ECCOE Landsat quarterly calibration and validation report—Quarter 1, 2025
Md Obaidul Haque, Nahid Hasan, Ashish Shrestha, Rajagopalan Rengarajan, Mark Lubke, Daniel Steinwand, Paul Bresnahan, Jerad L. Shaw, Kathryn Ruslander, Esad Micijevic, Michael J. Choate, Cody Anderson, Jeff Clauson, Kurt Thome, Ed Kaita, Amit Angal, Raviv Levy, Jeff Miller, Leibo Ding, Cibele Teixeira Pinto
2025, Open-File Report 2025-1048
Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually...
Remote sensing of chlorophyll a and temperature to support algal bloom monitoring in Blue Mesa Reservoir, Colorado
Tyler Victor King, Robert Allen Bean, Katherine Walton-Day, M. Alisa Mast, Evan John Gohring, Rachel G. Gidley, Natalie K. Day, Nicole D. Gibney
2025, Journal of the American Water Resources Association (61)
We present methods to reconstruct historical chlorophyll a and surface water temperatures from satellite-based remote sensing products for Blue Mesa Reservoir, Colorado, to support algal bloom monitoring. A machine learning model was trained to construct chlorophyll a concentrations from Sentinel-2 satellite imagery and in situ measurements of chlorophyll a concentrations (out of bag RMSE = 1.9 μg/L, R2 = 0.63) and reconstruct summertime...
Toward a near-lossless image compression strategy for the NASA/USGS Landsat Next mission
Rehman S. Eon, Craig De Groot, Jeffrey A. Pedelty, Aaron Gerace, Matthew Montanaro, Richard K. Covington, Amy S. DeLisa, Wen-Ting Hsieh, Joy M. Hengear-leon, Douglas J. Daniels, Christopher Engebretson, Christopher J. Crawford, Thomas R.H. Holmes, Philip Dabney, Bruce D. Cook
2025, Remote Sensing of Environment (329)
As orbiting Earth imaging platforms carry more complex and capable instruments, efficient methods are needed to reduce the time and cost associated with storing and downlinking greater volumes of image data. The upcoming NASA/USGS Landsat Next mission, with an increase in spatial and spectral resolution over previous Landsat missions, is...
ECCOE Landsat quarterly Calibration and Validation report—Quarter 4, 2024
Md Obaidul Haque, Nahid Hasan, Ashish Shrestha, Rajagopalan Rengarajan, Mark Lubke, Daniel Steinwand, Paul Bresnahan, Jerad L. Shaw, Kathryn Ruslander, Esad Micijevic, Michael J. Choate, Cody Anderson, Jeff Clauson, Kurt Thome, Ed Kaita, Raviv Levy, Jeff Miller, Leibo Ding, Cibele Teixeira Pinto
2025, Open-File Report 2025-1036
Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The Earth Resources Observation and Science Cal/Val...
In situ, modeled, and earth observation monitoring of surface water availability in West African rangelands
Kimberly Slinski, Gabriel B. Senay, Alkhalil Adoum, Shraddhanand Shukla, Amy McNally, James Rowland, Erwan Fillol, Soni Yatheendradas, Chris Funk, Andrew Hoell, Michael Jasinski
2025, Frontiers in Water (7)
Introduction: Rangeland ponds are vital to the livelihoods of pastoral and agropastoral communities in Africa, providing an important source of water for livestock. However, sparse instrumentation across much of Africa makes it extremely challenging to monitor surface water availability in these areas. Model estimates of surface water, for example, as...
Modeling daily ice cover in northern hemisphere lakes with a long short‐term memory neural network
Xinchen He, Konstantinos M. Andreadis, Allison H. Roy, Theodore Langhorst, Abhishek Kumar, Caitlyn S. Butler
2025, Geophysical Research Letters (52)
Quantifying lake ice loss is crucial for understanding the impact of climate change on lake ecosystems. In this study, we trained a deep learning model (Long-Short Term Memory with Landsat observations, 1984–2012) to simulate Northern Hemisphere lake ice changes at a fine spatial scale (> 0.1 km2) from 1980 to...
Resiliency of land change monitoring efforts to input data resampling
Nathan C. Healey, Christopher Barber, Kelcy Smith, Rohan Mital, Jesslyn F. Brown, Charles Robison
2025, Frontiers in Remote Sensing (6)
The geometric transformation of remotely sensed imagery from one map projection to another necessitates a data resampling operation which alters the recorded values. The global Landsat archive is made available in the Universal Transverse Mercator (UTM) projection system which preserves geographic shape across small area but introduces small errors in...
