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Automatic Extraction of Individual Tree Height in Mountainous Forest Using Airborne Lidar Data  

Woo, Choong-Shik (Department of Geoinformatic Engineering Inha University)
Yoon, Jong-Suk (Department of Geoinformatic Engineering Inha University)
Shin, Jung-Il (Department of Geoinformatic Engineering Inha University)
Lee, Kyu-Sung (Department of Geoinformatic Engineering Inha University)
Publication Information
Journal of Korean Society of Forest Science / v.96, no.3, 2007 , pp. 251-258 More about this Journal
Abstract
Airborne Lidar (light detection and ranging) can be an effective alternative in forest inventory to overcome the limitations of conventional field survey and aerial photo interpretation. In this study, we attempt to develop methodologies to identify individual trees and to estimate tree height from airborne Lidar data. Initially, digital elevation model (DEM) data representing the exact ground surface were generated by removing non-ground returns from the multiple-return laser point clouds, obtained over the coniferous forest site of rugged terrain. Based on the canopy height model (CHM) data representing non-ground layer, individual tree heights are extracted through pseudo-grid method and moving window filtering algorithm. Comparing with field survey data and aerial photo interpretation on sample plots, the number of trees extracted from Lidar data show over 90% accuracy and tree heights were underestimated within 1.1m in average at two plantation stands of pine (Pinus koraiensis) and larch (Larix leptolepis).
Keywords
Lidar; forest measurement; tree height; moving window filtering; DEM;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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