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At least 253 records · Page 14Linked to original sources
USGS2003

Status and interconnections of selected environmental issues in the global coastal zones

This study focuses on assessing the state of population distribution, land cover distribution, biodiversity hotspots, and protected areas in global coastal zones. The coastal zone is defined as land within 100 km of the coastline. This study attempts to answer such questions as: how crowded are the coastal zones, what is the pattern of land cover distribution in these areas, how much of these areas are designated as protected areas, what is the state of the biodiversity hotspots, and what are the interconnections between people and coastal environment. This study uses globally consistent and comprehensive geospatial datasets based on remote sensing and other sources. The application of Geographic Information System (GIS) layering methods and consistent datasets has made it possible to identify and quantify selected coastal zones environmental issues and their interconnections. It is expected that such information provide a scientific basis for global coastal zones management and assist in policy formulations at the national and international levels.

Ambio↗
USGS2010

Hyperspectral analysis of columbia spotted frog habitat

Wildlife managers increasingly are using remotely sensed imagery to improve habitat delineations and sampling strategies. Advances in remote sensing technology, such as hyperspectral imagery, provide more information than previously was available with multispectral sensors. We evaluated accuracy of high-resolution hyperspectral image classifications to identify wetlands and wetland habitat features important for Columbia spotted frogs (Rana luteiventris) and compared the results to multispectral image classification and United States Geological Survey topographic maps. The study area spanned 3 lake basins in the Salmon River Mountains, Idaho, USA. Hyperspectral data were collected with an airborne sensor on 30 June 2002 and on 8 July 2006. A 12-year comprehensive ground survey of the study area for Columbia spotted frog reproduction served as validation for image classifications. Hyperspectral image classification accuracy of wetlands was high, with a producer's accuracy of 96 (44 wetlands) correctly classified with the 2002 data and 89 (41 wetlands) correctly classified with the 2006 data. We applied habitat-based rules to delineate breeding habitat from other wetlands, and successfully predicted 74 (14 wetlands) of known breeding wetlands for the Columbia spotted frog. Emergent sedge microhabitat classification showed promise for directly predicting Columbia spotted frog egg mass locations within a wetland by correctly identifying 72 (23 of 32) of known locations. Our study indicates hyperspectral imagery can be an effective tool for mapping spotted frog breeding habitat in the selected mountain basins. We conclude that this technique has potential for improving site selection for inventory and monitoring programs conducted across similar wetland habitat and can be a useful tool for delineating wildlife habitats. ?? 2010 The Wildlife Society.

Journal of Wildlife Management↗
USGS2016

A Unified Cropland Layer at 250-m for global agriculture monitoring

Accurate and timely information on the global cropland extent is critical for food security monitoring, water management and earth system modeling. Principally, it allows for analyzing satellite image time-series to assess the crop conditions and permits isolation of the agricultural component to focus on food security and impacts of various climatic scenarios. However, despite its critical importance, accurate information on the spatial extent, cropland mapping with remote sensing imagery remains a major challenge. Following an exhaustive identification and collection of existing land cover maps, a multi-criteria analysis was designed at the country level to evaluate the fitness of a cropland map with regards to four dimensions: its timeliness, its legend, its resolution adequacy and its confidence level. As a result, a Unified Cropland Layer that combines the fittest products into a 250 m global cropland map was assembled. With an evaluated accuracy ranging from 82% to 95%, the Unified Cropland Layer successfully improved the accuracy compared to single global products.

Data↗
USGS2013

The LANDFIRE Refresh strategy: updating the national dataset

The LANDFIRE Program provides comprehensive vegetation and fuel datasets for the entire United States. As with many large-scale ecological datasets, vegetation and landscape conditions must be updated periodically to account for disturbances, growth, and natural succession. The LANDFIRE Refresh effort was the first attempt to consistently update these products nationwide. It incorporated a combination of specific systematic improvements to the original LANDFIRE National data, remote sensing based disturbance detection methods, field collected disturbance information, vegetation growth and succession modeling, and vegetation transition processes. This resulted in the creation of two complete datasets for all 50 states: LANDFIRE Refresh 2001, which includes the systematic improvements, and LANDFIRE Refresh 2008, which includes the disturbance and succession updates to the vegetation and fuel data. The new datasets are comparable for studying landscape changes in vegetation type and structure over a decadal period, and provide the most recent characterization of fuel conditions across the country. The applicability of the new layers is discussed and the effects of using the new fuel datasets are demonstrated through a fire behavior modeling exercise using the 2011 Wallow Fire in eastern Arizona as an example.

