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Quality assurance and quality control of geochemical data—A primer for the research scientist

Geochemistry is a constantly expanding science. More and more, scientists are employing geochemical tools to help answer questions about the Earth and earth system processes. Scientists may assume that the responsibility of examining and assessing the quality of the geochemical data they generate is not theirs but rather that of the analytical laboratories to which their samples have been submitted. This assumption may be partially based on knowledge about internal and external quality assurance and quality control (QA/QC) programs in which analytical laboratories typically participate. Or there may be a perceived lack of time or resources to adequately examine data quality. Regardless of the reason, the lack of QA/QC protocols can lead to the generation and publication of erroneous data. Because the interpretations drawn from the data are primary products to U.S. Geological Survey (USGS) stakeholders, the consequences of publishing erroneous results can be significant. The principal investigator of a scientific study ultimately is responsible for the quality and interpretation of the project's findings, and thus must also play a role in the understanding, implementation, and presentation of QA/QC information about the data. Although occasionally ignored, QA/QC protocols apply not only to procedures in the laboratory but also in the initial planning of a research study and throughout the life of the project. Many of the tenets of developing a sound QA/QC program or protocols also parallel the core concepts of developing a good study: What is the main objective of the study? Will the methods selected provide data of enough resolution to answer the hypothesis? How should samples be collected? Are there known or unknown artifacts or contamination sources in the sampling and analysis methods? Assessing data quality requires communication between the scientists responsible for designing the study and those collecting samples, analyzing samples, treating data, and interpreting results. This primer has been developed to provide basic information and guidance about developing QA/QC protocols for geochemical studies. It is not intended to be a comprehensive guide but rather an introduction to key concepts tied to a list of relevant references for further reading. The guidelines are presented in stepwise order beginning with presampling considerations and continuing through final data interpretation. The goal of this primer is to outline basic QA/QC practices that scientists can use before, during, and after chemical analysis to ensure the validity of the data they collect with the goal of providing defendable results and conclusions.

Open-File Report↗

National Land Imaging Requirements (NLIR) Pilot Project summary report: Summary of moderate resolution imaging user requirements

Under the National Land Imaging Requirements (NLIR) Project, the U.S. Geological Survey (USGS) is developing a functional capability to obtain, characterize, manage, maintain and prioritize all Earth observing (EO) land remote sensing user requirements. The goal is a better understanding of community needs that can be supported with land remote sensing resources, and a means to match needs with appropriate solutions in an effective and efficient way. The NLIR Project is composed of two components. The first component is focused on the development of the Earth Observation Requirements Evaluation System (EORES) to capture, store and analyze user requirements, whereas, the second component is the mechanism and processes to elicit and document the user requirements that will populate the EORES. To develop the second component, the requirements elicitation methodology was exercised and refined through a pilot project conducted from June to September 2013. The pilot project focused specifically on applications and user requirements for moderate resolution imagery (5–120 meter resolution) as the test case for requirements development. The purpose of this summary report is to provide a high-level overview of the requirements elicitation process that was exercised through the pilot project and an early analysis of the moderate resolution imaging user requirements acquired to date to support ongoing USGS sustainable land imaging study needs. The pilot project engaged a limited set of Federal Government users from the operational and research communities and therefore the information captured represents only a subset of all land imaging user requirements. However, based on a comparison of results, trends, and analysis, the pilot captured a strong baseline of typical applications areas and user needs for moderate resolution imagery. Because these results are preliminary and represent only a sample of users and application areas, the information from this report should only be used to indicate general user needs for the applications covered. Users of the information are cautioned that use of specific numeric results may be inappropriate without additional research. Any information used or cited from this report should specifically be cited as preliminary findings.

Open-File Report↗

Land processes distributed active archive center product lifecycle plan

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the National Aeronautics and Space Administration (NASA) Earth Science Data System Program worked together to establish, develop, and operate the Land Processes (LP) Distributed Active Archive Center (DAAC) to provide stewardship for NASA’s land processes science data. These data are critical science assets that serve the land processes science community with potential value beyond any immediate research use, and therefore need to be accounted for and properly managed throughout their lifecycle. A fundamental LP DAAC objective is to enable permanent preservation of these data and information products. The LP DAAC accomplishes this by bridging data producers and permanent archival resources while providing intermediate archive services for data and information products.

