Estimation above Ground Biomass of Private Forest Using Sentinel-1 and Sentinel-2 Satellite data (A Case Study in Gunung Kidul, Yogyakarta, Indonesia)

Abstract

Private forest has crucial role in maintaining the functioning of Indonesian forest ecosystem especially the continuous degradation of natural forest. Private forest is a part of social forestry which becomes a tool for the Indonesian government to reduce Carbon dioxide (CO2) emission by 26% by 2030. The Reduction Emission Degradation and Deforestation (REDD) scheme has encouraged the Indonesian government to establish forest monitoring system by estimating forest carbon stock using a combination of forest inventory and remote sensing. This study aimed to assess potential Sentinel-1 and Sentinel-2 for estimating Above Ground Biomass (AGB) of private forest. We found that gamma VH delivered from sentinel-1 had significant correlation with AGB whereas parameters from sentinel-2 which had significant correlation with AGB were B3, B4, NDI45, NDVI, SR, IRECI, EVI and NDI75. Combination between NDI45 and EVI through Stepwise linear regression fitted for establishing model between field AGB and vegetation indices (R2 = 0.81). We also found that the AGB in the study area based on spatial analysis was 72.54 ton/ha. A Root Mean Square Error (RMSE) value from predicted and observed AGB was 27 ton/ha. AGB in private forest is categorized into moderate class due to behavior of the farmers to cut the forest in particular time. Overall, vegetation indices more superior than spectral value and radar backscatter to assess AGB in private forest.