Fire Ecology↗
USGS2006

Atlantic Seaduck Project

Atlantic Seaduck Project is being conducted to learn more about the breeding and moulting areas of seaducks in northern Canada and more about their feeding ecology on wintering areas, especially Chesapeake Bay. Satellite telemetry is being used to track surf scoters wintering in Chesapeake Bay, Maryland and black scoters on migrational staging areas in New Brunswick, Canada to breeding and moulting areas in northern Canada. Various techniques used to capture the scoters included mist netting, night-lighting, and net capture guns. All captured ducks were transported to a veterinary hospital where surgery was conducted following general anaesthesia procedures. A PTT100 transmitter (39 g) manufactured by Microwave, Inc., Columbia, Maryland was implanted into the duck?s abdominal cavity with an external (percutaneous) antenna. Eight of the surf scoters from Chesapeake Bay successfully migrated to possible breeding areas in Canada and all 13 of the black scoters migrated to suspected breeding areas. Ten of the 11 black scoter males migrated to James Bay presumably for moulting. Updated information from the ARGOS Systems aboard the NOAA satellites on scoter movements was made accessible on the Patuxent Website. Habitat cover types of locations using GIS (Geographical Information Systems) and aerial photographs (in conjunction with remote sensing software) are currently being analyzed to build thematic maps with varying cosmetic layer applications. Many factors related to human population increases have been implicated in causing changes in the distribution and abundance of wintering seaducks. Analyses of the gullet (oesophagus and proventriculus) and the gizzard of seaducks are currently being conducted to determine if changes from historical data have occurred. Scoters in the Bay feed predominantly on the hooked mussel and several species of clams. The long-tailed duck appears to select the gem clam in greater amounts than other seaducks, but exhibits a diverse diet of other mollusks and crustaceans. Seaduck food habits in the Maritimes are decidedly different, where all three species of scoters feed extensively on the blue mussel. Understanding the feeding ecology of seaducks in wintering areas such as the Chesapeake Bay and the Maritimes will provide managers with a better understanding of the changes in the distribution and abundance of these ducks. Future studies will attempt to determine the effects of experimental diets varying in protein and energy levels on the physiology and behaviour of captive seaducks. An attempt will be made to determine if seaducks exhibit an endogenous rhythm in regard to body weight and condition during the winter. Foraging energetics in relation to different food sources found in the Chesapeake Bay will be measured in two large aquariums (dive tanks) with scoters and long-tailed ducks. The combined studies being conducted in the Atlantic Seaduck Project will greatly aid the conservation effort for seaducks presently being conducted throughout the world.

Book chapter↗
USGS1980

An assessment of Landsat data acquisition history on identification and area estimation of corn and soybeans

During the past decade, numerous studies have demonstrated the potential of satellite remote sensing for providing accurate and timely crop area information. This study assessed the impact of Landsat data acquisition history on classification and area estimation accuracy of corn and soybeans. Multitemporally registered Landsat MSS data from four acquisitions during the 1978 growing season were used in classification of eight sample segments in the U.S. Corn Belt. The results illustrate the importance of selecting Landsat acquisitions based on spectral differences in crops at certain growth stages.

Technical Report↗
USGS2011

The use of historical imagery in the remediation of an urban hazardous waste site

The information derived from the interpretation of historical aerial photographs is perhaps the most basic multitemporal application of remote-sensing data. Aerial photographs dating back to the early 20th century can be extremely valuable sources of historical landscape activity. In this application, imagery from 1918 to 1927 provided a wealth of information about chemical weapons testing, storage, handling, and disposal of these hazardous materials. When analyzed by a trained photo-analyst, the 1918 aerial photographs resulted in 42 features of potential interest. When compared with current remedial activities and known areas of contamination, 33 of 42 or 78.5% of the features were spatially correlated with areas of known contamination or other remedial hazardous waste cleanup activity.

