Orchard Classification from Satellite Image Data using Fuzzy K-mean to Estimate of Carbon Sequestration

摘要

The aim of the study is to estimate carbon sequestration in terms of above-ground biomass (AGB) within the orchard or perennial tree from the high resolution image. The objective of this study is to classify the land use from the Sentinel-2 image data for estimating the AGB by using the vegetation indices consists: normalization difference vegetation index (NDVI) and ratio vegetation index (RVI). The fuzzy k-mean was applied to classify the land use divide into 6 classes. The orchard or perennial (OP) from the classified was to estimated the AGB value by using the spatial analysis based on regression model. The results of land use classified show that the overall accuracy and the kappa coefficient was 88%, and 0.65, respectively. The regression equation for estimated of the AGB value using vegetation indices, the regression equation was the y=(27.23*NDVI)+(-3.21*RVI) with coefficient of determination R~2 = 0.71. The calculate of the AGB in the orchard or perennial tree from the classified was 14769.93 tCO2e.