International Journal of Environment and Climate Change

This study investigates the relationship between above-ground biomass (AGB) and various vegetation indices in the tea plantations of Alipurduar District, West Bengal, India. The research was conducted in three major tea estates: Kumargram, Sankos and Newlands, using stratified random sampling across 36 plots. Field measurements of trees, shrubs and herbs were taken and AGB was estimated using allometric equations. Sentinel-2 satellite data was utilized to derive vegetation indices such as NDVI, GNDVI, SAVI, MSAVI, EVI-1, EVI-2, NDVI_RE, RDVI, DVI, OSAVI and ARVI. The study found significant variation in AGB, ranging from 31.40 Mg ha^-1 to 68.84 Mg ha^-1, with an average of 47.22 Mg ha^-1. Strong positive correlations were observed between AGB and indices like GNDVI (r=0.96) and EVI-2 (r=0.96), indicating their effectiveness in biomass prediction. The integration of remote sensing technologies enhances the scalability and precision of biomass estimation, providing valuable insights into the carbon storage potential and ecological health of tea plantations. These findings have implications for sustainable management and climate change mitigation in agroforestry systems.