IEEE Journal of Selected Topics in Applied Earth O↗
USGS2008

Monitoring fine-grained sediment in the Colorado River ecosystem, Arizona — Control network and conventional survey techniques

In 2002, fine-grained sediment (sand, silt, and clay) monitoring in the Colorado River downstream from Glen Canyon Dam was initiated to survey channel topography at scales previously unobtainable in this canyon setting. This report presents the methods used to establish the high-resolution global positioning system (GPS) control network required for this effort as well as the conventional surveying techniques used in the study. Using simultaneous, dual-frequency GPS vector-based methods, the network points were determined to have positioning accuracies of less than 0.03 meters (m) and ellipsoidal height accuracies of between 0.01 and 0.10 m at a 95-percent degree of confidence. We also assessed network point quality with repeated, electronic (optical) total-station observations at 39 points for a total of 362 measurements; the mean range was 0.022 m in horizontal and 0.13 in vertical at a 95-percent confidence interval. These results indicate that the control network is of sufficient spatial and vertical accuracy for collection of airborne and subaerial remote-sensing technologies and integration of these data in a geographic information system on a repeatable basis without anomalies. The monitoring methods were employed in up to 11 discrete reaches over various time intervals. The reaches varied from 1.3 to 6.4 kilometers in length. Field results from surveys in 2000, 2002, and 2004 are described, during which conventional surveying was used to collect more than 3000 points per day. Ground points were used as checkpoints and to supplement areas just below or above the water surface, where remote-sensing data are not collected or are subject to greater error. An accuracy of +or- 0.05 m was identified as the minimum precision of individual ground points. These results are important for assessing digital elevation model (DEM) quality and identifying detection limits of significant change among surfaces generated from remote-sensing technologies.

Arizona↗
USGS2016

The Land Processes Distributed Active Archive Center (LP DAAC)

The Land Processes Distributed Active Archive Center (LP DAAC) operates as a partnership with the U.S. Geological Survey and is 1 of 12 DAACs within the National Aeronautics and Space Administration (NASA) Earth Observing System Data and Information System (EOSDIS). The LP DAAC ingests, archives, processes, and distributes NASA Earth science remote sensing data. These data are provided to the public at no charge. Data distributed by the LP DAAC provide information about Earth’s surface from daily to yearly intervals and at 15 to 5,600 meter spatial resolution. Data provided by the LP DAAC can be used to study changes in agriculture, vegetation, ecosystems, elevation, and much more. The LP DAAC provides several ways to access, process, and interact with these data. In addition, the LP DAAC is actively archiving new datasets to provide users with a variety of data to study the Earth.

Fact Sheet↗
USGS2017

Monitoring protocols: Options, approaches, implementation, benefits

Monitoring and adaptive management are fundamental concepts to rangeland management across land management agencies and embodied as best management practices for private landowners. Historically, rangeland monitoring was limited to determining impacts or maximizing the potential of specific land uses—typically grazing. Over the past several decades, though, the uses of and disturbances to rangelands have increased dramatically against a backdrop of global climate change that adds uncertainty to predictions of future rangeland conditions. Thus, today’s monitoring needs are more complex (or multidimensional) and yet still must be reconciled with the realities of costs to collect requisite data. However, conceptual advances in rangeland ecology and management and changes in natural resource policies and societal values over the past 25 years have facilitated new approaches to monitoring that can support rangeland management’s diverse information needs. Additionally, advances in sensor technologies and remote-sensing techniques have broadened the suite of rangeland attributes that can be monitored and the temporal and spatial scales at which they can be monitored. We review some of the conceptual and technological advancements and provide examples of how they have influenced rangeland monitoring. We then discuss implications of these developments for rangeland management and highlight what we see as challenges and opportunities for implementing effective rangeland monitoring. We conclude with a vision for how monitoring can contribute to rangeland information needs in the future.

Book chapter↗
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↗
USGS2024

Identifying conservation introduction sites for endangered birds through the integration of lidar-based habitat suitability models and population viability analyses

Similar to other single-island endemic Hawaiian honeycreepers, the critically endangered ‘ākohekohe ( Palmeria dolei ) is threatened by climate-driven disease spread. To avert the imminent risk of extinction, managers are considering novel measures, including the conservation introduction (CI) of ‘ākohekohe from Maui to higher elevation habitats on the Island of Hawai’i. This study integrated lidar-based habitat suitability models (LHSMs) and population viability analyses (PVAs) to assess five candidate sites currently considered by managers for CI. We first developed an LHSM for the species’ native range on Maui. We then projected habitat suitability across candidate CI sites, using forest structure and topography metrics standardized across sensor types. Given the structural variability observed within the five candidate sites, we identified clusters of contiguous, highly suitable habitat as potential release sites. We then determined how many adult individuals could be supported by each cluster based on adult home range estimates. To determine which clusters could house the minimum number of ‘ākohekohe birds necessary for a stable or increasing future population, we conducted PVAs under multiple scenarios of bird releases. We found that canopy height and relative height 90 had the greatest effects on model performance, possibly reflecting ‘ākohekohe’s preference for taller canopies. We found that a small release of at least nine pairs of equal sex ratios were sufficient for an 80% chance of success and a <1% chance of extirpation in 20 years, resulting in a minimum release area of 4.5 ha in size. We integrated the results of the LHSM and PVA into an interactive web application that allowed managers to consider the caveats and uncertainties associated with both LHSMs and PVAs in their decision-making process. As climate change continues to threaten species worldwide, this research demonstrates the value of lidar remote sensing combined with species-specific models to enable rapid, quantitative assessments that can inform the increasing consideration of time-sensitive conservation introductions.

