Isolating individual trees in a closed coniferous forest using small footprint lidar data

Abstract

Numerous individual tree parameters can be isolated from a canopy height model derived from light detection and ranging. However, closed canopy forests make isolating individual trees difficult. A watershed method based on morphological crown control is studied in this research to isolate individual trees in a closed canopy forest and find how much the tree density influences the individual tree parameters. Morphological crown control is introduced to ensure that the watershed results locate in the crown area. The local maxima algorithm is used to identify potential tree positions in the crown area. Double watershed transformations, in which a simple reconstruction operation is inserted into the two transformations, are then applied to delineate the tree crowns. Finally, the individual trees are isolated, and their parameters are extracted. An experiment is conducted in a closed coniferous forest dominated by Picea crassifolia Kom. in northwest China. Results show that the proposed method can isolate the most dominant and subdominant trees, more than half of the intermediate trees and some suppressed trees.