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USGS2025

System characterization report on Resourcesat-2A Linear Imaging Self Scanning-4 sensor

Executive Summary This report documents the system characterization of the Indian Space Research Organisation Resourcesat-2A Linear Imaging Self Scanning-4 (LISS–4) sensor. It is part of a series of system characterization reports produced by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports describe the methodology and procedures used 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. Resourcesat-2A was launched in 2016 on the Polar Satellite Launch Vehicle-C36; it is identical to Resourcesat-2, and together, they decrease imaging revisit time from 5 days to 2–3 days, providing data continuity and improved temporal resolution. Resouresat-2 and 2A carry the Advanced Wide Field Sensor, Linear Imaging Self Scanning-3, and LISS–4 medium-resolution imaging sensors, continuing the legacy of the Indian Space Research Organisation’s Indian Remote Sensing-1C/1D/P3 satellite programs. More information about the Indian Space Research Organisation’s satellites and sensors is available through the Joint Agency Commercial Imagery Evaluation Earth Observing Satellites Online Compendium at https://calval.cr.usgs.gov/apps/compendium/ and from the manufacturer at https://www.isro.gov.in/ . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team assessed the geometric, radiometric, and spatial performances of the Resourcesat-2A LISS–4 sensor. Geometric performance is divided into the interior geometric performance of band-to-band registration and the exterior geometric performance of geolocation accuracy. The interior geometric performance had mean offsets in the range of −0.118 to 0.024 pixel in easting and −0.053 to 0.022 pixel in northing with root mean square error values from 0.067 to 0.230 pixel in easting and from 0.087 to 0.2 pixel in northing. The exterior geometric performance had offsets in the range of 2.55 to 7.85 meters (m) in easting and −6.15 to 11.15 m in northing with root mean square error values in the range of 2.6 to 8.2 m in easting and 6.35 to 11.8 m in northing compared to the U.S. Department of Agriculture National Agriculture Imagery Program and WorldView-3 orthoimages. The measured radiometric performance had offsets from 0.003 to 0.024 and slopes from 0.736 to 0.952, and spatial performance was in the range of 1.633 to 1.903 pixels for the full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.0529 to 0.0952.

Open-File Report↗
USGS2025

System characterization report on Resourcesat-2A Linear Imaging Self Scanning-3 sensor

Executive Summary This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2A Linear Imaging Self Scanning-3 sensor 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 since 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. Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 for continuity of data and improved temporal resolution. The Resourcesat-2 platform (which includes Resourcesat-2A) is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the Linear Imaging Self Scanning-3 and Linear Imaging Self Scanning-4 sensors for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/ . 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. To summarize the results, we have determined that this sensor provides an interior geometric performance with mean offsets in the range of 1.75 meters (m; 0.06 pixel) to 6.83 m (0.23 pixel) in easting and −1.83 m (−0.06 pixel) to 1.81 m (0.06 pixel) in northing in band-to-band registration and a root mean square error in the range of 3.81 m (0.13 pixel) to 8.19 m (0.27 pixel) in easting and 2.21 m (0.09 pixel) to 4.72 m (0.16 pixel) in northing. We have measured an exterior geometric error offset in the range of −21.29 to 6.88 m in easting and −7.35 to −2.63 m in northing, and the root mean square error is in the range of 7.19 to 21.43 m in easting and 3.64 to 8.19 m in northing in comparison to the Landsat 8 Operational Land Imager. The measured radiometric performance was in the range of −0.002 to 0.031 in offset and 0.701 to 0.940 in slope, and the spatial performance was in the range of 1.204 to 1.265 pixels for full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.251 to 0.277.

Open-File Report↗
USGS1987

Reflections on writing hydrologic reports

Reporting of scientific work should be characterized by a logical argument that is developed through presentation of the problem, tabulation and display of data pertinent to the problem , and testing and interpretation of the data to prove hypotheses that address the problem. Organization of the report is vital to developing this logical argument: it provides structure, continuity, logic, and emphasis to the presentation. Each part of the report serves a specific function and each is linked by a connecting logic, the logical argument of the report. Each scientific report normally has a title, table of contents, abstract, introduction, body (of the report), and summary and/or conclusions. Organization of sections within the body of the report is exactly parallel to overall organization; subjects presented in the section title are developed by logical subdivisions and pertinent discussion. The summary and/or conclusions section culminates the logical argument of the report by drawing together and quantitatively reiterating the principal conclusions developed in the discussion. Supplemental information on report content, background of the study, additional data or details on procedures, and other information of interest to the reader is presented in the foreward or preface, list of illustrations or tables, glossaries, and appendixes. (Lantz-PTT)