Hawaii↗
USGS2022

Keeping an eye on water quality from the sky

You can learn a lot about rivers, lakes, estuaries, and oceans by looking down at them from the sky. Scientists use a technique called remote sensing to measure the amount of light or heat energy reflected and emitted from the Earth. Sensors can be on satellites or mounted on airplanes, helicopters, or drones. Scientists use this information to map the quality of water in the San Francisco Bay-Delta estuary. Remote sensing helps scientists see where and when there might be problems for human health or for the plants and animals living in the estuary.

California↗
USGS1993

Availability of Earth observations data from the U.S. Geological Survey's EROS data center

For decades federal and state agencies have been collecting regional, continental, and global Earth observations data acquired by satellites, aircraft, and other information-gathering systems. These data include photographic and digital remotely sensed images of the Earth's surface, as well as earth science, cartographic, and geographic data. Since 1973, the U.S. Geological Survey's Earth Resources Observation Systems (EROS) Data Center (EDC) in Sioux Falls, South Dakota, has been a data management, production, dissemination, and research center for these data. Currently, the Data Center holds over 10 million satellite images and aerial photographs, in photographic and digital formats. Users are able to place inquiries and orders for these holdings via a nationwide computer network. In addition to cataloging the data stored in its archives, the Data Center provides users with rapid access to information on many data collections held by other facilities.

Pecora 12 Symposium↗
USGS2010

A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km 2 study area in Arctic Alaska. The study area is centered at 69 °N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10°, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000–2009.

Alaska↗
USGS1979

The brightness of lights on Earth at night, digitally recorded by DMSP satellite

The U.S. Air Force has operated its Defense Meteorological Satellite Program (DMSP) for nearly a decade, and film images from the system have been openly available since 1973. Films are well suited for the study of weather, and users of such films have derived much useful data. For many potential remote sensing applications, however, a quantitative measurement of the brightness of the imaged light patterns is needed, and it cannot be extracted with adequte accuracy from the films. Such information is contained in the telemetry from the spacecraft and is retained on digital tapes, which store the images for a few days while they await filming. For practical reasons, it has not heretofore been feasible for the Air Force to provide a remote-sensing user with these digital data, and the quantitative brightness information has been lost with the erasure of tapes for re-use. For the purpose of evaluation of tapes as a means for remote sensing, the Air Force recently did provide to the author six examples containing records of nighttime DMSP imagery similar to that which has previously 1 been evaluated by SRI International in a film format. The digital data create many new applications for these images, owing to a combination of several factors, the most important of which are the preservation of photometric information and of full spatial resolution. In this evaluation, stress has been placed upon determination of the broad potential value of the data rather than the full exploitation of any one aspect of it. The effort was guided by an objective to develop handling methods for the vast body of numbers--methods which will be practical for use in a research or engineering environment where budgets are limited, and specialized capabilities and image reproduction equipment has not already been developed. We report the degree of success obtained in this effort, pointing out the relative strengths and the relative limitations, as compared to the sophisticated, weather-oriented data processing which is well suited for the Air Force requirements. Both geometric and photometric calibration methods are evaluated. An image can be considered as a 3-dimensional array, X, Y, Z, in which X and Y are the coordinates of a picture element (pixel) and Z is the brightness at that location. A method of approach to handling these parameters, particularly Y and Z, is developed in a form quite different from that which serves the operational applications. The user of digital data will need the film images which are generated by the Air Force from the same data as is provided on digital tape. In the first stages of analysis, the films provide both a convenient index and a guide to identification of large patterns in the data. Additionally, the infrared (8 to 13 0 film provides a valuable indicator of cloud cover. Two general conclusions are drawn from this study. Firstly, the digital DMSP data have great potential value but their cost, in terms of the interruption of the present operational routine, is quite high. Therefore, if a program is undertaken to provide for the open availability of an archive of digital records, great care must be exercised in selecting only those records which have unusually high value in order that the effort will be cost-effective. Secondly, it is concluded that several aspects of the program, well designed for Air Force operational purposes, are not adapted to earth-sensing needs. This is probably inevitable, since the two applications are largely different and in some ways incompatible. For example, the nighttime visual sensor saturates in the center of major cities and in moderately large fires (such as gas flares). This saturation prevents the analyst from integrating photometric parameters. For weather observation, this inability is unimportant, and acceptance of such saturation makes feasible a decrease in the data rate. Such limitations in the data will probably be overcome only through modifying the existing system or the implementation of a similar system designed specifically to serve earth-sensing needs.

