ESTIMATING ABOVE-GROUND BIOMASS OF AGROFORESTRY TREE SPECIES IN BHADADRI KOTHAGUDEM DISTRICT, TELANGANA, INDIA, USING SENTINEL-2 SATELLITE DATA

This study investigates the relationship between Above Ground Biomass (AGB) and Vegetation Indices (VIs) derived from Sentinel-2 satellite data for Eucalyptus, Subabul and Oil palm-based agroforestry systems (AFS) in Bhadradri Kothagudem District, Telangana state, India.Field measurements were collected and above-ground biomass (AGB) was estimated using allometric equations.The vegetation indices derived for this study area were Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI) and Modified Soil Adjusted Vegetation Index (MSAVI).In this study, Linear regression model was fitted to establish the relationship between AGB and VIs.Among the VIs, strongest positive correlation was observed for EVI with correlation coefficient (r) of 0.94 and coefficient of determination (R 2 ) value of 0.88 compared to another VIs.The mean AGB estimated for Eucalyptus (3years old) was 42 t ha -1 , Subabul (3 years old) was 66 t ha -1 and Oil palm (up to 21 years) was 152 t ha -1 for the study area.The lowest Root mean square error (RMSE) value from predicted and observed AGB was 24 t ha -1 for EVI.Thus, it was concluded that the Enhanced Vegetation Index (EVI) is the most suitable index for estimating the above-ground biomass (AGB) of Eucalyptus, Subabul, and Oil Palm-based agroforestry systems.The yield model developed incorporating EVI was utilized to estimate the AGB of these species in this study.