TY - JOUR
T1 - Estimating stem volume and biomass of Pinus koraiensis using LiDAR data
AU - Kwak, Doo Ahn
AU - Lee, Woo Kyun
AU - Cho, Hyun Kook
AU - Lee, Seung Ho
AU - Son, Yowhan
AU - Kafatos, Menas
AU - Kim, So Ra
N1 - Funding Information:
Acknowledgment This study was carried out with the support of ‘‘Forest Science and Technology Projects (Project No. S120909L010130)’’ provided by Korea Forest Service.
PY - 2010
Y1 - 2010
N2 - The objective of this study was to estimate the stem volume and biomass of individual trees using the crown geometric volume (CGV), which was extracted from small-footprint light detection and ranging (LiDAR) data. Attempts were made to analyze the stem volume and biomass of Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes of tree density: low (240 N/ha), medium (370 N/ha), and high (1,340 N/ha). To delineate individual trees, extended maxima transformation and watershed segmentation of image processing methods were applied, as in one of our previous studies. As the next step, the crown base height (CBH) of individual trees has to be determined; information for this was found in the LiDAR point cloud data using k-means clustering. The LiDAR-derived CGV and stem volume can be estimated on the basis of the proportional relationship between the CGV and stem volume. As a result, low tree-density plots had the best performance for LiDAR-derived CBH, CGV, and stem volume (R2 = 0.67, 0.57, and 0.68, respectively) and accuracy was lowest for high tree-density plots (R2 = 0.48, 0.36, and 0.44, respectively). In the case of medium tree-density plots accuracy was R2 = 0.51, 0.52, and 0.62, respectively. The LiDAR-derived stem biomass can be predicted from the stem volume using the wood basic density of coniferous trees (0.48 g/cm3), and the LiDAR-derived above-ground biomass can then be estimated from the stem volume using the biomass conversion and expansion factors (BCEF, 1.29) proposed by the Korea Forest Research Institute (KFRI).
AB - The objective of this study was to estimate the stem volume and biomass of individual trees using the crown geometric volume (CGV), which was extracted from small-footprint light detection and ranging (LiDAR) data. Attempts were made to analyze the stem volume and biomass of Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes of tree density: low (240 N/ha), medium (370 N/ha), and high (1,340 N/ha). To delineate individual trees, extended maxima transformation and watershed segmentation of image processing methods were applied, as in one of our previous studies. As the next step, the crown base height (CBH) of individual trees has to be determined; information for this was found in the LiDAR point cloud data using k-means clustering. The LiDAR-derived CGV and stem volume can be estimated on the basis of the proportional relationship between the CGV and stem volume. As a result, low tree-density plots had the best performance for LiDAR-derived CBH, CGV, and stem volume (R2 = 0.67, 0.57, and 0.68, respectively) and accuracy was lowest for high tree-density plots (R2 = 0.48, 0.36, and 0.44, respectively). In the case of medium tree-density plots accuracy was R2 = 0.51, 0.52, and 0.62, respectively. The LiDAR-derived stem biomass can be predicted from the stem volume using the wood basic density of coniferous trees (0.48 g/cm3), and the LiDAR-derived above-ground biomass can then be estimated from the stem volume using the biomass conversion and expansion factors (BCEF, 1.29) proposed by the Korea Forest Research Institute (KFRI).
KW - Above-ground biomass
KW - Crown base height
KW - Crown geometric volume
KW - K-means clustering
KW - LiDAR
KW - Stem volume
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U2 - 10.1007/s10265-010-0310-0
DO - 10.1007/s10265-010-0310-0
M3 - Article
C2 - 20182905
AN - SCOPUS:77953961040
VL - 123
SP - 421
EP - 432
JO - Journal of Plant Research
JF - Journal of Plant Research
SN - 0918-9440
IS - 4
ER -