Estimation of carbon dioxide stocks in forest using airborne LiDAR data

Sang Jin Lee, Yun Soo Choi, Ha Su Yoon

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish
Pages (from-to)259-268
Number of pages10
JournalJournal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
Issue number3
StatePublished - 2012


  • Biomass
  • Carbon dioxide stocks
  • Digital terrain modeling
  • Individual tree detection
  • LiDAR Filtering


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