Use of LiDAR and supplemental data to estimate forest maturity in Charles County, MD, USA

This study evaluated the utility of remotely sensed data to estimate forest maturity within Charles County, MD. We calculated tree canopy height using airborne scanning LiDAR (light detection and ranging) data over the entire county, and compared this to crown top height, stand age, and other data collected from randomly selected plots on the ground. Canopy height was a strong predictor of forest age, and we improved predictive power by including other variables such as land cover, slope, stream proximity, wetlands, and floodplains. These comparisons allowed us to construct a spatial model classifying forest in the study area into three age categories: ≤30 years old, 30–70 years old, and >70 years old, corresponding to young, intermediate, and mature. This spatial model was used to help characterize ecosystem condition and wildlife habitat, and help prioritize conservation decisions in the study area.