Estimation of Forest Carbon Stock using LiDAR Data in Intact Tropical Rain Forest

Abstract:

Forest biomass has been recognized as an important indicator of carbon sequestration. However, field measurement of individual tree biomass is time-consuming, requires intensive labor, and is rather expensive, especially for tropical rain forest. As an alternative of this issue, application of remote sensing techniques to forest carbon quantification is essential. In this study, the plot biomass was predicted using LiDAR data and field measurements. The study area is located in Kuala Belalong Field Studies Centre (KBFSC), Brunei Temburong. KBFSC covers 25 ha native tropical rain forest and is consisted of mixed Dipterocarp. This study set total 54 plots (20m X 20m) in forest dynamics plot. The scheme of this study was as follows: 1) Calculate the plot biomass using field measurements, 2) Estimate the plot biomass using LiDAR data and field measurement, 3) Verify accuracy. The derived plot average biomass of LiDAR and field measurement were 376.16 Mg ha-1 and 391.85 Mg ha-1, respectively. This study focused on estimating forest biomass and it was converted to carbon stocks using carbon fraction. The result of this study is expected to be applied in decision making climate change adaptation policies.