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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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These data represent total vegetation and surface water along approximately 12 kilometers of the Paria River upstream from the confluence of the Colorado River at Lees Ferry, Arizona. They are derived from airborne, multispectral imagery obtained in late May 2009, 2013, and 2021, collected with a push-broom sensor with 4 spectral bands depicting Blue, Green, Red and Near-Infrared wavelengths at a spatial resolution of 20 centimeters. The vegetation classification data were created using a supervised classification algorithm provided by Harris Geospatial in ENVI version 5.6.3 (Exelis Visual Information Solutions, Boulder, Colorado). The water data were created using a Green Normalized Difference Vegetation Index...
Tags: Arizona, Botany, Cloud Optimized GeoTIFF data, Colorado River, Ecology, All tags...
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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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These data were compiled for evaluating plant water use, or river-reach level evapotranspiration (ET) data, in the riparian corridor of the Colorado River delta as specified under Minute 319 of the 1944 Water Treaty. Additionally, these data were compiled for evaluating restoration-level data in Reach 2 and Reach 4, as specified under Minute 323 of the 1944 Water Treaty. Objectives of our study were to measure the peak growing season evapotranspiration (ET) for the average of months in summer-fall (May to October) for the seven reaches, for the full riparian corridor, and for four restoration sites, from 2013 through 2022. The seven reach areas from the Northerly International Boundary (NIB) to the end of the delta...
Tags: 1944 Water Treaty, Arizona, Botany, Colorado River, Colorado River delta, 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),...
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These data were collected to support the development of detection and classification algorithms to support Bureau of Ocean Energy Management (BOEM) studies and assessments associated with offshore wind energy production. There are 3 child zip files included in this data release. 01_Codebase.zip contains a codebase for using deep learning to filter images based on the probability of any bird occurrence. It includes instructions and files necessary for training, validating, and testing a machine learning detection algorithm. 02_Imagery.zip contains imagery that were collected using a Partenavia P68 fixed-wing airplane using a PhaseOne iXU-R 180 forward motion compensating 80-megapixel digital frame camera with...
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Active channel as defined by remote sensing before (2010 and after (2011) a 40 year return period flood (December 2010) within the lower Virgin River, Nevada.
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The Gap Analysis Project (GAP) Analytical Database represents a synthesis of three core datasets for the conterminous U.S. Specifically 1) the GAP/LANDFIRE National Terrestrial Ecosystems_2011; 2) the Protected Areas Database of the United States (PAD-US) 1.4; and 3) the Species Ranges and Habitat Distribution Models for all terrestrial vertebrates. This database provides a mechanism to effiiently obtain summary statistics of those for a variety of spatial extents, including US states, US counties, Landscape Conservation Cooperation Network Areas, EPA's Level III-IV Ecoregions of the United States, and Level I-III Ecoregions of North America and 12-digit (6th level) hydrologic units. Disclaimer for Approved Database...
Tags: Alabama, Alaska, Arizona, Arkansas, California, All tags...
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These data were compiled for the Altar Valley Conservation Alliance and the U. S. Fish and Wildlife Service to identify and quantify the spatial distribution of fine fuels in relation to wildfire management across jurisdictional boundaries. Objective(s) of our study were to map the 2021 annual distribution of the biomass (kg/ha) of fine fuels (grasses, shrubs, and forbs) for the whole of the Altar Valley, AZ, including the Buenos Aires National Wildlife Refuge. These data represent estimated biomass of fine fuels (kg/ha) at a 10-m resolution. These data were collected/created in September through October 2021 for the Altar Valley, located in Pima County, AZ, USA. These data were collected/created by the U.S. Geological...
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Unpiloted aerial system (UAS) flight campaigns were conducted at two rangeland sites in Southwestern Montana during the 2018 growing season to classify vegetation and landcover types. A total of nine flights were conducted at the Argenta site and seven at the Virginia City site. To align images in space and time, we used four-dimensional structure from motion (4D SfM) and continued with processing for each flight date based on the full suite of images aligned for the entire growing season. We created dense point clouds, digital terrain models (bare earth), digital elevation models (including vegetation), and orthorectified images for each flight date at each site. We used the orthoimages to calculate the Normalized...