Open-File Report↗
USGS1947

Summary of records of surface waters at stations on tributaries in lower Colorado River Basin, 1888-1938

This report presents summaries of records of discharge at gaging stations on tributaries in the Lower Colorado River Basin. The lower Colorado River Basin as used in this report is the "lower basin" defined in the Colorado River Compact, as that part of the Colorado River Basin below a point 1 mile downstream from the mouth of Paria River. Records for Paria River, also included in this report, when combined with those for Colorado River at Lees Ferry show the flow at the point of division between the upper and lower basins. This report and water-Supply Paper 918, "Summary of Records of Surface waters at Base Stations in Colorado River Basin, 1891-1938", furnish a complete compilation of all records of surface waters collected by the Geological Survey in the Lower Colorado River Basin prior to October 1, 1938, and contain all stream-flow records collected in Arizona prior to that date. Records for 16 gaging stations, which are base stations on tributaries and canals, are given in both reports.

Colorado River Basin↗
USGS2021

Summary of the final report from the Ice and Climate Evolution Science Analysis group (ICE-SAG)

The Ice and Climate Evolution Science Analysis Group (ICE-SAG) was convened by the Mars Exploration Program Analysis Group (MEPAG) in fall 2018, with the aims of (1) identifying and prioritizing fundamental science questions related to the recent and ongoing evolution of Mars volatiles and climate, and (2) exploring new mission approaches that could address these high-priority science questions during the coming decade (2023–2032). In this white paper, we summarize the ICE-SAG final report via a selection of report materials and provide broad context for the content of this MEPAG-generated report (which is likely a reference mentioned within a number of other, community-based white papers).

Bulletin of the AAS↗
USGS2021

System characterization report on Resourcesat-2 Linear Imaging Self Scanning-3 (LISS–3) sensor

Executive Summary This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2 Linear Imaging Self Scanning-3 (LISS–3) sensor 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. Resourcesat-2 is a medium-resolution satellite launched in 2011 on the Polar Satellite Launch Vehicle-C16 launch vehicle. Resourcesat-2 carries the same sensing elements as Resourcesat-1 (launched in October 2003) and provides continuity for the mission. The objectives of the Resourcesat mission are to provide remote sensing data services to global users, focusing on data for integrated land and water resources management. Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 launch vehicle for continuity of data and improved temporal resolution. The two satellites operating in tandem improved the revisit capability from 5 days to 2–3 days. The Resourcesat-2 platform is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the Advanced Wide Field Sensor and LISS–3, as well as the Linear Imaging Self Scanning-4 for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/ . 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 LISS–3 has an interior geometric performance in the range of −4.620 (−0.154 pixel) to 13.230 meters (m; 0.441 pixel) in easting and −12.360 (−0.412 pixel) to 1.500 m (0.050 pixel) in northing in band-to-band registration, an exterior geometric error of −27.805 (−0.927 pixel) to 26.578 m (0.886 pixel) in easting and −35.341 (−1.178 pixel) to −6.286 m (−0.210 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.096 to 0.036 in offset and 0.585–0.946 in slope, and a spatial performance in the range of 1.87–1.95 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.045–0.070.

Open-File Report↗
USGS2016

Mineral commodity summaries 2016

This report is the earliest Government publication to furnish estimates covering 2015 nonfuel mineral industry data. Data sheets contain information on the domestic industry structure, Government programs, tariffs, and 5-year salient statistics for more than 90 individual minerals and materials

Mineral Commodity Summaries↗
USGS2017

Mineral commodity summaries 2017

This report is the earliest Government publication to furnish estimates covering 2016 nonfuel mineral industry data. Data sheets contain information on the domestic industry structure, Government programs, tariffs, and 5-year salient statistics for more than 90 individual minerals and materials.

Mineral Commodity Summaries↗
USGS2018

Mineral commodity summaries 2018

This report is the earliest Government publication to furnish estimates covering 2017 nonfuel mineral industry data. Data sheets contain information on the domestic industry structure, Government programs, tariffs, and 5-year salient statistics for more than 90 individual minerals and materials.

Mineral Commodity Summaries↗
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↗
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↗
USGS1996

Mineral Commodity Summaries 1996

This report is the earliest Government publication to furnish estimates covering 1995 nonfuel mineral industry data. Most of the estimates are based on at least 6 months of data. These data sheets contain information on the domestic industry structure, Government programs, tariffs, and 5-year salient statistics for over 90 individual minerals and materials. Most data are rounded to no more than 3 significant figures.

Mineral Commodity Summaries↗