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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013-2018 from Assessment, Inventory, and Monitoring (AIM) instead of using the 2016 “base” map as an intermediary....
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant...
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LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types. HDist includes the year of disturbance that is recorded for that pixel. In LF 2022, the time since disturbance code is the same for both HDist...
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LANDFIRE (LF) 2022 Fuel Vegetation Type (FVT) represents the LF Existing Vegetation Type Ecological Systems (EVT) product, modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances...
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LANDFIRE's (LF) 2022 Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. CC supplies information for fire behavior models to determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. To create this product, plot level CC values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance CC and Canopy Height (CH) are used as predictors of disturbed CC using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and...
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LANDFIRE (LF) 2022 Fuel Vegetation Cover (FVC) represents the LF Existing Vegetation Cover (EVC) product, modified to represent pre-disturbance EVC in areas where disturbances have occurred over the past 10 years. EVC is mapped as continuous estimates of canopy cover for tree, shrub, and herbaceous lifeforms with a potential range from 10% to 100%. Continuous EVC values are binned to align with fuel model assignments when creating FVC. FVC is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVC is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
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Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. The blue water evapotranspiration (BWET) raster dataset at 30-meter resolution is created to estimate agricultural irrigation water consumption. The dataset contains seasonal total (1 May to 30 September) BWET time series (1986 – 2020) for the croplands across the U.S. High Plains aquifer region. The BWET estimates are generated by integrating an energy-balance ET model (Operational Simplified Surface Energy Balance model) and a water-balance ET model (Vegetation ET model). BWET in croplands reflects crop consumptive use of irrigation water extracted from surface water and groundwater...
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Climate change over the past century has altered vegetation community composition and species distributions across rangelands in the western United States. The scale and magnitude of climatic influences are largely unknown. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2023 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate the ramifications of future change across the western US, we extended models based on historical relationships over the reference period to model landscape effects based on future weather conditions from two emissions scenarios...
Tags: AB, AZ, Alberta, Arizona, Arizona Plateau, All tags...
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The LANDFIRE (LF) Canadian Forest Fire Danger Rating System (CFFDRS) product depicts fuel types as an identifiable association of fuel elements of distinctive species, form, size, arrangement, and continuity. CFFDRS exhibits characteristic fire behavior under the specified burn conditions. In LF 2022 Canadian fuel models are derived from the Fuel Model Guide to Alaska Vegetation (Alaska Fuel Model Guide Task Group, 2018) and subsequent updates. The LF CFFDRS product contains the fuel models used for the Fire Behavior Prediction (FBP) system fuel type inputs. Default values assigned to the Canadian Fuel Models required to run the Prometheus fire behavior software (Prometheus, 2021) are added as attributes to the...
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LANDFIRE's (LF) 2022 Forest Canopy Height (CH) describes the average height of the top of the canopy for a stand. CH is used in the calculation of Canopy Bulk Density (CBD) and Canopy Base Height (CBH). CH supplies information for fire behavior models, such as FARSITE (Finney 1998), that can determine the starting point of embers in the spotting model, wind reductions, and the volume of crown fuels. To create this product, plot level CH values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance Canopy Cover and CH are used as predictors of disturbed CH using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and time since...
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LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. LF 2022 Fuel Disturbance (FDist) uses the latest Annual Disturbance products from the effective disturbance years of 2013 to 2022. FDist is created from LF 2022 Historical Disturbance (HDist) which in turn aggregates the Annual Disturbance products. FDist groups similar disturbance types, severities and time since disturbance categories which represent disturbance scenarios within the fuel environment. FDist is used in conjunction with Fuel Vegetation Type (FVT), Cover (FVC), and Height (FVH) to calculate Canopy Cover (CC), Canopy Height (CH), Canopy Bulk Density (CBD), Canopy Base Height (CBH),...
We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by land surface phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute...
External websites where EvapoTranspiration data is available for download.
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Surface Urban Heat Island (SUHI) hotspot data are defined as areas of statistically high land surface temperature (LST). A pixel is determined as statistically high if it exceeds one standard deviation above the mean of all pixels with similar land cover type. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual maximum land surface temperature (MaxLST) – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. The data is further separated into persistent urban and new urban outputs. Persistent Urban is defined as areas that are reported as urban in 1985 and...
