3D model-based tree measurement from high-resolution aerial imagery

Abstract

This paper introduces a 3D model-based tree interpreter, a semi-automatic method for tree measurement from high-resolution aerial images. It emphasizes the extraction of the 3D geometric information such as tree location, tree height, crown depth (or crown height), crown radius, and surface curvature. First, trees are modeled as 3D hemi-ellipsoids with the following parameters: tree-top coordinates, trunk base height, crown depth, crown radius, and crown surface curvature. This model-based approach turns a tree interpretation task into a problem of optimal tree model determination. Multi-angular images are used to determine the optimal tree model for each tree. Tree tops in each image of a stereo pair are identified interactively with the epipolar constraint, and the 3D geometry of trees can be determined automatically. With such a semi-automatic scheme, efficiency and reliability of 3D tree measurements are achieved by taking advantages of both the operator's interpretation skills and the machine's computation. This paper mainly deals with conifers. The method was tested with a closed conifer stand on 1:2,400-scale photographs. An overall accuracy of 94 percent and 90 percent was obtained for tree height and crown radius measurements, respectively.