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Water-chemistry data collected in and near Kaloko-Honokohau National Historical Park, Hawaii, 2012–2014

Kaloko-Honokōhau National Historical Park (KAHO) on western Hawaiʻi was established in 1978 to preserve, interpret, and perpetuate traditional Native Hawaiian culture and activities, including the preservation of a variety of culturally and ecologically significant water resources that are vital to this mission. KAHO water bodies provide habitat for 1 threatened, 11 endangered, and 3 candidate threatened or endangered species. These habitats are sustained by, and in the case of ʻAimakapā Fishpond and the anchialine pools, entirely dependent on, groundwater from the Keauhou aquifer system. Development of inland impounded groundwater in the Keauhou aquifer system may affect the coastal freshwater-lens system on which KAHO depends, if the inland impounded-groundwater and coastal freshwater-lens systems are hydrologically connected. This report documents water-chemistry results from a U.S. Geological Survey study that collected and analyzed water samples from 2012 to 2014 from 25 sites in and near KAHO to investigate potential geochemical indicators in water that might indicate the presence or absence of a hydrologic connection between the inland impounded-groundwater and coastal freshwater-lens systems in the area. Samples were collected under high-tide and low-tide conditions for KAHO sites, and in dry-season and wet-season conditions for all sites. Samples were collected from two ocean sites, two fishponds, three anchialine pools, and three monitoring wells within KAHO. Two additional nearshore wells were sampled on property adjacent to and north of KAHO. Additional samples from the freshwater-lens system were collected from six inland wells located upslope from KAHO, including three production wells. Seven production wells in the inland impounded-groundwater system also were sampled. Water samples were analyzed for major ions, selected trace elements, rare-earth elements, strontium-isotope ratio, and stable isotopes of water. Precipitation samples from five sites were collected roughly along a transect upslope from KAHO. All precipitation samples were analyzed for stable isotopes of water and some precipitation samples were analyzed for rare-earth and selected trace elements.

Hawai'i↗

Validation of eDNA markers for New Zealand mudsnail surveillance and initial eDNA monitoring at Mississippi River Basin sites

The performance of newly developed New Zealand mudsnail ( Potamopyrgus antipodarum ; NZMS) genetic markers for environmental (eDNA) analysis of water were compared across two laboratories. The genetic markers were tested in four quantitative polymerase chain reaction assays targeting two regions of the NZMS mitochondrial genome, specifically the cytochrome c oxidase subunit 1 (coi) and cytochrome b (cytb) genes. In a blind study, analysts tested each sample eight times with each assay. There were 10 expected-negative samples from the Black River in La Crosse, Wisconsin, 10 expected-positive samples from the Black Earth Creek in Black Earth, Wisconsin, and 10 known-positive samples from the Black River spiked with NZMS DNA. Previously extracted samples, kept at the Upper Midwest Environmental Sciences Center, were pooled by sample location and then equal quantities were distributed between the Upper Midwest Environmental Sciences Center and the Molecular Conservation Genetics Laboratory at the University of Wisconsin-Stevens Point for analysis. The assays tested were (1) the assay targeting cytb with a minor groove binder probe described by Goldberg and others (2013), (2) the cytb assay with a modified double-quenched probe, (3) an assay targeting coi with a double-quenched probe, and (4) a duplex reaction combining the modified cytb assay and the coi assay. Samples were considered positive for the presence of NZMS DNA when quantitative polymerase chain reaction amplification and probe signal was higher than the normalized threshold value above baseline fluorescence. For the duplex assay, samples were considered positive only when both probe signals were higher than the normalized threshold value above baseline fluorescence. Positive results were then confirmed by sequencing the products. All four assays detected the DNA of NZMS in all expected-positive and known-positive samples in both labs. The modified cytb assay, the coi assay, and the duplex assay all failed to detect the DNA of NZMS in all expected-negative samples in both labs. The cytb assay, as described by Goldberg and others (2013), failed to detect the DNA of NZMS in all expected-negative samples for the Molecular Conservation Genetics Laboratory, but some reactions resulted in positive detection in late cycles for 9 of the 10 expected-negative samples at the Upper Midwest Environmental Sciences Center. Amplicons for expected-negative samples with positive reactions were sent for sequencing, and none were confirmed as NZMS. Six amplicons failed to give readable sequences, and three gave sequences without similarity to any known sequence in GenBank. Amplicons from each assay for one representative positive sample were sequenced and identified as NZMS with greater than 99 percent identity. The duplex assay was chosen as the most efficient assay and was used at the Upper Midwest Environmental Sciences Center to analyze triplicate samples from 29 streams in Wisconsin, 8 streams in Illinois, and 8 streams in Iowa. In order to verify results, additional triplicate samples were collected from two of the streams in Iowa and two of the streams in Wisconsin for analysis at the Molecular Conservation Genetics Laboratory. All samples at all sites were negative for NZMS DNA.

