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What is Estimating Grassland Biomass with Sentinel-2 about?

This study investigates the estimation of aboveground biomass (AGB) in grasslands of the Shengjin Lake wetland using Sentinel-2 MSI data and ensemble algorithms, specifically random forest (RF) and extreme gradient boosting (XGBoost). The results demonstrate that both models effectively estimate AGB, with XGBoost showing superior performance, and the incorporation of texture features significantly enhances estimation accuracy. The findings highlight the potential of using Sentinel-2 data for sustainable man

Author

Dwiputra Ahmad Ramdani

Language

EN