Geology topics

Minsu Kim

Publications and source records attributed to Minsu Kim.

At least 19 recordsLinked to original sources

USGS2026

System characterization report on Tanager

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

Open-File Report↗

USGS2026

Is satellite-derived bathymetry vertical accuracy dependent on satellite mission and processing method?

This research focusses on three satellite-derived bathymetry methods and optical satellite instruments: (1) a stereo photogrammetry bathymetry module (SaTSeaD) developed for the NASA Ames stereo pipeline open-source software (version 3.6.0) using stereo WorldView data; (2) physics-based radiative transfer equations (PBSDB) using Landsat data; and (3) a modified composite band-ratio method for Sentinel-2 (SatBathy) with an initial simplified calibration, followed by a more rigorous linear regression against in situ bathymetry data. All methods were tested in three different areas with different geological and environmental conditions, Cabo Rojo, Puerto Rico; Key West, Florida; and Cocos Lagoon and Achang Flat Reef Preserve, Guam. It is demonstrated that all satellite derived bathymetry (SDB) methods have increased accuracy when the results are aligned with higher-accuracy ICESat-2 ATL24 track bathymetry data using the iterative closest point (ICP). SDB vertical accuracy depends more on location characteristics than the method or optical satellite instrument used. All error metrics considered (mean absolute error, median absolute deviation, and root mean square error) can be less than 5% of the maximum bathymetry depth penetration for at least one method, although not necessarily for the same method for all sites. The SDB error distribution tends to be bimodal irrespective of method, satellite instrument, alignment, site, or maximum bathymetry depth, leading to the potential ineffectiveness of traditional error metrics, such as the root mean square error. However, our analysis demonstrates that performing detrending where possible can achieve an error distribution as close to normality as possible for which error metrics are more diagnostic.

Florida↗

USGS2025

System characterization report on Resourcesat-2A Advanced Wide Field Sensor

Executive Summary This report documents the system characterization of the Indian Space Research Organisation Resourcesat-2A Advanced Wide Field Sensor (AWiFS) and 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. Resourcesat-2 and -2A carry the AWiFS, Linear Imaging Self Scanning-3, and Linear Imaging Self Scanning-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 Indian Space Research Organisation satellites and sensors is available through the Joint Agency Commercial Imagery Evaluation Earth Observing Satellites Online Compendium and from the Indian Space Research Organisation 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 performance of the Resourcesat-2A AWiFS 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 offsets in the range of −1.10 meters (m; −0.020 pixel) to 3.67 m (0.066 pixel) in easting and −5.68 m (−0.101 pixel) to 10.38 m (0.185 pixel) in northing with root mean square error values from 5.60 m (0.100 pixel) to 11.31 m (0.202 pixel) in easting and from 3.00 m (0.054 pixel) to 13.52 m (0.241 pixel) in northing. The exterior geometric performance had mean offsets of −25.29 m in easting and 16.22 m northing with root mean square error values of 26.07 m in easting and 17.60 m in northing compared to the Landsat 8 Operational Land Imager sensor. The radiometric performance had offsets from −0.002 to 0.029 and slopes from 0.733 to 1.012. Spatial performance was in the range of 1.354 to 1.639 pixels for full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.108 to 0.174.

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↗

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 the Environmental Mapping and Analysis Program (EnMAP)

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

Open-File Report↗

USGS2024

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

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

Open-File Report↗

USGS2024

System characterization report on Vision-1

Executive Summary This report addresses system characterization of the Airbus Vision-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. Vision-1 is a high-resolution Earth observation satellite launched in September 2018 as a collaborative effort between Airbus and Surrey Satellite Technology Ltd. It features a Newtonian telescope with a refractive relay, capturing images in panchromatic and multispectral bands. Operating in a Sun-synchronous orbit at an altitude of 583 kilometers, Vision-1 ensures consistent illumination conditions during image acquisition. It has a revisit time of 1 to 8 days depending on latitude and viewing angle, and it features an off-pointing agility of plus or minus 45 degrees, allowing for multiple target captures in a single pass using spot, strip, and mosaic imaging modes. The panchromatic band offers a resolution of 0.87 meter (m), whereas the multispectral bands (blue, green, red, and near infrared) provide a resolution of 3.48 m. These capabilities support a variety of applications including urban planning, agricultural monitoring, land classification, natural resource management, and disaster response. More information on the Vision-1 satellite 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. Results of these analyses indicate that the Vision-1 satellite has an interior geometric performance in the range of 0 to 0.02 m in easting and −0.01 to 0.03 m in northing in band-to-band registration, an exterior geometric performance of 1.7 to 2.2 m in easting and −1.1 to −0.7 m in northing offset with a 90-percent circular error of 3.4 to 3.7 m, a radiometric performance in the range of −0.029 to 0.017 in offset and 0.884 to 0.984 in slope, and a spatial performance in the range of 0.992 to 1.092 pixels for multispectral full width at half maximum and 1.895 pixels for the panchromatic band full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.29 to 0.36 for the multispectral bands and 0.05 for the panchromatic band.

