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USGS2008

Integrating remotely acquired and field data to assess effects of setback levees on riparian and aquatic habitat in glacial-melt water rivers

Setback levees, in which levees are reconstructed at a greater distance from a river channel, are a promising restoration technique particularly for alluvial rivers with broad floodplains where river-floodplain connectivity is essential to ecological processes. Documenting the ecological outcomes of restoration activities is essential for assessing the comparative benefits of different restoration approaches and for justifying new restoration projects. Remote sensing of aquatic habitats offers one approach for comprehensive, objective documentation of river and floodplain habitats, but is difficult in glacial rivers because of high suspended-sediment concentrations, braiding and a lack of large, well-differentiated channel forms such as riffles and pools. Remote imagery and field surveys were used to assess the effects of recent and planned setback levees along the Puyallup River and, more generally, the application of multispectral imagery for classifying aquatic and riparian habitats in glacial-melt water rivers. Airborne images were acquired with a horizontal ground resolution of 0.5 m in three spectral bands (0.545-0.555, 0.665-0.675 and 0.790-0.810 ??m) spanning from green to near infrared (NIR) wavelengths. Field surveys identified river and floodplain habitat features and provided the basis for a comparative hydraulic analysis. Broad categories of aquatic habitat (smooth and rough water surface), exposed sediment (sand and boulder) and vegetated surfaces (herbaceous and deciduous shrub/forest) were classified accurately using the airborne images. Other categories [e.g. conifers, boulder, large woody debtis (LWD)] and subdivisions of broad categories (e.g. riffles and runs) were not successfully classified either because these features did not form large patches that could be identified on the imagery or their spectral reflectances were not distinct from those of other habitat types. Airborne imagery was critical for assessing fine-scale aquatic habitat heterogeneity including shallow, low-velocity regions that were not feasible or practical to map in the field in many cases due to their widespread distribution, small size and poorly defined boundaries with other habitat types. At the reach-scale, the setback levee affected the amount and distribution of riparian and aquatic habitats: (1) the area of all habitats was greater where levees had been set back and with relatively more vegetated floodplain habitat and relatively less exposed sediment and aquatic habitat, (2) where levees confine the river, less low-velocity aquatic habitat is present over a range of flows with a higher degree of bed instability during high flows. As river restoration proceeds in the Pacific Northwest and elsewhere, remotely acquired imagery will be important for documenting its effects on the amount and distribution of aquatic and floodplain habitats, complimenting field data as a quantitative basis for evaluating project efficacy.

River Research and Applications↗

USGS2012

Mapping temperature and radiant geothermal heat flux anomalies in the Yellowstone geothermal system using ASTER thermal infrared data

The purpose of this work was to use satellite-based thermal infrared (TIR) remote sensing data to measure, map, and monitor geothermal activity within the Yellowstone geothermal area to help meet the missions of both the U.S. Geological Survey Yellowstone Volcano Observatory and the Yellowstone National Park Geology Program. Specifically, the goals were to: 1) address the challenges of remotely characterizing the spatially and temporally dynamic thermal features in Yellowstone by using nighttime TIR data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and 2) estimate the temperature, geothermal radiant emittance, and radiant geothermal heat flux (GHF) for Yellowstone’s thermal areas (both Park wide and for individual thermal areas). ASTER TIR data (90-m pixels) acquired at night during January and February, 2010, were used to estimate surface temperature, radiant emittance, and radiant GHF from all of Yellowstone’s thermal features, produce thermal anomaly maps, and update field-based maps of thermal areas. A background subtraction technique was used to isolate the geothermal component of TIR radiance from thermal radiance due to insolation. A lower limit for the Yellowstone’s total radiant GHF was established at ~2.0 GW, which is ~30-45% of the heat flux estimated through geochemical (Cl-flux) methods. Additionally, about 5 km 2 was added to the geodatabase of mapped thermal areas. This work provides a framework for future satellite-based thermal monitoring at Yellowstone as well as exploration of other volcanic / geothermal systems on a global scale.

