Other Forestry and Forest Sciences Commons^™

Using Landsat-Based Phenology Metrics, Terrain Variables, And Machine Learning For Mapping And Probabilistic Prediction Of Forest Community Types In West Virginia, Faith M. Hartley

Graduate Theses, Dissertations, and Problem Reports

This study investigates the mapping of forest community types for the entire state of West Virginia, USA using Global Land Analysis and Discovery (GLAD) Phenology Metrics analysis ready data (ARD) derived from the Landsat time series and digital terrain variables derived from a digital terrain model (DTM). Both classifications and probabilistic predictions were made using random forest (RF) machine learning (ML) and training data derived from ground plots provided by the West Virginia Natural Heritage Program (WVNHP). The primary goal of this study is to explore the use of globally consistent ARD data for operational forest type mapping over a …