Estimating number of trees, tree height and crown width using Lidar data

Abstract

Estimating tree characteristics with field plots located in remote and inaccessible areas can be a costly and timely endeavor. Light Detection and Ranging (Lidar) remote sensing allowing for the estimation of the 3-dimensional structure of forest vegetation offers an alternative to traditional ground based forest measurements. This project assessed the utility of using Lidar data to estimate number of trees, tree height and crown width within Barksdale Air Force Base forest management area, Bossier City, Louisiana. Two programs, Lidar Data Filtering and Forest Studies (Tiffs) and Lidar Analyst were used to derive forest measurements, which were compared to field measurements. Based on Root Mean Square Error (RMSE), Lidar Analyst (3.81 trees) performed better than Tiffs (5.71 trees) at estimating average tree count per plot. Tiffs was better at deriving average tree height than Lidar Analyst with an RMSE of 19.08 feet to Lidar Analyst’s RMSE of 21.20 feet. Lidar Analyst, with a RMSE of 25.41 feet, was better in deriving average crown diameter over Tiffs RMSE of 30.54 feet. All linear correlation coefficients between average field measured tree height and Lidar derived average tree height were highly significant at the 0.01 probability level for both Tiffs and Lidar Analyst on hardwood, conifers and a combined hardwood-conifer comparison.