作者: Doo-Ahn Kwak , Woo-Kyun Lee , Hyun-Kook Cho , Seung-Ho Lee , Yowhan Son
DOI: 10.1007/S10265-010-0310-0
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摘要: The objective of this study was to estimate the stem volume and biomass individual trees using crown geometric (CGV), which extracted from small-footprint light detection ranging (LiDAR) data. Attempts were made analyze Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes tree density: low (240 N/ha), medium (370 N/ha), high (1,340 N/ha). To delineate trees, extended maxima transformation watershed segmentation image processing methods applied, as in one our previous studies. As next step, base height (CBH) has be determined; information found LiDAR point cloud data k-means clustering. LiDAR-derived CGV can estimated on basis proportional relationship between volume. a result, tree-density plots had best performance CBH, CGV, (R 2 = 0.67, 0.57, 0.68, respectively) accuracy lowest 2 = 0.48, 0.36, 0.44, respectively). In case R 2 = 0.51, 0.52, 0.62, respectively. predicted wood basic density coniferous (0.48 g/cm3), above-ground then conversion expansion factors (BCEF, 1.29) proposed by Korea Forest Research Institute (KFRI).