ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Download
Citation
Articles | Volume I-3
https://doi.org/10.5194/isprsannals-I-3-129-2012
https://doi.org/10.5194/isprsannals-I-3-129-2012
20 Jul 2012
 | 20 Jul 2012

A COMPARITIVE STUDY USING GEOMETRIC AND VERTICAL PROFILE FEATURES DERIVED FROM AIRBORNE LIDAR FOR CLASSIFYING TREE GENERA

C. Ko, G. Sohn, and T. K. Remmel

Keywords: LiDAR, tree genera, classification, Random Forest, feature selection, vertical profile

Abstract. We present a comparative study between two different approaches for tree genera classification using descriptors derived from tree geometry and those derived from the vertical profile analysis of LiDAR point data. The different methods provide two perspectives for processing LiDAR point clouds for tree genera identification. The geometric perspective analyzes individual tree crowns in relation to valuable information related to characteristics of clusters and line segments derived within crowns and overall tree shapes to highlight the spatial distribution of LiDAR points within the crown. Conversely, analyzing vertical profiles retrieves information about the point distributions with respect to height percentiles; this perspective emphasizes of the importance that point distributions at specific heights express, accommodating for the decreased point density with respect to depth of canopy penetration by LiDAR pulses. The targeted species include white birch, maple, oak, poplar, white pine and jack pine at a study site northeast of Sault Ste. Marie, Ontario, Canada.