4.1–20.4% of the CONUS area. After excluding the 5 years with high SZA (>40°) from the analysis, the temporal SZA trend was largely reduced, significantly affecting less than 2% of the study area. Additionally, significant correlation between the phenological metrics and SZA was observed in less than 7% of the study area. Our study concluded that the NOAA satellite orbital drift increased SZA, and in turn, influenced the phenological metrics. Elimination of the years with high median SZA reduced the influence of orbital drift on the RSP time series.

International Journal of Applied Earth Observation↗
USGS2021

System characterization report on the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS)

Executive Summary This report addresses system characterization of the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present the methodology and procedures for characterization and the technical and operational information about the specific sensing system being evaluated. These reports also provide a description of data measurements, data retention practices, and data analysis results and provide system characterization conclusions. In partnership with Teledyne Brown Engineering, DLR built the DESIS hyperspectral instrument, which Teledyne Brown Engineering then integrated onto its International Space Station-based imaging platform, the Multi-User System for Earth Sensing. DLR developed the processing software and, together with Innovative Imaging and Research, completes the validation and calibration of the data products. DESIS was launched in 2018, and the data are used for scientific research in atmospheric physics and Earth sciences. The DESIS sensor contributes to the scientific and commercial utilization of the International Space Station and helps to further hyperspectral remote sensing technologies for future satellites. More information on DLR satellites and sensors is included within the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and at https://www.dlr.de/DE/Home/home_node.html . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that DESIS has an interior geometric performance of less than a 3.30-meter (less than 0.11 pixel) root mean square error in band-to-band registration, an exterior geometric performance in the range of a 2.40- (0.08 pixel) to 17.40-meter (0.58 pixel) offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.013 to 1.011 (offset and slope), and a spatial performance for band 130 of 1.5 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency of 0.167.

Open-File Report↗
USGS2021

System characterization report on the China-Brazil Earth Resources Satellite-4A (CBERS–4A)

Executive Summary This report addresses system characterization of the China-Brazil Earth Resources Satellite-4A (CBERS–4A) multispectral remote sensing satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2021. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. CBERS–4A is a joint Chinese-Brazilian medium-resolution satellite launched in December 2019 by the China National Space Agency/National Institute for Space Research (Brazil) on a Chang Zheng 4B rocket from the Taiyuan Satellite Launch Center for Earth resources monitoring. The CBERS–4A mission continues the CBERS mission that has been in continual operation since the launch of CBERS–1 in 1999. The CBERS–4A satellite was designed and built by Academia Chinesa de Tecnologia Espacial/National Institute for Space Research and uses the Phoenix-Eye bus. CBERS–4A carries the multispectral camera and wide field imager sensors for medium-resolution land imaging and the wide swath panchromatic and multispectral camera sensor for high-resolution land imaging. This assessment focused on the multispectral camera sensor only. More information on CBERS sensors is available in the “ 2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium ” and at https://www.gov.br/pt-br/servicos/obter-imagens-de-sensoriamento-remoto-da-terra-geradas-pelo-satelite-cbers-04a . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that CBERS–4A provides an interior (band-to-band) geometric performance in the range of −0.02 to −0.16 pixel; an exterior geometric accuracy performance of −22.02 (−1.47 pixels) to −16.06 meters (−1.07 pixels); a radiometric accuracy performance of –0.006 to 0.925 (offset and slope); and a spatial performance for relative edge response in the range of 0.39 to 0.44, for full width at half maximum in the range of 2.38 to 2.56 pixels, and for a modulation transfer function at a Nyquist frequency in the range of 0.001 to 0.013.

Open-File Report↗
USGS2022

System characterization report on the Amazônia-1 multispectral sensor

Executive Summary This report addresses system characterization of the Instituto Nacional de Pesquisas Espaciais Amazônia-1 satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. Amazônia-1 is a four-band imager with a 64-meter (m) pixel ground sample distance. Amazônia-1 was launched in February 2021 into a Sun-synchronous orbit of 752 kilometers with an inclination of 98.4 degrees and a swath width of 850 kilometers. The satellite has an expected lifetime of about 4 years. More information on Amazônia-1 is available in the “Land Remote Sensing Satellites Online Compendium” ( https://calval.cr.usgs.gov/apps/compendium ). The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that the Amazônia-1 satellite has an interior geometric performance in the range of −3.584 m (−0.056 pixel) to 0.320 m (0.005 pixel) in easting and −1.984 m (−0.031 pixel) to 2.048 m (0.032 pixel) in northing in band-to-band registration, an exterior geometric performance of −37.256 m (−0.621 pixel) to 54.758 m (0.913 pixel) in easting and −12.684 m (−0.211 pixel) to 54.898 m (0.915 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of 0.030 to 0.143 in offset and 0.662 to 0.825 in slope, and a spatial performance in the range of 1.62 to 2.06 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.062 to 0.115.

Open-File Report↗
USGS2018

2017 Landsat Science Team Summer Meeting Summary

The summer meeting of the U.S. Geological Survey (USGS)-NASA Landsat Science Team (LST) was held June 11-13, 2017, at the USGS’s Earth Resources Observation and Science (EROS) Center near Sioux Falls, SD. This was the final meeting of the Second (2012-2017) LST.1 Frank Kelly [EROS—Center Director] welcomed the attendees and expressed his thanks to the LST members for their contributions. He then introduced video-recorded messages from South Dakota’s U.S. senators, John Thune and Mike Rounds, in which they acknowledged the efforts of the team in advancing the societal impacts of the Landsat Program.

The Earth Observer↗