Airborne LiDAR for Estimating Aboveground Biomass in Dry Evergreen Forest : A Site of Khao Yai National Park, Thailand
Kanchana Nakapakorn, Treechai Anuwongjareon, and Sura Pattanakiat
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Abstract
The objective of this study was to utilize the advanced LiDAR technology and high resolution aerial photography in conjunction with an allometric and regression model to determine the value of coefficient of determination between the tree height estimated from LiDAR and fieldmeasurement. The study covered an area of 22.5 square kilometers of Khao Yai national park, in Hintang sub-district, meung Nakhorn Nayok district, Nakhon Nayok province, Thailand. The results of the study indicate that tree heights generated from LiDAR data can be used to calculate the diameter at breast height (DBH) using a regression model and to estimate the aboveground biomass using allometric equations for a dry evergreen forest. Through the results, we concluded that the aboveground biomass can be categorized into three levels: a high level (more than 1,000 kg of aboveground biomass) estimated for 36.8% of the study area, moderate level (500 1,000 kg of aboveground biomass) estimated for 23.4% of the study area, and low level (under 500 kg of aboveground biomass) estimated for 39.8% of the study area. Using the LiDAR and high resolution aerial photography, it is possible to estimate the aboveground biomass of the crown cover with a high level of accuracy in a real world setting. The results prove the potential of the LiDAR technique in accurately estimating the aboveground biomass of a multi-layerd and complex forest structure such as a dry evergreen forest in Khao Yai national park, as indicated by the prediction accuracy of the regression model . The authors must inform the RMSE and percentage of RMSE for aboveground biomass estimations.
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