This dataset represents mean percent are burned from wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018. The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions

This dataset represents percent area burned in each burn severity class for wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018.The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions

This dataset represents the historical fire perimeters within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the GeoMAC (Geospatial Multi-Agency Coordination) mapping tool. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. Fire perimeters contain data as they are submitted by field offices to GeoMAC (Geospatial Multi-Agency Coordination) in a polygon format. Fire perimeter data is based on input from incident intelligence sources, GPS data, infrared (IR) imagery from fixed wing and satellite platforms. Polygons are selected by year and then converted into a binary raster format where values of 1 represent fire perimeters of the given year and 0 describes the remaining areas across the CONUS, leaving No Data to be anything outside the CONUS border. The wildland fire characteristics (% forest loss to fire) were summarized by year to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents the average height of the dominant vegetation for a 30-m grid cell within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on field reference data and Landsat, elevation, and ancillary data. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The Existing Vegetation Type (EVT) layer represents the species composition currently present at a given site. Vegetation map units are primarily derived from NatureServe's Ecological Systems classification, which is a nationally consistent set of mid-scale ecological units. Additional units are derived from NLCD, National Vegetation Classification Standard (NVCS) Alliances, and LANDFIRE specific types. - Reclassified into introduced managed vegetation cover - IntrodManagVeg class - reclass from EVT - groups (EVT_GP) = (701,702,703,704,705,706,707,708,709,711,731) Canopy height is generated separately for tree, shrub and herbaceous lifeforms using training data and other layers. EVH is determined by the average height weighted by species cover and based on the existing vegetation type (EVT) lifeform. Decision tree models using field reference data and Landsat, elevation, and ancillary data are developed separately for each lifeform. Decision tree relationships are used to generate lifeform specific height class layers, which are merged into a single composite EVH layer. The vegetation characteristics (%) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents mean percent are burned from wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018. The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions

This dataset represents percent area burned in each burn severity class for wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018.The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions

This dataset represents the historical fire perimeters within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the GeoMAC (Geospatial Multi-Agency Coordination) mapping tool. Fire perimeters contain data as they are submitted by field offices to GeoMAC (Geospatial Multi-Agency Coordination) in a polygon format. Fire perimeter data is based on input from incident intelligence sources, GPS data, infrared (IR) imagery from fixed wing and satellite platforms. Polygons are selected by year and then converted into a binary raster format where values of 1 represent fire perimeters of the given year and 0 describes the remaining areas across the CONUS, leaving No Data to be anything outside the CONUS border. The wildland fire characteristics (% forest loss to fire) were summarized by year to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents the characterization of global forest extent and change by year from 2001 through 2013 within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the Global Forest Change 2000, 2013, 2013. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. These data are based on global tree cover loss for the period from 2001 to 2013 at a spatial resolution of 30m. The analysis used to create the landscape layer is based on Landsat data. Forest loss was defined as a stand-replacement disturbance or the complete removal of tree cover canopy at the Landsat pixel scale. This landscape layer is a disaggregation of total forest loss to annual time scales. Encoded as either 0 (no loss) or else a value in the range 1, 201313, representing loss detected primarily in the year 2001, 2013, 2013, respectively. The forest loss by year characteristics (%) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents the elevation values within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Elevation Dataset. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. NHDPlusV2 records NED snapshot dates as follows: August 2010 - VPU04 February 2011 - VPUs 05, 06 June 2011 - VPU 17 August 2011 - VPUs 07, 10L, 10U, 11, 18 December 2011 - VPUs 01, 02, 03N, 03S, 03W, 08, 09, 12, 13, 14, 15, 16 The elevation characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents the land cover data within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the NLCD. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. This data set is derived from the NLCD raster composed of 16 land cover classes (categorical data type) for the conterminous USA. Four classes of the NLCD were excluded as they were specific to Alaska land covers. This raster was produced based on a decision-tree classification of 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 Landsat satellite data. This dataset will include additional years as they become available.