Wyoming↗

USGS2023

The future of ecosystem assessments is automation, collaboration, and artificial intelligence

Robust and routine ecosystem assessments will be fundamental to track progress towards achieving this decade’s global environmental and sustainability goals. Here we examine four needs that address common failure points of ecosystem assessments. These are (1) developing rapid, reproducible, and repeatable ecological data workflows, (2) harmonizing in situ and remotely sensed data, (3) integrating socioeconomic and biophysical data, and (4) increasing access to the digital resources and cyberinfrastructure needed to perform assessments. These four needs have profound potential to help us achieve our environmental objectives through cross-sector collaborations that leverage advancements in digital resources, remote data streams, and data science.

Environmental Research Letters↗

USGS2006

Mountain hydrology of the western United States

Climate change and climate variability, population growth, and land use change drive the need for new hydrologic knowledge and understanding. In the mountainous West and other similar areas worldwide, three pressing hydrologic needs stand out: first, to better understand the processes controlling the partitioning of energy and water fluxes within and out from these systems; second, to better understand feedbacks between hydrological fluxes and biogeochemical and ecological processes; and, third, to enhance our physical and empirical understanding with integrated measurement strategies and information systems. We envision an integrative approach to monitoring, modeling, and sensing the mountain environment that will improve understanding and prediction of hydrologic fluxes and processes. Here extensive monitoring of energy fluxes and hydrologic states are needed to supplement existing measurements, which are largely limited to streamflow and snow water equivalent. Ground‐based observing systems must be explicitly designed for integration with remotely sensed data and for scaling up to basins and whole ranges.

Water Resources Research↗

USGS2020

Thicknesses of lava flows in satellite images: Comparison of layered mare units with terrestrial analogs

Recent advances in satellite imaging technology have greatly improved our observations of planetary surfaces. The Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) records images with resolutions on average of 0.5 m per pixel, resolving meter scale features on the surface of the Moon. NAC images have revealed layered deposits, interpreted to be sequences of mare basalt flows, in the walls of impact craters on the lunar nearside. However, caution must be exercised in the interpretation of surface processes from morphologies of features that are close to the limits of detectability. Our goal is to quantify where that limit is for lava flow stratigraphy. Here we report on a terrestrial analog study conduced to better constrain limitations in the measurements of thicknesses of lava flows observed in high-resolution satellite-collected images. Using WorldView-2 satellite images, we mapped layered basalt flows at three sites in the Wai'anae and Ko'olau Ranges of O'ahu, Hawai'i. Fieldwork conducted at these sites allowed for assessment of the accuracy of image interpretations. We found that flow thickness estimates made using WorldView-2 images overestimated thicknesses of individual lava flows measured in the field at all eight locations visited by a factor of 1.2 to 3.5. A primary reason for this overestimation by remote sensing analysis is that many outcropping “layers” within a transect contain more than one individual flow, a distinction that is not visible in satellite images. However, the mean thickness of the layers seen in the orbital data was 0.8 to 1.7 times the outcrop thickness measured in the field, suggesting that the remote measurements should be considered estimates of the outcrop thickness rather than the thickness of individual lava flows. Measurements of layered lunar mare lava units in LRO NAC images provided layer thicknesses that ranged from <1–6 times greater than those derived from images of the O'ahu study sites. It is reasonable to expect that many lunar outcrops similarly contain more than one individual flow and display similar outcropping patterns. This suggests that many current estimates of layer thicknesses derived by comparable methods actually correspond to outcrop thicknesses. Current interpretations of lava flow thicknesses derived from planetary images should be considered maximums for individual flow thicknesses with uncertainties that may be as high as a factor of 3 or more.

