Raster surfaces created from the cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data project

This data publication contains twenty-four GeoTIFF files for four significant geographic areas (SGAs) in Alabama, Florida, and Georgia. The extent of the SGAs are defined within the America's Longleaf Range-wide Conservation Plan for Longleaf (2009). A raster grid file is provided for the extent of each SGA within each state and shows the amount of pine basal area per acre (BAA), the amount of all species BAA, the amount of pine trees per acre (TPA), the amount of all species TPA, dominant forest type classification, visually identified classification, the probability of an area being composed primarily of longleaf pine BAA, and the probability of an area being composed primarily of regeneration. These raster surfaces were created using machine learning relationships between FIA plot information (2010-2015) and NAIP imagery (2013) and are intended to be used to help quantify existing conditions of forested ecosystems and help prioritize longleaf restoration efforts across the four SGAs.

Data and Resources

Field Value
accessLevel public
bureauCode {005:96}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
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catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier https://www.arcgis.com/home/item.html?id=692c0135dab146499d8f17837971a2ef
issued 2018-04-26
landingPage https://data-usfs.hub.arcgis.com/documents/usfs::raster-surfaces-created-from-the-cost-effective-mapping-of-longleaf-extent-and-condition-using-naip-imagery-and-fia-data-project
license https://creativecommons.org/licenses/by/4.0/
metadata_type geospatial
modified 2022-08-29
old-spatial -131.3620,6.8980,-65.6380,72.6220
programCode {005:059}
progressCode onGoing
publisher U.S. Forest Service
resource-type Dataset
source_datajson_identifier true
source_hash b4902e89defc0ced6cfdc7b6d99d419f310902a8741148b2ac7acd5f4ded33b0
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-131.3620, 6.8980], [-131.3620, 72.6220], [-65.6380, 72.6220], [-65.6380, 6.8980], [-131.3620, 6.8980]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • alabama
  • analysis
  • biota
  • florida
  • forest-plant-health
  • georgia
  • inventory
  • longleaf
  • mapping
  • monitoring
  • multiple-species
  • natural-resource-management-use
  • open-data
  • plants
  • prioritization
  • rda
  • restoration
  • wildlife
isopen True
license_id cc-by
license_title Creative Commons Attribution
license_url http://www.opendefinition.org/licenses/cc-by
maintainer USFSEnterpriseContent
maintainer_email SM.FS.data@usda.gov
metadata_created 2025-09-23T15:39:25.487479
metadata_modified 2025-09-23T15:39:25.487486
notes This data publication contains twenty-four GeoTIFF files for four significant geographic areas (SGAs) in Alabama, Florida, and Georgia. The extent of the SGAs are defined within the America's Longleaf Range-wide Conservation Plan for Longleaf (2009). A raster grid file is provided for the extent of each SGA within each state and shows the amount of pine basal area per acre (BAA), the amount of all species BAA, the amount of pine trees per acre (TPA), the amount of all species TPA, dominant forest type classification, visually identified classification, the probability of an area being composed primarily of longleaf pine BAA, and the probability of an area being composed primarily of regeneration. These raster surfaces were created using machine learning relationships between FIA plot information (2010-2015) and NAIP imagery (2013) and are intended to be used to help quantify existing conditions of forested ecosystems and help prioritize longleaf restoration efforts across the four SGAs.
num_resources 3
num_tags 26
title Raster surfaces created from the cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data project