Individual tree segmentation in deciduous forests using geodesic voting

摘要

Airborne Laser Scanning (ALS) has been widely used to survey forest areas. The extraction (segmentation) of individual trees from ALS point clouds is a prerequisite step for tree biophysical parameter estimation. For this purpose, we develop and evaluate a graph based segmentation algorithm adapted to deciduous forests scanned with high density LiDAR (~50 points / m) in leaf-off conditions. The algorithm is applied to a 1 ha deciduous forest plot in western Switzerland and the accuracy of individual trunk locations is evaluated in terms of recall, precision and F-score. The results indicate that the algorithm performs satisfactorily within the experimental setup conditions.