Illinois, Iowa, Wisconsin↗

Gravity and magnetic studies of the eastern Mojave Desert, California and Nevada

Introduction From May 2011 to August 2014, the U.S. Geological Survey (USGS) collected gravity data at more than 2,300 stations and physical property measurements on more than 640 rock samples from outcrops in the eastern Mojave Desert, California and Nevada. Gravity, magnetic, and physical-property data are used to study and locate regional crustal structures as an aid to understanding the geologic framework related to mineral resources of the eastern Mojave Desert. The eastern Mojave Desert is host to a world-class rare earth element carbonatite deposit located at Mountain Pass, California. Carbonatites are typically defined as magmatic rocks with high modal abundances of primary carbonate minerals >50 weight percent and elevated abundances of rare earth elements (REEs) (Nelson and others, 1988; Woolley and Kempe, 1989). The “Sulphide Queen” carbonatite ore deposit is a composite, tabular body made up of sills and dikes of REE-bearing sovites and beforsites that occurs just south of the Clark Mountain Range along a north-northwest trending fault-bounded block that extends along the northeast edge of the Mescal Range and northwestern extent of Ivanpah Mountains. This early to middle Proterozoic block is composed of a 1.7 Ga metamorphic complex of gneiss and schist that underwent widespread metamorphism and associated plutonism during the Ivanpah orogeny (Miller and others, 2007). Subsequently, these rocks were intruded by a series of granitoids, which included the 1.4 Ga (DeWitt and others, 1987) ultrapotassic alkaline suite of intrusions that are spatially and temporally associated with hundreds of dikes, outcrops, and a carbonatite ore body. The relative age sequence of this intrusive suite of alkaline rocks from oldest to youngest includes shonkinite, mesosyenite, syenite, quartz syenite, potassic granite, carbonatite, and late shonkinite dikes (Olson and others, 1954; Wooden and Miller, 1990; Haxel, 2005; Miller and others, 2007).

California, Nevada↗

Grand challenges for integrated USGS science — A workshop report

Executive Summary The U.S. Geological Survey (USGS) has a long history of advancing the traditional Earth science disciplines and identifying opportunities to integrate USGS science across disciplines to address complex societal problems. The USGS science strategy for 2007–2017 laid out key challenges in disciplinary and interdisciplinary arenas, culminating in a call for increased focus on a number of crosscutting science directions. Ten years on, to further the goal of integrated science and at the request of the Executive Leadership Team (ELT), a workshop with three dozen invited scientists spanning different disciplines and career stages in the Bureau convened on February 7–10, 2017, at the USGS John Wesley Powell Center for Analysis and Synthesis in Fort Collins, Colorado. The workshop focused on identifying “grand challenges” for integrated USGS science. Individual participants identified nearly 70 potential grand challenges before the workshop and through workshop discussions. After discussion, four overarching grand challenges emerged: Natural resource security, Societal risk from existing and emerging threats, Smart infrastructure development, and Anticipatory science for changing landscapes. Participants also identified a “comprehensive science challenge” that highlights the development of integrative science, data, models, and tools—all interacting in a modular framework—that can be used to address these and other future grand challenges: Earth Monitoring, Analyses, and Projections (EarthMAP) EarthMAP is our long-term vision for an integrated scientific framework that spans traditional scientific boundaries and disciplines, and integrates the full portfolio of USGS science: research, monitoring, assessment, analysis, and information delivery. The Department of Interior, and the Nation in general, have a vast array of information needs. The USGS meets these needs by having a broadly trained and agile scientific workforce. Encouraging and supporting cross-discipline engagement would position the USGS to tackle complex and multifaceted scientific and societal challenges in the 21st Century.

