LANDFIRE 2023 Existing Vegetation Cover (EVC) Puerto Rico US Virgin Islands

Description

LANDFIRE's (LF) 2023 update (LF 2023) 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 lifeform of each pixel. The EVC product is then reconciled through QA/QC measures to ensure lifeform is synchronized with Existing Vegetation Height (EVH). In LF 2023 Conterminous United States (CONUS) extent, LF will map the lifeform, cover, and height of existing vegetation in areas that were mapped as disturbed over the last twenty years (see LF Annual Disturbance products) using machine learning methods. These disturbed areas were the focus because they are the areas that have changed the most since LF 2016 Remap. To learn more about this new methodology for LF EVC, EVH, and Existing Vegetation Type (EVT) go to https://landfire.gov/data/lf2023.

Resources

Name Format Description Link
55 The metadata original format https://data.usgs.gov/datacatalog/metadata/USGS.673f65b3d34e565ca5dd0a54.xml
55 Landing page for access to the data https://doi.org/10.5066/P9BJP7OV

Tags

  • u-s-geological-survey-usgs
  • puerto-rico
  • insular-areas
  • biota
  • landfire-2023
  • image-collections
  • us-virgin-islands
  • united-states
  • fires
  • ia
  • lf-2023
  • raster-digital-data
  • geospatial-datasets
  • hazard-preparedness
  • existing-vegetation-cover
  • evc
  • us
  • geographic-information-systems
  • remote-sensing
  • usgs-673f65b3d34e565ca5dd0a54
  • oconus
  • u-s-forest-service-usfs
  • imagerybasemapsearthcover

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