Assessing gap-filled Landsat land surface temperature time-series data using different observational datasets
Hua Shi, George Z. Xian
2025, International Journal of Remote Sensing (46) 4559-4582
Landsat Analysis Ready Data (ARD)-based time-series present challenges in monitoring surface urban heat islands (SUHI) due to rapid changes in land surface temperature (LST) compared to cloud-free satellite observations. This research investigates the use of a spatiotemporal gap-filling model as a feasible and cost-effective solution to produce Landsat time-series LST...
Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery
David C. Douglas, Michael D. Fleming, Vijay P. Patil, David H. Ward
2025, Open-File Report 2025-1007
The U.S. Geological Survey and the U.S. Fish and Wildlife Service have developed a three-tiered strategy for monitoring eelgrass (Zostera marina) beds at Izembek Lagoon, Alaska, that targets different spatial and temporal scales. The broadest-scale monitoring (tier-1) uses satellite imagery about every 5 years to delineate the spatial extent of...
Fine-resolution satellite remote sensing improves spatially distributed snow modeling to near real time
Graham A. Sexstone, Garrett Alexander Akie, David J. Selkowitz, Theodore B. Barnhart, David M. Rey, Claudia León-Salazar, Emily Carbone, Lindsay A. Bearup
2025, Remote Sensing (17)
Given the highly variable distribution of seasonal snowpacks in complex mountainous environments, the accurate snow modeling of basin-wide snow water equivalent (SWE) requires a spatially distributed approach at a sufficiently fine grid resolution (<500 m) to account for the important processes in the seasonal evolution of a snowpack (e.g., wind...
System characterization report on Resourcesat-2A Advanced Wide Field Sensor
Mahesh Shrestha, Minsu Kim, Aparajithan Sampath, Jeffrey Clauson
2025, Open-File Report 2021-1030-V
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...
Automated snow cover detection on mountain glaciers usingspaceborne imagery and machine learning
Rainey Aberle, Ellyn Enderlin, Shad O'Neel, Caitlyn Florentine, Louis C. Sass, Adam Dickson, Hans-Peter Marshall, Alejandro Flores
2025, The Cryosphere (19) 1675-1693
Tracking the extent of seasonal snow on glaciers over time is critical for assessing glacier vulnerability and the response of glacierized watersheds to climate change. Existing snow cover products do not reliably distinguish seasonal snow from glacier ice and firn, preventing their use for glacier snow cover detection. Despite previous...
System characterization report on Resourcesat-2A Linear Imaging Self Scanning-3 sensor
Seonkyung Park, Mahesh Shrestha, Minsu Kim, Aparajithan Sampath, Jeffrey Clauson
2025, Open-File Report 2021-1030-T
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...
Landsat surface product validation instrumentation: The BigMAC exercise
Dennis Helder, Mahesh Shrestha, Joshua J. Mann, Emily Maddox, Jeffrey Irwin, Larry Leigh, Aaron Gerace, Rehman Eon, Lucy Falcon, David Conran, Nina G. Raqueno, Timothy Bauch, Christopher Durell, Brandon Russell
2025, Sensors (25)
Users of Earth remotely sensed optical imagery are increasingly demanding a surface reflectance or surface temperature product instead of the top-of-atmosphere products that have been produced historically. Validating the accuracy of surface products remains a difficult task since it involves assessment across a range of atmospheric profiles, as well as...
Satellite-based evidence of recent decline in global forest recovery rate from tree mortality events
Yuchao Yan, Songbai Hong, Anping Chen, Josep Peñuelas, Craig D. Allen, William M. Hammond, Seth Munson, Ranga B. Myneni, Shilong Piao
2025, Nature Plants (11) 731-742
Climate-driven forest mortality events have been extensively observed in recent decades, prompting the question of how quickly these affected forests can recover their functionality following such events. Here we assessed forest recovery in vegetation greenness (normalized difference vegetation index) and canopy water content (normalized difference infrared index) for 1,699 well-documented...
The Harmonized Landsat and Sentinel-2 version 2.0 surface reflectance dataset
Junchang Ju, Qiang Zhou, Brian Freitag, David P. Roy, Hankui Zhang, Madhu Sridhar, John Mandel, Saeed Arab, Gail L. Schmidt, Christopher J. Crawford, Ferran Gascon, Peter A. Strobl, Jeffrey G. Masek, Christopher S.R. Neigh
2025, Remote Sensing of Environment (324)
Frequent multispectral observations of sufficient spatial detail from well-calibrated spaceborne sensors are needed for large-scale terrestrial monitoring. To meet this demand, the NASA Harmonized Landsat and Sentinel-2 (HLS) project was initiated in early 2010s to produce comparable 30-m surface reflectance from the US Landsat 8 Operational Land Imager (OLI) and...