Hawaii↗

USGS2014

InSAR imaging of aleutian volcanoes: Monitoring a volcanic arc from space

Interferometric synthetic aperture radar (InSAR) is a relatively new remote sensing tool that is capable of measuring ground-surface deformation with centimeter-to-subcentimeter precision at a spatial resolution of tens of meters over an area of hundreds to thousands of square kilometers. With its global coverage and all-weather imaging capability, InSAR has become an increasingly important technique for studying volcanoes in remote regions such as the Aleutian Islands. The spatial distribution of surface deformation data derived from InSAR images enables the construction of detailed mechanical models to enhance the study of magmatic processes.

Book↗

USGS1968

Infrared survey of the Pisgah Crater area, San Bernardino County, California - a geologic interpretation

The infrared survey of the Pisgah Crater Area, San Bernardino County, California was primarily undertaken to establish parameters by which rock types, structures, and textures peculiar to this locale could be recognized or differentiated. A secondary purpose was to provide an adequate evaluation and calibration of airborne and ground-based instruments used in the survey. Pisgah Crater and its vicinity was chosen as one of the fundamental test sites for the NASA remote sensing program because of its relatively fresh basaltic flows and pyroclastics. Its typical exposure of basalt also made it a possible lunar analogue. A fundamental test site for the purpose of the program is defined as a readily accessible area for which the topography, geology, hydrology, soils, vegetation and other features are relatively well known. All remote sensor instrument teams, i.e. infrared, radar, microwave, and photography, were obligated to use the fundamental test sites for instrument evaluation and to establish terrain identification procedures. Pisgah Crater, nearby Sunshine Cone, and their associated lava flows are in the southern Mojave Desert about 40 miles east-southeast of Barstow, California. (See fig. 1.) U. S. Highway 66 skirts .the northern part of the area and provides access via asphalt-paved and dirt roads to the Crater and to the perimeters of the flows. Pisgah Crater, which is a pumiceous cone, is owned and occasionally quarried by the Atchison, Topeka and Santa Fe Railroad. The remaining part of the area to the south is within the boundary of the Marine Corps Base, Twentynine Palms, California and is currently being used as a gunnery, and bombing range. The proximate area to east, west, and north of Pisgah Crater is public domain. Originally, an area totaling 10 square miles was outlined for detailed study. (See plate 1.) This included an 8 mile long strip extending south- east from and including Pisgah Crater to Lavic Dry Lake, and a 2 mile strip aligned to include a portion of the Sunshine lava flow and the dry lake. Additional aerial infrared imagery of the Sunshine and Pisgah flows along the Pisgah fault proved so interesting and informative that this area is included in the discussion. Infrared surveys were flown February ii through 13, 1965 and August 5 and 9, 1966. The initial survey was flown by the NASA personnel aboard the NASA 926 Convair 240 aircraft. Because of technical problems with the infrared scanners (4.5-5.5 and 8-14 micron bands) and with certain ground instruments, most of the imagery and ground temperature data obtained during the initial survey period was of little value. However, excellent infrared imagery in the 8-14 micron (?) region of the spectrum was acquired by the Geological Survey during the August 1966 survey. The scanner was mounted in a Beech D-18 aircraft provided by the Survey's Water Resources Division. Likewise, more reliable ground data was obtained at this time owing to improved instrumentation and technique. Ground data were taken by Geological Survey personnel including W. A. Fischer, J. D. Friedman, W. R. Hemphill, D. L. Daniels, G. R. Boynton, Po W. Philbin and the author. C. R. Fross operated the infrared scanner during the August, 1966 survey and R. M. Turner was-responsible for photo processing of the infrared imagery. Their assistance is gratefully acknowledged.

