Analysis of Vegetation Carbon Stock Using Remote Sensing In Penggaron Forest, Central Java Province

Abstract

Abstract Global warming is a climate problem due to the greenhouse effect so it must be anticipated from external factors in the form of carbon stocks from forest vegetation. Forest areas have an important role in maintaining carbon reserves so that they become a pillar of controlling carbon emissions, one of which is the Penggaron Forest in Ungaran City. The Penggaron Forest needs to be studied regarding estimates of carbon stock abundance so that the research carries out estimates using remote sensing data. The method in this research uses light use efficiency (LUE). The concept of this method estimates vegetation biomass based on 3 parameters such as the Normalized Difference Vegetation Index (NDVI) value to model the fraction of photosynthetic active radiation (fPAR), maximum efficiency of using sunlight, and photosynthetic active radiation (PAR). This research resulted in an estimate of the total carbon stock content in the Penggaron Forest of 3,049,515.14 KgC with a forest area of 9,183 km2. 46,921 cm. Accuracy testing was carried out for carbon stock modeling which obtained an RMSE value of 97.289 KgC. The carbon stock modeling estimation was carried out by the Pearson correlation test which obtained a correlation result of 0.0974.