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Disclaimer: this is an historic version of NLCD provided for research and citation purposes. Different release dates of NLCD cannot be used with other release dates for correct analysis. Each release of NLCD generates a complete set of directly comparable products. These products must be used together for correct analysis. You can find the latest suite of synced products at www.mrlc.gov. The National Land Cover Database 2001 land cover layer for mapping zones 01-66 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National...
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These datasets provide early estimates of 2024 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from April to late June. Typically, the EAG estimates are publicly released within 7-13 days of the latest satellite observation used for that version. Each weekly release contains five fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) Field Brome (Bromus arvensis); 4) medusahead (Taeniatherum caput-medusae); and 5) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory,...
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Disclaimer: this is an historic version of NLCD provided for research and citation purposes. Different release dates of NLCD cannot be used with other release dates for correct analysis. Each release of NLCD generates a complete set of directly comparable products. These products must be used together for correct analysis. You can find the latest suite of synced products at www.mrlc.gov. The National Land Cover Database 2011 (NLCD2011) USFS percent tree canopy product was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium (www.mrlc.gov). The MRLC Consortium is a partnership of federal agencies, consisting of the U.S. Geological Survey, the National...
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The National Land Cover Database (NLCD) is a land cover monitoring program providing land cover information for the United States. NLCD2016 extended temporal coverage to 15 years (2001–2016). We collected land cover reference data for the 2011 and 2016 nominal dates to report land cover accuracy for the NLCD2016 database 2011 and 2016 land cover components. We measured land cover accuracy at Level II and Level I, and change accuracy at Level I. For both the 2011 and 2016 land cover components, single-date Level II overall accuracies (OA) were 72% (standard error of ±0.9%) when agreement was defined as match between the map label and primary reference label only and 86% (± 0.7%) when agreement also included the alternate...
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The National Park Service (NPS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic...


map background search result map search result map National Land Cover Database (NLCD) 2001 Land Cover Conterminous United States (ver. 2.0, July 2024) National Land Cover Database (NLCD) 2011 Land Cover Conterminous United States (ver. 2.0, May 2024) National Park Service Thematic Burn Severity Mosaic in 2013 (ver. 8.0, August 2024) Rangeland Condition Monitoring Assessment and Projection (RCMAP) Non Sagebrush Shrub Fractional Component Time-Series Across the Western U.S. 1985-2021 Data Distribution LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Forest Canopy Height (CH) AK LANDFIRE 2022 Fuel Disturbance (FDist) AK LANDFIRE 2022 Canadian Forest Fire Danger Rating System (CFFDRS) AK National Land Cover Database (NLCD) 2016 Accuracy Assessment Points Conterminous United States LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI SUHI Hotspot from MaxLST in persistent urban and new growth urban area of 50 cities of CONUS from 1985 to 2020 Seasonal Blue Water Evapotranspiration 1986 – 2020 for the Croplands in the High Plains Aquifer Region Projections of Rangeland Fractional Component Cover Across Western Northern American Rangelands for Representative Concentration Pathways (RCP) 4.5 and 8.5 Scenarios for the 2020s, 2050s, and 2080s Time-Periods Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2024 LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI National Land Cover Database (NLCD) 2001 Land Cover Conterminous United States (ver. 2.0, July 2024) Seasonal Blue Water Evapotranspiration 1986 – 2020 for the Croplands in the High Plains Aquifer Region Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2024 Projections of Rangeland Fractional Component Cover Across Western Northern American Rangelands for Representative Concentration Pathways (RCP) 4.5 and 8.5 Scenarios for the 2020s, 2050s, and 2080s Time-Periods Rangeland Condition Monitoring Assessment and Projection (RCMAP) Non Sagebrush Shrub Fractional Component Time-Series Across the Western U.S. 1985-2021 LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Forest Canopy Height (CH) AK LANDFIRE 2022 Fuel Disturbance (FDist) AK LANDFIRE 2022 Canadian Forest Fire Danger Rating System (CFFDRS) AK National Land Cover Database (NLCD) 2016 Accuracy Assessment Points Conterminous United States SUHI Hotspot from MaxLST in persistent urban and new growth urban area of 50 cities of CONUS from 1985 to 2020 LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS National Land Cover Database (NLCD) 2011 Land Cover Conterminous United States (ver. 2.0, May 2024) Data Distribution National Park Service Thematic Burn Severity Mosaic in 2013 (ver. 8.0, August 2024)