Open-File Report↗

USGS2012

Detecting hidden volcanic explosions from Mt. Cleveland Volcano, Alaska with infrasound and ground-couples airwaves

In Alaska, where many active volcanoes exist without ground-based instrumentation, the use of techniques suitable for distant monitoring is pivotal. In this study we report regional-scale seismic and infrasound observations of volcanic activity at Mt. Cleveland between December 2011 and August 2012. During this period, twenty explosions were detected by infrasound sensors as far away as 1827 km from the active vent, and ground-coupled acoustic waves were recorded at seismic stations across the Aleutian Arc. Several events resulting from the explosive disruption of small lava domes within the summit crater were confirmed by analysis of satellite remote sensing data. However, many explosions eluded initial, automated, analyses of satellite data due to poor weather conditions. Infrasound and seismic monitoring provided effective means for detecting these hidden events. We present results from the implementation of automatic infrasound and seismo-acoustic eruption detection algorithms, and review the challenges of real-time volcano monitoring operations in remote regions. We also model acoustic propagation in the Northern Pacific, showing how tropospheric ducting effects allow infrasound to travel long distances across the Aleutian Arc. The successful results of our investigation provide motivation for expanded efforts in infrasound monitoring across the Aleutians and contributes to our knowledge of the number and style of vulcanian eruptions at Mt. Cleveland.

Alaska↗

USGS2026

What is the (real) rate of soil health practice adoption? Making sense of three data sources

Conservation stakeholders looking to quantify the impact of their investments to increase soil health practice adoption over time often face challenges in interpreting practice adoption data due to discrepancies in language and results among data sources. Similarly, efforts to estimate environmental outcomes of practice adoption, such as water quality and greenhouse gas emissions, can vary depending on different practice adoption input data. To help make sense of different adoption data sources, we compared county-level adoption data for winter cover crops (WCC), no-till (NT), and reduced tillage (RT) in three areas of the United States with contrasting climates and production systems: central Illinois (CIL), southern Illinois (SIL), and western New York (WNY). We analyzed data available during 2015 through 2022 from the Operational Tillage Information System (OpTIS, remote sensing), US Census of Agriculture (AgCensus, a farmer survey), and, specifically in Illinois, the Illinois Soil Conservation Transect Survey (Transect, a roadside survey). The magnitude of differences between the datasets depended on the practice and geographic location. For example, OpTIS and AgCensus tillage data were much more similar in Illinois (average difference of less than 4 percentage points) compared to New York (average differences of 20 percentage points). Similarly, there was less variability and smaller differences between OpTIS and AgCensus WCC data in Illinois compared to WNY. AgCensus tended to report lower WCC adoption for Illinois and greater adoption in WNY compared to OpTIS. All data sources agreed that the rate of change in tillage practices is slow (mainly –1% to 1%) and that adoption of WCC is low (assuming linear growth, it could take nearly a century to reach 50% WCC adoption in CIL). Differences among the datasets were attributed to definitional inconsistencies for RT and NT and how WCC data were acquired. For example, the AgCensus asks if a WCC was planted, whereas OpTIS and Transect evaluate the presence of a standing WCC. Data sources also reflect different time periods (calendar years or crop years) and types of cropland assessed (corn [ Zea mays L.], soybean [ Glycine max {L.} Merr.], or all cropland). We propose two recommendations to improve interpretation and consistency: (1) a working group to harmonize definitions and protocols and develop educational materials for data users, and (2) a research effort that integrates different adoption data types and produces publicly available adoption data at HUC-10 and county scales. Such activities could help improve data access and utility for evidence-based conservation decision-making and enhance the accuracy of environmental models that rely on adoption data as input.

Journal of Soil and Water Conservation↗

USGS2020

Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing

Landslides modify the natural landscape and cause fatalities and property damage worldwide. Quantifying landslide dynamics is challenging due to the stochastic nature of the environment. With its large area of ~1 km 2 and perennial motions at ~10–20 mm per day, the Slumgullion landslide in Colorado, USA, represents an ideal natural laboratory to better understand landslide behavior. Here, we use hybrid remote sensing data and methods to recover the four-dimensional surface motions during 2011–2018. We refine the boundaries of an area of ~0.35 km 2 below the crest of the prehistoric landslide. We construct a mechanical framework to quantify the rheology, subsurface channel geometry, mass flow rate, and spatiotemporally dependent pore-water pressure feedback through a joint analysis of displacement and hydrometeorological measurements from ground, air and space. Our study demonstrates the importance of remotely characterizing often inaccessible, dangerous slopes to better understand landslides and other quasi-static mass fluxes in natural and industrial environments, which will ultimately help reduce associated hazards.

