Estimation of Stand-level Above Ground Biomass in Intact Tropical Rain Forests of Brunei using Airborne LiDAR data
- Authors
- Yoon, Mihae; Kim, Eunji; Kwak, Doo-Ahn; Lee, Woo-Kyun; Lee, Jong-Yeol; Kim, Moon-Il; Lee, Sohye; Son, Yowhan; Abu Salim, Kamariah
- Issue Date
- 4월-2015
- Publisher
- KOREAN SOC REMOTE SENSING
- Keywords
- Airborne LiDAR; Tropical Rain Forest; Above Ground Biomass
- Citation
- KOREAN JOURNAL OF REMOTE SENSING, v.31, no.2, pp.127 - 136
- Indexed
- KCI
- Journal Title
- KOREAN JOURNAL OF REMOTE SENSING
- Volume
- 31
- Number
- 2
- Start Page
- 127
- End Page
- 136
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/94055
- DOI
- 10.7780/kjrs.2015.31.2.7
- ISSN
- 1225-6161
- Abstract
- This study aims to quantify the stand-level above ground biomass in intact tropical rain forest of Brunei using airborne LiDAR data. Twenty four sub-plots with the size of 0.09ha (30 mx30 m) were located in the 25ha study area along the altitudinal gradients. Field investigated data (Diameter at Breast Height (DBH) and individual tree position data) in sub-plots were used. Digital Surface Model (DSM), Digital Terrain Model (DTM) and Canopy Height Model (CHM) were constructed using airborne LiDAR data. CHM was divided into 24 sub-plots and 12 LiDAR height metrics were built. Multiple regression equation between the variables extracted from the LiDAR data and biomass calculated by using a allometric equation was derived. Stand-level biomass estimated from LiDAR data were distributed from 155.81 Mg/ha to 597.21 Mg/ha with the mean value of 366.48 Mg/ha. R-square value of the verification analysis was 0.84.
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Collections - College of Life Sciences and Biotechnology > Division of Environmental Science and Ecological Engineering > 1. Journal Articles
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