Above Ground Forest Biomass Estimation Using Sentinel-2 Data in the Upper Blue Nile Basin, North-Western Ethiopia

Abstract

Forest biomass plays a decisive role in the global climatic condition. Therefore, rapid and accurate estimation of forest biomass is crucial for greatly reducing the uncertainty in carbon stock assessments, and for designing strategic forest management plans. Because, forest above-ground biomass (AGB) estimation is important in determining the management, environmental, and economic roles of forests in the Blue Nile basin. This study aimed to estimate forest above-ground biomass in the Upper Blue Nile Basin by integrating field-measured data with observations from Sentinel-2. Therefore, the first correlation between measured forest AGB and derived vegetation indices and biophysical parameters was investigated. A stepwise regression analysis was carried out to estimate forest AGB. The maximum forest AGB value of 268.32 t/ha was estimated in the Alemsaga natural forest. Green normalized difference vegetation index, leaf area index, fraction of absorbed photosynthetic active radiation, and fractional vegetation cover achieved moderate performance in predicting AGB with R² value > 0.5. Forest AGB was estimated with a coefficient of determination (R²) of 0.59, an adjusted R² of 0.618, and a root mean square error (RMSE) of 38.36 t/ha in comparison to field observations.