Detection of Individual Tree Crowns in Airborne Lidar Data

TLDR

Laser scanning is an effective method for gathering forest stand information. The study proposes an automated method to delineate individual trees in small‑footprint LiDAR data from deciduous and mixed temperate forests. The method rasterizes LiDAR data, identifies tree tops via a local maximum filter, then delineates crowns using a pouring algorithm with shape assumptions and vector‑based edge detection, and evaluates results against terrestrial and photogrammetric references. The algorithm performs well on coniferous stands but tends to merge crowns in dense deciduous forests.

Abstract

Laser scanning provides a good means to collect information on forest stands. This paper presents an approach to delineate single trees automatically in small footprint light detection and ranging (lidar) data in deciduous and mixed temperate forests. In rasterized laser data possible tree tops are detected with a local maximum filter. Afterwards the crowns are delineated with a combination of a pouring algorithm, knowledge-based assumptions on the shape of trees, and a final detection of the crown-edges by searching vectors starting from the trees’ tops. The segmentation results are assessed by comparison with terrestrial measured crown projections and with photogrammetrically delineated trees. The segmentation algorithm works well for coniferous stands. However, the implemented method tends to merge crowns in dense stands of deciduous trees.