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U.S. Geological Survey Community for Data Integration 2017 Workshop Proceedings

Executive Summary The U.S. Geological Survey (USGS) Community for Data Integration (CDI) Workshop was held May 16–19, 2017 at the Denver Federal Center. There were 183 in-person attendees and 35 virtual attendees over four days. The theme of the workshop was “Enabling Integrated Science,” with the purpose of bringing together the community to discuss current topics, shared challenges, and steps forward to advance integrated science at the USGS. The CDI welcomed several keynote speakers, including Bill Werkheiser, USGS Acting Director; Kevin T. Gallagher, USGS Associate Director of the Core Science Systems Mission Area; Bruce Caron, Earth Science Information Partners Community Architect; and Tim Quinn, Chief of the USGS Office of Enterprise Information. Their presentations focused on the importance of collaborative, cross-disciplinary, and open science and the role of the CDI in identifying and supporting new opportunities in these areas for the USGS and its partners. In addition to the stated theme, the workshop agenda was driven by the needs of the CDI, with topics highlighting current resources and technologies that could help attendees in their daily work. Topical sessions were proposed by CDI members and included subjects such as data citation, information technology architecture, legacy data, real-time data, and many more. Plenary speakers from the community talked about USGS activities in data science, elevation and hydrography data integration, advanced scientific computing solutions, cloud computing, data-management training, and data-sharing agreements. Two panels addressed the role of the CDI in enabling integrated science and examples of CDI-supported projects in action. Breakout discussions focused on the workshop theme of “Enabling Integrated Science” and covered five topics: Data and Data Integration, Modeling, Computing Capacity, Science Data Integration, and User Needs and Experience. Sessions on each topic identified actions that could bring the USGS and the broader Earth science community closer to the goal of making integrated science commonplace. The breakouts produced recommendations with the broad themes of improving communication and connections across the USGS, reducing duplication and increasing knowledge transfer, increasing training and testbed opportunities to learn and experiment, and creating community-supported standards to enable better integration and interoperability. The DataBlast poster and live demonstration session showcased 36 projects from around the CDI and included recent CDI-funded projects as well as other USGS and partner initiatives that were related to data and software integration and discovery. Importantly, the CDI workshop provided a forum for scientists, technologists, data and resource managers, program managers, and others to convene face to face to discuss common methods, interests, challenges, and solutions related to scientific data and technologies. As a result of this rare convergence, new connections were made across disciplines, backgrounds, and geographical locations, seeding future activities and collaborations. Sharing of ideas from all attendees was encouraged through the use of a mobile application to collect real-time questions and feedback from the audience The primary outcomes of the workshop are the recommendations from the breakout sessions titled “Roadmap Discussions on Enabling Integrated Science” and from the topical sessions detailed in these proceedings. These sessions, as well as the plenary discussions, identified new areas of collaboration and learning that the CDI will facilitate, such as data science, software development, scientific modeling practices, and user needs and experience. The CDI will build on the results of the workshop to guide its future topics, events, and funding opportunities to support an integrated science capacity for the USGS.

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Calibration of the U.S. Geological Survey National Crustal Model

The U.S. Geological Survey National Crustal Model (NCM) is being developed to include spatially varying estimates of site response in seismic hazard assessments. Primary outputs of the NCM are continuous velocity and density profiles from the Earth’s surface to the mantle transition zone at 410-kilometer (km) depth for each location on a 1-km grid across the conterminous United States. Datasets used to produce the NCM may have a resolution of better than 1 km near the Earth’s surface in some regions, but, with increasing depth, NCM resolution decreases to tens to hundreds of kilometers in the mantle. Basic subsurface information is provided by the NCM geologic framework, thermal model, and petrologic and mineral physics database. In this report, the velocities and densities that can be extracted from the NCM are calibrated through the development of a porosity model based on Biot-Gassmann theory and more than 2,000 compressional- and (or) shear-wave velocity profiles less than 10 km deep from across the conterminous United States and southwestern Canada. Sediment and rock porosities are derived from shear-wave velocity and are found to depend on effective pressure, rock type, and age (for sedimentary and extrusive volcanic deposits). Porosity-effective pressure functions are then estimated for each rock type (and age for sedimentary and extrusive volcanic deposits). Unconsolidated sediments are found to have higher porosities than consolidated units, which have higher porosities than unweathered igneous units; young sedimentary units (for example, Quaternary age units) tend to have higher porosities than older sedimentary units (for example, pre-Cenozoic age units); porosity decreases with increasing effective pressure; and porosities can decrease quickly through the weathered layer of intrusive rocks. Comparing two Los Angeles area velocity models and the U.S. Geological Survey Bay Area velocity model with the NCM, the NCM does a better job on average of reproducing observed shear-wave velocities below 1 km per second because it has less bias and uncertainty. Approaching and above 1 km per second, the NCM tends to underpredict observed shear-wave velocity. Whereas several factors could contribute to this, the primary factor is probably bias in the NCM geologic framework. For example, the NCM will predict lower velocities in places where the depth to bedrock and basement appear shallower in the measured velocity profiles than specified in the NCM geologic framework. With regard to observed compressional-wave velocity and density, the NCM has significantly less bias than California models for the former, especially below 2 km per second, and all models tend to overpredict density for densities less than about 2,200 kilograms per cubic meter.

