Vatandaşlar, CanLee, TaeyoonPeduzzi, AliciaBettinger, PeteMerry, KristaStober, Jonathan2025-07-252025-07-252023979-835032010-7https://hdl.handle.net/11494/5888Accurate knowledge of ecological condition (EC) is crucial to evaluate the deviation of a given ecosystem from a reference condition, and is of interest to forest managers as it helps them prioritize management activities. The present study aimed to estimate EC classes of the Talladega National Forest (NF) using NAIP images, and airborne laser scanning (ALS) data, as well as field measurements from 255 plots. The results indicated that the EC classes could be distinguished using zq25, imean, and p5th metrics from ALS, as well as Enhanced Vegetation Index. Among them, we used zq25 to generate a map for the entire study area. Accordingly, the dominant EC was class 3, suggesting that almost half of the forestland is composed of young and dense stands with woody understory. This cover type is not desirable in terms of wildfire risk and far from the historical conditions. Thus, NF managers might thin and/or prescribed burn these areas to improve EC.eninfo:eu-repo/semantics/embargoedAccessAirborne laser scanningLand managementLiDAR metricsPrescribed firesVegetation indexConference Object20232676267910.1109/IGARSS52108.2023.102815922-s2.0-85178383561Q3