PENDUGAAN POTENSI BIOMASSAVEGETASI MENGGUNAKAN INDEKS ARVI PADA CITRA SENTINEL2A DI KAWASAN HUTAN PRODUKSITERBATAS DESA SEJAHTERA

This study was carried out to develop a suitable biomass estimation model for dryland forests in Production Forest areas. The research took place from February to April 2025 in the Limited Production Forest area of Sejahtera Village, Palolo District, Sigi Regency. Observation plots measuring 10 m × 10 m were determined based on ARVI value classification from Sentinel-2A image processing, grouped into three vegetation density classes: sparse, medium, and dense. Each class consisted of 15 plots, making a total of 45 observation plots. Field data were collected by measuring the tree diameter at breast height, and biomass was then calculated using the appropriate allometric equations. Next, the data was analyzed using exponential nonlinear regression to find out the relationship between biomass and ARVI values and to develop a biomass estimation model. The study results showed that the Limited Production Forest area in Sejahtera Village is dominated by dense vegetation based on ARVI values. Biomass in the 45 observation plots ranged from 81.41 to 10,219.48 kg per tree and was more influenced by stem diameter (DBH) than ARVI values. Regression analysis indicated that the relationship between ARVI and biomass is still weak, so even though the linear model was chosen as the best model, ARVI needs to be combined with other biophysical variables to improve biomass estimation accuracy.