Open-File Report↗
USGS2001

Transboundary movement of airborne pollutants — A methodology for integrating spaceborne images and ground based data

The availability of relevant and accurate environmental information is essential for environmental policy-makers. Recent improvements in satellite remote sensing technologies, groundbased monitors, and data access have resulted in the ability to observe and assess major atmospheric and ecological events around the world on a timely basis Each of these monitoring technologies reveals different and useful information, yet rarely are the resulting data sets used together in an integrated manner. The U.S. Environmental Protection Agency (EPA) and the United Nations Environment Programme (UNEP) Global Resource Information Database (GRID) office in Sioux Falls identified an environmental issue of global interest as a test case for applying an integrated approach: the transboundary movement of atmospheric pollutants. Transboundary movement of atmospheric pollutants has ramifications for human and environmental health, as well as economic impacts. As a result, it is the focus of many bilateral, regional, and international policy efforts. A central question with atmospheric pollutant transport is how to monitor pollutant movement and how to merge different monitoring datasets into useful information. Highly visible regional plumes of dust, smoke, and urban haze can be seen with satellite sensors, while ground-based monitoring of air pollutants such as fine particulates, SO2 , and toxics occurs at the local level. Integration of these two kinds of measurements allows the user to remotely observe large environmental effects in many areas of the world, while obtaining more detailed information from ground-based monitors. Hence, the combination of satellite-based sensor data and ground-based monitoring data promotes greater understanding of the movement of pollutants than either data set alone. Combined data sets are important for use by both scientists and international policy-makers. A standard methodology did not exist to guide and encourage integrated use of satellite images and ground-based data to monitor and understand major pollution events, such as air pollution. Thus, a small team was assembled to develop a methodology for the integration of satellite images and ground-based data. First, we conducted a literature and project review covering past and current integrated remote and ground-based data projects, a literature search of published work, and a search of data sets and technologies that could be used in a combined form. Second, based on this search and documentation, a general methodology was developed for using integrated spaceborne and ground-based data sets, intended as a guide for general scientists and policy-makers. Third, we found an existing project that was willing to be a pilot for testing the methodology: a U.S. EPANOAA project that was using aerial and ground-based sampling to learn more about the airborne sources of mercury deposition in the Florida Everglades. This document presents the results of the literature and project review, the complete methodology, and the outcome of the Florida Everglades pilot project.

Report↗
USGS2026

Basal area loss from fire using field-calibrated remote sensing refines western US fire severity measurements

The spatial patterns of fire effects and tree mortality have profound consequences for forest resilience. Cost-effective, medium-resolution, and spatiotemporally extensive fire severity measurements are essential for informing post-fire restoration and improving our understanding of wildfires—from forest stands to continents and from days to decades. Remote sensing advancements have improved burn severity mapping, but methods vary in interpretability, scalability, generalizability, and alignment with field measurements. One meaningful metric of fire effects on forests is proportion basal area loss, but existing methods are limited by a lack of region-specific field reference data and a scalable mapping framework. To address these issues, we compiled 3280 field reference plots from 123 fires in forests across the Western US to calculate the proportion of fire-induced basal area loss. We then used spatially cross-validated machine learning models with concurrent hyperparameter tuning to select a skillful, parsimonious model from a large candidate set of remotely-sensed, climatic, and topographic predictors. Spectral-only measures of severity over- or underestimated basal area loss in dry versus wet years and across aspects, demonstrating the value of incorporating climatic and topographic context. We also tested model performance on a separate holdout dataset in the Southwest US as a demonstration of reproducibility and transparency. We provide a Google Earth Engine tool for estimating proportional basal area loss for any fire perimeter in the Western US, enabling rapid map creation for land management and ecological modeling. All code, model parameters, and training data are released to support reproducibility, community adoption, regional refinement, and adaptation to new regions.

western United States↗