Isolating Individual Trees in a Savanna Woodland Using Small Footprint Lidar Data

Abstract

This study presents a new method of detecting individual treetops from lidar data and applies marker-controlled watershed segmentation into isolating individual trees in savanna woodland. The treetops were detected by searching local maxima in a canopy maxima model (CMM) with variable window sizes. Different from previous methods, the variable windows sizes were determined by the lower-limit of the prediction intervals of the regression curve between crown size and tree height. The canopy maxima model was created to reduce the commission errors of treetop detection. Treetops were also detected based on the fact that they are typically located around the center of crowns. The tree delineation accuracy was evaluated by a five-fold, cross-validation method. Results showed that the absolute accuracy of tree isolation was 64.1 percent, which was much higher than the accuracy of the method, which only searched local maxima within window sizes determined by the regression curve (37.0 percent).