Open-File Report↗

USGS2024

Airborne lidar accuracy analysis for dual photogrammetric and lidar sensor pilot project in Colorado, 2019

This report presents accuracy assessment results of the light detection and ranging (lidar) data collected in Colorado during a pilot project in fall 2019. The purpose of the pilot project was to assess the accuracy of lidar and imagery data collected simultaneously for the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program and the U.S. Geological Survey National Geospatial Program 3D Elevation Program (3DEP). A multiagency group consisting of U.S. Department of the Interior agencies and USDA agencies participated in the effort. Department of the Interior agencies included Bureau of Land Management, National Park Service, and U.S. Geological Survey; USDA agencies included the Farm Services Agency, the Natural Resource Conservation Service, and U.S. Forest Service. This pilot project was designed to help determine if a lidar sensor system has the potential to meet future 3DEP topographic lidar collection requirements, ideally at the same altitudes and leaf-on times that National Agriculture Imagery Program is flown. The airborne sensor system from Leica Geosystems (part of Hexagon) (hereafter referred to as dual sensor system) was used in the pilot project and can collect imagery and three-dimensional point cloud data concurrently. This report examines the characteristics of lidar data from a geometric accuracy perspective. Field surveys were performed to evaluate the three-dimensional absolute and relative accuracy of the airborne lidar data and to determine if the data met 3DEP specifications.

Colorado↗

USGS2024

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.

Open-File Report↗

USGS2024

Physics-based satellite-derived bathymetry (SDB) using Landsat OLI images

The estimation of depth in optically shallow waters using satellite imagery can be efficient and cost-effective. Active sensors measure the distance traveled by an emitted laser pulse propagating through the water with high precision and accuracy if the bottom peak intensity of the waveform is greater than the noise level. However, passive optical imaging of optically shallow water involves measuring the radiance after the sunlight undergoes downward attenuation on the way to the sea floor, and the reflected light is then attenuated while moving back upward to the water surface. The difficulty of satellite-derived bathymetry (SDB) arises from the fact that the measured radiance is a result of a complex association of physical elements, mainly the optical properties of the water, bottom reflectance, and depth. In this research, we attempt to apply physics-based algorithms to solve this complex problem as accurately as possible to overcome the limitation of having only a few known values from a multispectral sensor. Major analysis components are atmospheric correction, the estimation of water optical properties from optically deep water, and the optimization of bottom reflectance as well as the water depth. Specular reflection of the sky radiance from the water surface is modeled in addition to the typical atmospheric correction. The physical modeling of optically dominant components such as dissolved organic matter, phytoplankton, and suspended particulates allows the inversion of water attenuation coefficients from optically deep pixels. The atmospheric correction and water attenuation results are used in the ocean optical reflectance equation to solve for the bottom reflectance and water depth. At each stage of the solution, physics-based models and a physically valid, constrained Levenberg–Marquardt numerical optimization technique are used. The physics-based algorithm is applied to Landsat Operational Land Imager (OLI) imagery over the shallow coastal zone of Guam, Key West, and Puerto Rico. The SDB depths are compared to airborne lidar depths, and the root mean squared error (RMSE) is mostly less than 2 m over water as deep as 30 m. As the initial choice of bottom reflectance is critical, along with the bottom reflectance library, we describe a pure bottom unmixing method based on eigenvector analysis to estimate unknown site-specific bottom reflectance.

