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Maximum Canopy Height Estimation Using ICESat GLAS Laser Altimetry
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  • Maximum Canopy Height Estimation Using ICESat GLAS Laser Altimetry
  • Maximum Canopy Height Estimation Using ICESat GLAS Laser Altimetry
저자명
Park. Tae-Jin,Lee. Woo-Kyun,Lee. Jong-Yeol,Hayashi. Masato,Tang. Yanhong,Kwak. Doo-Ahn,Kwak. Han-Bin,Kim. Moon-Il,Cui. Guishan,N
간행물명
大韓遠隔探査學會誌
권/호정보
2012년|28권 3호|pp.307-318 (12 pages)
발행정보
대한원격탐사학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

To understand forest structures, the Geoscience Laser Altimeter System (GLAS) instrument have been employed to measure and monitor forest canopy with feasibility of acquiring three dimensional canopy structure information. This study tried to examine the potential of GLAS dataset in measuring forest canopy structures, particularly maximum canopy height estimation. To estimate maximum canopy height using feasible GLAS dataset, we simply used difference between signal start and ground peak derived from Gaussian decomposition method. After estimation procedure, maximum canopy height was derived from airborne Light Detection and Ranging (LiDAR) data and it was applied to evaluate the accuracy of that of GLAS estimation. In addition, several influences, such as topographical and biophysical factors, were analyzed and discussed to explain error sources of direct maximum canopy height estimation using GLAS data. In the result of estimation using direct method, a root mean square error (RMSE) was estimated at 8.15 m. The estimation tended to be overestimated when comparing to derivations of airborne LiDAR. According to the result of error occurrences analysis, we need to consider these error sources, particularly terrain slope within GLAS footprint, and to apply statistical regression approach based on various parameters from a Gaussian decomposition for accurate and reliable maximum canopy height estimation.