Open-File Report↗

System characterization report on Planet’s Dove Classic

Executive Summary This report addresses system characterization of Planet’s Dove Classic satellites 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. Since 2013, Planet has launched more than 360 Dove 3U CubeSats, where U stands for 10-centimeter (cm) x 10-cm x 10-cm stowed dimensions, each weighing about 5 kilograms. Since 2015, all Dove satellites have had four-band imagers with about a 4-meter (m) pixel ground sample distance. Since 2016, all Doves have been launched into Sun-synchronous orbits varying from 474 to 524 kilometers, with inclinations between 97 and 98 degrees. The Dove series satellites do not have orbit maintenance capabilities; thus, their orbits decay slowly over time, contributing to shorter lifetimes of about 3 years. More information on Planet satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.planet.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 Dove Classic has an interior geometric performance in the range of −0.218 (−0.073 pixel) to −0.037 m (−0.012 pixel) in easting and −0.167 (−0.056 pixel) to −0.111 m (−0.037 pixel) in northing in band-to-band registration, an exterior geometric error of −6.841 (−2.280 pixels) in easting and −6.235 m (−2.078 pixels) in northing offset in comparison to Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.057 to −0.010 in offset and 0.963 to 1.298 in slope, and a spatial performance in the range of 2.77 to 3.35 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.003 to 0.010.

Open-File Report↗

System characterization report on Planet’s Dove-R

Executive Summary This report addresses system characterization of Planet’s Dove-R 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. Since 2013, Planet has launched more than 360 Dove 3U CubeSats, where U stands for 10-centimeter (cm) x 10-cm x 10-cm stowed dimensions, each weighing about 5 kilograms. Since 2015, all Dove satellites have had four-band imagers with about a 4-meter (m) pixel ground sample distance. Since 2016, all Doves have been launched into Sun-synchronous orbits varying from 474 to 524 kilometers, with inclinations between 97 and 98 degrees. The Dove series satellites do not have orbit maintenance capabilities; thus, their orbits decay slowly over time, contributing to shorter lifetimes of about 3 years. More information on Planet satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.planet.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 Dove-R has an interior geometric performance in the range of −0.306 (−0.102 pixel) to 0.286 m (0.095 pixel) in easting and 0.090 (0.030 pixel) to 1.084 m (0.361 pixel) in northing in band-to-band registration, an exterior geometric performance of −5.10 m (−0.51 pixel) in easting and 3.30 m (0.33 pixel) in northing offset in comparison to Sentinel-2, a radiometric performance in the range of −0.023 to −0.008 in offset and 0.948 to 1.077 in slope, and a spatial performance in the range of 2.96 to 3.15 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.001 to 0.003.

