Using feature analyst & NAIP imagery to conduct a statewide tree canopy assessment of Georgia

Abstract

Background: A collaboration between agencies to conduct a statewide canopy assessment of Georgia was formed in order to develop a baseline dataset from 2015 NAIP imagery to be used as comparison to archival data and future data analysis to measure canopy growth/loss over time. Using Feature Analyst software, analysts processed the imagery running a minimum of 1 iteration on each tile, checking for accuracy at 70% or higher. If under 70% accuracy, up to 4 additional iterations were conducted until accuracy confirmed for some tiles at 90%. Random point checking was conducted by field foresters to confirm accuracy of the binary: canopy/no canopy. Due to size of the imagery on a statewide scale, the state was divided into 24 physiographic regions as specified by the Department of Natural Resources and then into 269 tiles to create manageable data files. This article will summarize the process for analyzing imagery to generate a statewide canopy assessment and recommend ways in which to use the results to manage forestry resources or to conduct further comparative analysis.