Assessing the influence of return density on estimation of lidar-based aboveground biomass in tropical peat swamp forests of Kalimantan, Indonesia

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• 作者：Solichin Manuri^a ; ^{solichin.solichin@anu.edu.au} ; ^{solichin.manuri@gmail.com} ; Hans-Erik Andersen^b ; ^{handersen@fs.fed.us} ; Robert J. McGaughey^b ; Cris Brack^a
• 关键词：Airborne lidar ; Aboveground biomass ; Return proportion metric ; Digital terrain model ; Model regression ; Model-based inference
• 刊名：International Journal of Applied Earth Observation and Geoinformation
• 出版年：2017
• 出版时间：April 2017
• 年：2017
• 卷：56
• 期：Complete
• 页码：24-35
• 全文大小：4845 K
• 卷排序：56

文摘

Cumulative return proportion variables have strong relationship with forest metrics. Low-density ALS is a feasible option for assessing AGB in vast areas of lowland PSF. Models of 1/4 return per m2 data yield good agreement with high-density lidar models. High-resolution DTM had little effect on the lidar metric accuracy in lowland PSF. Estimated mean AGB using 1/49 density yields good accuracy with SE <15%.