Model for Estimating Above Ground Biomass of Reclamation Forest using Unmanned Aerial Vehicles

Abstract

Among various stand parameters, the density of biomass volume is oftenly used as an indicator on evaluating the forest growth succes. The forest reclamation, which is intended to restore the land cover by revegetation process, the evaluation of biomass content has been a critical issue. Forest reclamation is expected to restore the land function to a proper state that might give better environment as well as productivity. In this study the authors develop a method for estimating above ground biomass (AGB), particularly in the ex open-pit coal mining area of PT. Bukit Asam Tbk using remotely-sended data taken from unmanned aerial vehicle (UAV) and developed using the least squares method. The main objective of this study is to develop a mathematical model of biomass estimation using UAV imagery having 10-cm spatial resolution. The study found that the best model of biomass estimation is: AGB(ton/ha)=0.2377Ci^1.3688 with the correlation coefficient of 0.844, mean deviation of 2.29, aggregate deviation of -0.023, bias of 0.98, and Root Mean Square Error (RMSE) of 1.784 and mean deviation (MD) < 10% while Ci. This research concluded that UAV imagery could be used to estimate above ground biomass accurately.