APPROXIMATION OF VOLUME AND BRANCH SIZE DISTRIBUTION OF TREES FROM LASER SCANNER DATA
- 1Department of Mathematics, Tampere University of Technology P.O. Box 553, FI-33101 Tampere, Finland
- 2Remote Sensing and Photogrammetry, Finnish Geodetic Institute P.O.Box 15, FI-02431 Masala, Finland
Keywords: LIDAR, point cloud, trees, classification, size approximation, carbon cycle
Abstract. This paper presents an approach for automatically approximating the above-ground volume and branch size distribution of trees from dense terrestrial laser scanner produced point clouds. The approach is based on the assumption that the point cloud is a sample of a surface in 3D space and the surface is locally like a cylinder. The point cloud is covered with small neighborhoods which conform to the surface. Then the neighborhoods are characterized geometrically and these characterizations are used to classify the points into trunk, branch, and other points. Finally, proper subsets are determined for cylinder ﬁtting using geometric characterizations of the subsets.