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The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) lake catchments and watersheds for the Conterminous United States: Wildland Fire Perimeters By Year 2000 - 2010
OwnerUnited State Environmental Protection Agency - view all
Update frequencyunknown
Last updatedabout 1 year ago
Format
Overview

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.

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Additional Information
KeyValue
dcat_issued2015-04-23
dcat_modified2015-01-01
dcat_publisher_nameUS EPA Office of Research and Development (ORD) - National Health and Environmental Effects Research Laboratory (NHEERL)
guid{7988E3BC-FD77-47F6-B098-77A686C55B7F}
ib1_trust_framework[]
languageen-US
Files
  • API
    69e1d291-8e21-45f8-9c04-d14563e43460
  • a96c1b78-7619-463d-b6c3-0855fcf3169d
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