PENDUGAAN POTENSI KARBON HUTAN DENGAN SISTEM PENGINDRAAN JAUH

Abstract

The relationship between remote sensing and biomass is that remote sensing is one of the best approaches for regional biomass estimation when forest stand data in the field are difficult to obtain. One used images satellite estimate forest carbon and biomass is the Landsat 8 OLI (Operational Land Imager) image with resolution of 30 meters. Study estimate potential tree carbon stored forest by using remote sensing system using Landsat 8 OLI satellite imagery. Regression analysis of actual biomass calculation using allometric equations developed lowland heterogeneous tropical forests with vegetation index NDVI (Normalized Difference Vegetation Index) and ARVI (Atmospherically Resistant Vegetation Index). Determination best of model by calculating the lowest standard error of estimation of each regression model by calculating carbon 50% from above-ground biomass. Estimation carbon potential in study area using linear regression model on the transformation the ARVI vegetation index (Y = 443.24 ln(X) + 576.93). The amount of biomass that The highest forest in the study area is 225.37 Ton/ha with the highest carbon potential of 112.69 Tons/ha. The forest carbon potential value obtained is classified into 5 classes using the Natural Breaks (Jenks) method facilitate at process estimating forest carbon potential so knowing distribution carbon of forest.