Multiyear crop residue cover mapping using narrow-band vs. broad-band shortwave infrared satellite imagery
Brian T Lamb, W. Dean Hively, Jyoti Jennewein, Alison Thieme, Alexander M. Soroka, Leticia Santos, Daniela Jones, Steven Mirsky
2025, Soil and Tillage Research (251)
Crop residue serves an important role in agricultural systems as high levels of fractional crop residue cover (fR) can reduce erosion, preserve soil moisture, and build soil organic carbon. However, the ability to accurately quantify fR at scale has been limited. In this study we produced annual maps of fR for farmland in Maryland,...
Wave driven cross shore and alongshore transport reveal more extreme projections of shoreline change in island environments
Richelle Moskvichev, Anna Mikkelsen, Tiffany Anderson, Sean Vitousek, Joel Nicolow, Charles Fletcher
2025, Scientific Reports (15)
Coastal erosion, intensified by sea level rise, poses significant threats to coastal communities in Hawaiʻi and similar island communities. This study projects long-term shoreline change on the Hawaiian Island of O‘ahu using the data-assimilated CoSMoS-COAST shoreline change model. CoSMoS-COAST models four key shoreline processes: (1) Alongshore transport, (2) Recession due...
System characterization report on the Environmental Mapping and Analysis Program (EnMAP)
Minsu Kim, Seonkyung Park, Cody Anderson
2025, Open-File Report 2021-1030-S
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...
ECCOE Landsat quarterly calibration and validation report—Quarter 3, 2024
Md Obaidul Haque, Nahid Hasan, Ashish Shrestha, Rajagopalan Rengarajan, Mark Lubke, Jerad L. Shaw, Kathryn Ruslander, Esad Micijevic, Michael J. Choate, Cody Anderson, Jeff Clauson, Kurt Thome, Ed Kaita, Raviv Levy, Jeff Miller, Leibo Ding
2025, Open-File Report 2025-1006
Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually...
Artificial neural network multilayer perceptron models to classify California’s crops using Harmonized Landsat Sentinel (HLS) data
Richard L. McCormick, Prasad Thenkabail, Itiya Aneece, Pardhasaradhi Teluguntla, Adam Oliphant, Daniel Foley
2025, Photogrammetric Engineering and Remote Sensing (91) 91-100
Advances in remote sensing and machine learning are enhancing cropland classification, vital for global food and water security. We used multispectral Harmonized Landsat 8 Sentinel-2 (HLS) 30-m data in an artificial neural network (ANN) multi-layer perceptron (MLP) model to classify five crop classes (cotton, alfalfa, tree crops, grapes, and others)...
Towards seamless global 30-meter terrestrial monitoring: Evaluating 2022 cloud free coverage of harmonized Landsat and Sentinel-2 (HLS) V2.0
Qiang Zhou, Christopher Neigh, Junchang Ju, Philip Dabney, Bruce Cook, Zhe Zhu, Christopher J. Crawford, Ferran Gascon, Peter Strobl, Madhu Sridhar
2025, IEEE Geoscience and Remote Sensing Letters (22)
Global observations at 30-m ground sampling distance (GSD) are now possible at a cadence of 1-3 days by combining Landsat 8 and 9 with Sentinel-2A and -2B satellites. Previous studies characterizing pixel-level Landsat-class measurement frequency used data from different sources but offered little information on observation availability after rigorous quality...
Annual NLCD (National Land Cover Database)—The next generation of land cover mapping
U.S. Geological Survey
2025, Fact Sheet 2025-3001
Introduction The widely used National Land Cover Database (NLCD) has long been the foundational land cover source for scientists, resource managers, and decision makers across the United States.In 2024, a reinvention as Annual NLCD added the key improvement of annual time steps to show decades of change at a higher frequency...
Modelling and mapping burn severity of prescribed and wildfires across the southeastern United States (2000-2022)
Melanie K. Vanderhoof, Casey Elizabeth Menick, Joshua J. Picotte, Kevin Robertson, Holly Nowell, Chris Matechik, Todd Hawbaker
2025, International Journal of Wildland Fire (34)
BackgroundThe southeastern United States (‘Southeast’) experiences high levels of fire activity, but the preponderance of small and prescribed fires means that existing burn severity products are incomplete across the region.AimsWe developed and applied a burn severity model across the Southeast to enhance our understanding of regional...
Leveraging airborne imaging spectroscopy and multispectral satellite imagery to map glacial sediment plumes in Kachemak Bay, Alaska
Lea Hartl, Carl Schmitt, Martin Stuefer, J. Jenckes, Benjamin Patrick Page, Christopher J. Crawford, Gail L. Schmidt, R. Yang, R. Hock
2025, Journal of Hydrology: Regional Studies (57)
Study RegionKachemak Bay is a fjord-type estuary in the northern Gulf of Alaska. Water quality and habitat characteristics are strongly influenced by freshwater and sediment input from multiple glacierized catchments.Study FocusWe present a new method combining imaging spectroscopy from an...