Open-File Report↗

System characterization report on Planet’s SuperDove

Executive Summary This report addresses system characterization of Planet’s SuperDove 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. Since 2013, Planet has launched more than 360 Dove 3U CubeSats, where U stands for 10-centimeter (cm) x 10-cm x 10-cm stowed dimensions, each weighing about 5.8 kilograms. Since 2015, all Dove satellites have had four-band imagers with about a 3-meter (m) pixel ground sample distance. Since 2016, all Doves have been launched into Sun-synchronous orbits varying from 474 to 524 kilometers, with inclinations between 97 and 98 degrees. The Dove series satellites do not have orbit maintenance capabilities; thus, their orbits decay slowly over time, contributing to shorter lifetimes of about 3 years. More information on Planet satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.planet.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 SuperDove has a band-to-band geometric performance in the range of −1.701 m (−0.567 pixel) to 1.173 m (0.391 pixel) in easting and −4.950 m (−1.650 pixels) to 6.051 m (2.017 pixels) in northing, an image-to-image geometric performance of −1.17 m (−0.39 pixel) to 23.45 m (7.82 pixels) in easting and −10.61 m (−3.54 pixels) to −4.43 m (−1.48 pixels) in northing offset in comparison to Sentinel-2, a radiometric performance in the range of −0.043 to 0.020 in offset and 0.812 to 1.246 in slope, and a spatial performance in the range of 3.59 to 3.70 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.005 to 0.008.

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System characterization report on Resourcesat-2 Advanced Wide Field Sensor

Executive Summary This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2 Advanced Wide Field Sensor (AWiFS) 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. 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 AWiFS, 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 “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 AWiFS has an interior geometric performance in the range of −16.080 (−0.268 pixel) to 35.520 meters (m; 0.592 pixel) in easting and −25.680 (−0.428 pixel) to 23.400 m (0.390 pixel) in northing in band-to-band registration, an exterior geometric error of −64.262 (−1.071 pixels) to −19.059 m (−0.318 pixel) in easting and −29.028 (−0.484 pixel) to 41.249 m (0.687 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of 2.29–2.36 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.030–0.035.

Open-File Report↗

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↗

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↗

System characterization report on the Satellogic NewSat multispectral sensor

Executive Summary This report addresses system characterization of Satellogic’s NewSat satellite (also known as ÑuSat) 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. Since 2016, Satellogic has launched 17 NewSat satellites. All NewSat satellites have four-band imagers with a 1-meter (m) ground sample distance, and values in pixels are identical to values in meters. All NewSats have been launched into Sun-synchronous orbits of about 475 kilometers, with inclinations of about 97.5 degrees. The satellites have expected lifetimes of about 3 years. More information on the Satellogic satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://satellogic.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 the NewSat satellites have an interior geometric performance in the range of −0.119 (−0.119 pixel) to 0.020 m (0.020 pixel) in easting and −0.148 (−0.148 pixel) to 0.014 m (0.014 pixel) in northing in band-to-band registration, an exterior geometric performance of −9.04 (−9.04 pixels) to −5.84 m (−5.84 pixels) in easting and 1.25 (1.25 pixels) to 3.11 m (3.11 pixels) in northing offset in comparison to Sentinel-2, an exterior geometric performance using ground control points of a 6.5-m circular error (95 percent), a radiometric performance in the range of 0.034 to 0.081 in offset and 0.652 to 0.808 in slope, and a spatial performance in the range of 1.61 to 1.76 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.081 to 0.138.

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System characterization report on the Gaofen-6

Executive Summary Gaofen-6 represents a series of Chinese high-resolution Earth observation satellites. More than 12 satellites have been launched in the Gaofen series, beginning with Gaofen-1 in 2013. Satellites within the series have varying infrared, radar, and optical imaging capabilities. The primary goal for the satellites in this series is to provide near real-time observations for climate change monitoring, geographical mapping, precision agriculture support, environmental and resource surveying, and disaster prevention. More information on Chinese satellites and sensors is available in the “2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite 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 of Gaofen-6. Results of these analyses indicate that Gaofen-6 has an interior geometric performance root mean square error ranging from 2.84 meters (m; 0.18 pixel) to 7.42 m (0.46 pixel) in easting and from 2.84 m (0.18 pixel) to 11.57 m (0.72 pixel) in northing in band-to-band registration, an exterior geometric performance root mean square error ranging from 154.50 m (8.80 pixels) in easting to 14.65 m (0.80 pixel) in northing in comparison to a corresponding Sentinel-2 scene, a radiometric performance ranging from 0.018 to 0.055 (in offset) and from 0.620 to 0.858 (in slope), and a spatial performance ranging from 2.10 to 2.30 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency ranging from 0.040 to 0.055.

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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.

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