Raster surfaces created from the cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data project
dataset
posted on 2024-09-13, 16:22authored byJohn S. Hogland, Joseph R. St. Peter, Nathaniel M. Anderson
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. Intended use for these datasets include: helping quantify existing conditions of forested ecosystems and helping to prioritize Longleaf restoration efforts across four significant geographic areas described in America’s Longleaf Range-wide Conservation Plan for Longleaf (2009). Original metadata date is 03/06/2017. Minor metadata updates made on 9/14/2018 and 07/02/2019.
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:
Hogland, John S.; St. Peter, Joseph R.; Anderson, Nathaniel M. 2017. Raster surfaces created from the longleaf mapping project. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2017-0014