Colorado↗

USGS2008

Categorizing natural disaster damage assessment using satellite-based geospatial techniques

Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services) and hazards (e.g., downed power lines, gas lines, etc.), the need for rapid mobilization (particularly for remote locations), and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's C , and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale). Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.

Natural Hazards and Earth System Sciences↗

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

Short-term forecasting and detection of explosions during the 2016–2017 eruption of Bogoslof volcano, Alaska

We describe a multidisciplinary approach to forecast, rapidly detect, and characterize explosive events during the 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc. The eruptive sequence began in December 2016 and included about 70 discrete explosive events. Because the volcano has no local monitoring stations, we used distant stations on the nearest volcanoes, Okmok (54 km) and Makushin (72 km), combined with regional infrasound sensors and lightning detection from the Worldwide Lightning Location Network (WWLLN). Pre-eruptive seismicity was detected for 12 events during the first half of the eruption; for all other events co-eruptive signals allowed for detection only. Monitoring of activity used a combination of scheduled checks combined with automated alarms. Alarms triggered on real-time data included real-time seismic amplitude measurement (RSAM); infrasound from several arrays, the closest being on Okmok; and lightning strokes detected from WWLLN within a 20-km radius of the volcano. During periods of unrest, a multidisciplinary response team of four people fulfilled specific roles to evaluate geophysical and remote-sensing data, run event-specific ash-cloud dispersion models, ensure interagency coordination, and develop and distribute of formalized warning products. Using this approach, for events that produced ash clouds ≥7.5 km above sea level, Alaska Volcano Observatory (AVO) called emergency response partners 15 min, and issued written notices 30 min, after event onset (mean times). Factors that affect timeliness of written warnings include event size and number of data streams available; bigger events and more data both decrease uncertainty and allow for faster warnings. In remote areas where airborne ash is the primary hazard, the approach used at Bogoslof is an effective strategy for hazard mitigation.

Alaska↗

USGS2022

Democratizing macroecology: Integrating unoccupied aerial systems with the National Ecological Observatory Network

Macroecology research seeks to understand ecological phenomena with causes and consequences that accumulate, interact, and emerge across scales spanning several orders of magnitude. Broad-extent, fine-grain information (i.e., high spatial resolution data over large areas) is needed to adequately capture these cross-scale phenomena, but these data have historically been costly to acquire and process. Unoccupied aerial systems (UAS or drones carrying a sensor payload) and the National Ecological Observatory Network (NEON) make the broad-extent, fine-grain observational domain more accessible to researchers by lowering costs and reducing the need for highly specialized equipment. Integration of these tools can further democratize macroecological research, as their strengths and weaknesses are complementary. However, using these tools for macroecology can be challenging because mental models are lacking, thus requiring large up-front investments in time, energy, and creativity to become proficient. This challenge inspired a working group of UAS-using academic ecologists, NEON professionals, imaging scientists, remote sensing specialists, and aeronautical engineers at the 2019 NEON Science Summit in Boulder, Colorado, to synthesize current knowledge on how to use UAS with NEON in a mental model for an intended audience of ecologists new to these tools. Specifically, we provide (1) a collection of core principles for collecting high-quality UAS data for NEON integration and (2) a case study illustrating a sample workflow for processing UAS data into meaningful ecological information and integrating it with NEON data collected on the ground—with the Terrestrial Observation System—and remotely—from the Airborne Observation Platform. With this mental model, we advance the democratization of macroecology by making a key observational domain—the broad-extent, fine-grain domain—more accessible via NEON/UAS integration.