Remote Sensing↗

USGS2023

System characterization report on the Pléiades Neo Imager

Executive Summary This report addresses system characterization of the Pléiades Neo 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. Pléiades Neo is a constellation of four identical very-high-resolution optical satellites operated by Airbus Defence and Space. The first two satellites, Pléiades Neo-3 and -4, were launched in April and August 2021, respectively. The next two satellites, launched in December 2022, did not reach orbit because of Vega-C launch vehicle failure. Pléiades Neo provides several technical improvements to previous Pléiades-HR satellites, including the addition of coastal aerosol (deep blue) and red edge spectral bands, with improved ground sample distance and swath. The Pléiades Neo satellites were designed and built by Airbus Defence and Space with the high-resolution, multispectral imager for Earth imaging and use the S950 optical satellite bus. The high-resolution sensor on Pléiades Neo collects Earth data in the visible and near-infrared region with six bands and a panchromatic band. The satellites can operate off nadir to achieve a revisit of less than 1 day. More information on Pléiades Neo satellites and sensors is available in the “Land Remote Sensing Satellites Online Compendium” ( https://calval.cr.usgs.gov/apps/compendium# ) and from the manufacturer ( https://www.intelligence-airbusds.com/imagery/constellation/pleiades-Neo/ ). 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 Pléiades Neo has an interior geometric performance in the range of 0.01 meter (m; 0.008 pixel) to −0.017 m (−0.014 pixel) in band-to-band registration; an exterior geometric performance in the range of −7.015 m (−0.702 pixel) to 3.846 m (0.385 pixel) offset in comparison to Sentinel-2 using ground control points of 2.2 to 7.2 m (95-percent circular error); a radiometric performance in the range of −0.070 (minimum) to −0.053 (maximum) in offset and 1.107 (minimum) to 1.202 (maximum) in slope; and a spatial performance in the range of 1.002 to 1.226 pixels at full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.22 to 0.34 (bands 2–7).

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↗

USGS2023

The 50-year Landsat collection 2 archive

The Landsat global consolidated data archive now exceeds 50 years. In recognition of the need for consistently processed data across the Landsat satellite series, the U.S. Geological Survey (USGS) initiated collection-based processing of the entire archive that was processed as Collection 1 in 2016. In preparation for the data from the now successfully launched Landsat 9, the USGS reprocessed the Landsat archive as Collection 2 in 2020. This paper describes the rationale for, and the contents and advancements provided by Collection 2, and highlights the differences between the Collection 1 and Collection 2 products. Notably, the Collection 2 products have improved geolocation and, for the first time, the USGS provides a global inventory of Level 2 surface reflectance and surface temperature products. Also for the first time, the USGS used a commercial cloud computing architecture to efficiently process the archive and enable direct cloud access of the Landsat products. The paper concludes with discussion of likely improvements expected in Collection 3 in preparation for the Landsat Next mission that is planned for launch in the early 2030s.

Science of Remote Sensing↗

USGS2022

Absolute accuracy assessment of lidar point cloud using amorphous objects

The accuracy assessment of airborne lidar point cloud typically estimates vertical accuracy by computing RMSEz (root mean square error of the z coordinate) from ground check points (GCPs). Due to the low point density of the airborne lidar point cloud, there is often not enough accurate semantic context to find an accurate conjugate point. To advance the accuracy assessment in full three-dimensional (3D) context, geometric features, such as the three-plane intersection point or two-line intersection point, are often used. Although the point density is still low, geometric features are mathematically modeled from many points. Thus, geometric features provide a robust determination of the intersection point, and the point is considered as a GCP. When no regular built objects are available, we describe the process of utilizing features of irregular shape called amorphous natural objects, such as a tree or a rock. When scanned to a high-density point cloud, an amorphous natural object can be used as ground truth reference data to estimate 3D georeferencing errors of the airborne lidar point cloud. The algorithm to estimate 3D accuracy is the optimization that minimizes the sum of the distance between the airborne lidar points to the ground scanned data. The search volume partitioning was the most important procedure to improve the computational efficiency. We also performed an extensive study to address the external uncertainty associated with the amorphous object method. We describe an accuracy assessment using amorphous objects (108 trees) spread over the project area. The accuracy results for ∆ x , ∆ y , and ∆ z obtained using the amorphous object method were 3.1 cm, 3.6 cm, and 1.7 cm RMSE, along with a mean error of 0.1 cm, 0.1 cm, and 4.5 cm, respectively, satisfying the accuracy requirement of U.S. Geological Survey lidar base specification. This approach shows strong promise as an alternative to geometric feature methods when artificial targets are scarce. The relative convenience and advantages of using amorphous targets, along with its good performance shown here, make this amorphous object method a practical way to perform 3D accuracy assessment.

Remote Sensing↗

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↗

USGS2022

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

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

Open-File Report↗

USGS2022

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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