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http://dx.doi.org/10.7848/ksgpc.2012.30.3.259

Estimation of Carbon Dioxide Stocks in Forest Using Airborne LiDAR Data  

Lee, Sang-Jin (서울시립대학교 도시과학대학 공간정보공학과)
Choi, Yun-Soo (서울시립대학교 도시과학대학 공간정보공학과)
Yoon, Ha-Su (서울시립대학교 도시과학대학 공간정보공학과)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.30, no.3, 2012 , pp. 259-268 More about this Journal
Abstract
This paper aims to estimate the carbon dioxide stocks in forests using airborne LiDAR data with a density of approximate 4.4 points per meter square. To achieve this goal, a processing chain consisting of bare earth Digital Terrain Model(DTM) extraction and individual tree top detection has been developed. As results of this experiment, the reliable DTM with type-II errors of 3.32% and tree positions with overall accuracy of 66.26% were extracted in the study area. The total estimated carbon dioxide stocks in the study area using extracted 3-D forests structures well suited with the traditional method by field measurements upto 7.2% error level. This results showed that LiDAR technology is highly valuable for replacing the existing forest resources inventory.
Keywords
LiDAR Filtering; Digital terrain modeling; Individual tree detection; Biomass; Carbon dioxide stocks;
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