Ecosphere↗

USGS2022

System characterization report on Planet SkySat

This report addresses system characterization of Planet’s SkySat 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. SkySat is a constellation of submeter resolution Earth observation satellites providing analytics services, high-definition video, and imagery. The goal for the constellation is to capture multiple daily repeats of high-resolution imagery over any spot on the Earth. As of September 2020, 21 SkySat satellites have been launched, and the first launch occurred in November 2013. 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 SkySat has an interior geometric performance in the range of a 0.38- (0.47 pixel) to 0.75-meter (m; 0.93 pixel) root mean square error in easting and a 0.27- (0.33 pixel) to 0.55-m (0.68 pixel) root mean square error in northing, in band-to-band registration; an exterior geometric performance in the range of 0.26 (0.32 pixel) to 1.04 m (1.28 pixels) offset in comparison to ground control points; a radiometric performance in the range of 0.033 to 0.797 (linear regression); and a spatial performance in the range of 3.7 to 4.3 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.004 to 0.009.

Open-File Report↗

USGS2022

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.

Open-File Report↗

USGS2021

System characterization report on the Gaofen-1

Executive Summary This report addresses system characterization of Gaofen-1 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 the detail 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. Gaofen 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 satellite 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 within the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and at http://www.cnsageo.com/#/detailIndex?secondIndex=2&id=3&code=8 . 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 Gaofen-1 has an interior geometric performance of −0.48 meter (m) (−0.03 pixel) northing and 0.42 m (0.03 pixel) easting offset for band 1, −0.99 m (−0.06 pixel) northing and −0.38 m (−0.02 pixel) easting offset for band 2, −0.45 m (−0.03) northing and 0.83 m (0.05 pixel) easting offset for band 3, −3.20 m (−0.20 pixel) northing and 1.44 m (0.09 pixel) easting offset for band 4 in band-to-band registration. Similarly, Gaofen-1 has an exterior geometric performance of 7.50 m (0.48 pixel) easting and 109.50 m (7.30 pixels) northing offset in comparison to the Landsat 8 Operational Land Imager; a radiometric performance in the range of −0.014 to 0.149 (absolute reflective difference); and a spatial performance in the range of 1.1 to 2.0 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.040 to 0.250.

Open-File Report↗

USGS2023

System characterization report on the BlackSky Global multispectral sensor

Executive Summary This report addresses system characterization of the BlackSky Global 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. The BlackSky Global satellites are three-band multispectral imagers (red, green, and blue multispectral bands plus a panchromatic band) with a 0.8- to 0.9-meter (m) pixel ground sample distance for the assessed satellites. BlackSky Global satellites 9 and 12–17 were launched in March and December 2021, respectively, into a Sun-synchronous orbit of 430–450 kilometers with an inclination of 42–53 degrees and a swath width of 6 kilometers at nadir. Each Global satellite has an expected lifetime of about 3 years. More information on the BlackSky Global satellites is available in the “Land Remote Sensing Satellites Online Compendium” ( https://calval.cr.usgs.gov/apps/compendium ) and from BlackSky at Real-Time Space-Based Intelligence (blacksky.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) and spatial performances. Results of these analyses indicate that the assessed BlackSky Global satellites have an interior geometric performance in the range of −0.011 m (−0.012 pixel) to 0.007 m (0.008 pixel) in easting and −0.018 m (−0.020 pixel) to 0.012 m (0.013 pixel) in northing in band-to-band registration; an exterior geometric performance using ground control points of 8.0-m circular error (95-percent certainty) for orthorectified products and 10.7- to 17.4-m circular error (95-percent certainty) for nonorthorectified products, depending on the geolocation metadata used; and a spatial performance in the range of 1.70 to 2.43 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.032 to 0.084.

Open-File Report↗