Active contour and hill climbing for tree crown detection and delineation

This paper presents a new approach for individual tree crown detection and delineation that is applicable under various imaging conditions. The approach extracts crown area using a region-based active contour model and then detects tree tops within the crown area by considering both spectral and shape characteristics of the crown. The detected tree tops allow subsequent clustering of crown pixels using a new hill-climbing algorithm. We tested the approach on a Norway spruce stand using three types of high spatial resolution imagery: an Emerge natural color vertical aerial image, an off-nadir QuickBird panchromatic image, and a natural color digital orthoimage. In comparison to the published region growing algorithm, our approach improved tree crown detection by over 10 percent for all three types of imagery, and provided accurate tree crown diameter estimation, which has utility in tree volume estimation, species composition, and forest health analysis.