$R^{2}$ of 0.747 and a root mean square error (RMSE) of 0.128. It preserved consistency with the spatial and temporal patterns of the original GLASS FVC while providing a more detailed representation of surface vegetation. Compared to existing FVC products (MultiVI 30-m, HXPT 250-m, MODIS 250-m, and GLASS 500-m), GFVC30 demonstrated superior spatial and temporal consistency, and better captured vegetation heterogeneity. This product enables refined and reliable vegetation monitoring over long time periods and broad geographic areas, supporting ecological assessment and climate response analysis from regional landscapes to localized communities. Overall, this study provides a robust and generalizable solution for producing fine-resolution, long-term FVC products to advance vegetation research and environmental monitoring.">

A Long-Term 30-m Fractional Vegetation Cover Dataset Downscaled From GLASS Products: Advancing Vegetation Monitoring at High Spatial Resolution (original) (raw)

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