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Remotely sensed elk locations were derived from satellite and Unmanned Aerial Systems (UAS) imagery collected during the winter of 2018 and the winter and spring of 2019 at the National Elk Refuge in Jackson, Wyoming and compared to locations from Global Positioning System (GPS) collars from 2017 - 2019. This data release provides the source, date, time, latitude, and longitude of elk locations and the type of analyses the location data were used for in the accompanying manuscript by Graves and others 2021. DOI will be provided once supplied by the journal.
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LANDFIRE's (LF) Annual Disturbance products provide temporal and spatial information related to landscape change. Annual Disturbance depicts areas of 4.5 hectares (11 acres) or larger that have experienced a natural or anthropogenic landscape change (or treatment) within a given year. For the creation of the Annual Disturbance product, information sources include national fire mapping programs such as Monitoring Trends in Burn Severity (MTBS), Burned Area Reflectance Classification (BARC) and Rapid Assessment of Vegetation Condition after Wildfire (RAVG), 18 types of agency-contributed "event" perimeters (see LF Public Events Geodatabase), and remotely sensed Landsat imagery. To create the LF Annual Disturbance...
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LANDFIRE (LF) 2022 Fuel Vegetation Height (FVH) represents the LF Existing Vegetation Height (EVH) product, modified to represent pre-disturbance EVH in areas where disturbances have occurred over the past 10 years. EVH is mapped as continuous estimates of canopy height for tree, shrub, and herbaceous lifeforms with a potential range of 0-100m. Continuous EVH values are binned to align with fuel model assignments when creating FVH. FVH 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 FVH is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
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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),...
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LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Height (EVH) represents the average height of the dominant vegetation for a 30-m cell. EVH is produced separately for tree, shrub, and herbaceous lifeforms using training data depicting the weighted average height by species cover and Existing Vegetation Type (EVT) lifeform. Decision tree models using field reference data, lidar, and Landsat are developed separately for each lifeform, then lifeform specific height class layers are merged along with land cover into a single EVH product based on the dominant lifeform of each pixel. EVH ranges are continuous for the herbaceous lifeform category ranging from 0.1 to 1 meter with decimeter increments, 0.1 to 3...


map background search result map search result map U.S. Geological Survey Gap Analysis Project (GAP) Analytical Database Active channel in the Lower Virgin River before and after a 40 yr flood (December 2010) Remotely sensed elk locations on the National Elk Refuge, Wyoming, 2017-2019 UAV based vegetation classification results and input NDVI, vegetation height, and texture datasets for two Montana rangeland sites in 2018 Predicted biomass of fine fuel for Altar Valley, Arizona, 2021 Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Fuel Vegetation Height (FVH) AK LANDFIRE 2022 Forest Canopy Height (CH) AK LANDFIRE 2022 Fuel Disturbance (FDist) AK LANDFIRE 2022 Canadian Forest Fire Danger Rating System (CFFDRS) AK Remotely-sensed observations of restoration sites of the riparian corridor of the Colorado River Delta in Mexico, 2013-2022 LANDFIRE Annual Disturbance AK 2022 LANDFIRE 2022 Existing Vegetation Height (EVH) Puerto Rico US Virgin Islands LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Fuel Disturbance (FDist) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI Code, imagery, and annotations for training a deep learning model to detect wildlife in aerial imagery Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA Remotely sensed elk locations on the National Elk Refuge, Wyoming, 2017-2019 Active channel in the Lower Virgin River before and after a 40 yr flood (December 2010) Predicted biomass of fine fuel for Altar Valley, Arizona, 2021 Remotely-sensed observations of restoration sites of the riparian corridor of the Colorado River Delta in Mexico, 2013-2022 LANDFIRE 2022 Existing Vegetation Height (EVH) Puerto Rico US Virgin Islands LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Fuel Disturbance (FDist) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI Code, imagery, and annotations for training a deep learning model to detect wildlife in aerial imagery LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Fuel Vegetation Height (FVH) AK LANDFIRE 2022 Forest Canopy Height (CH) AK LANDFIRE 2022 Fuel Disturbance (FDist) AK LANDFIRE 2022 Canadian Forest Fire Danger Rating System (CFFDRS) AK LANDFIRE Annual Disturbance AK 2022 LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS U.S. Geological Survey Gap Analysis Project (GAP) Analytical Database