Advancing the mapping of vegetation structure in savannas using Sentinel-1 imagery

Vegetation structure monitoring is important for the understanding and conservation of savanna ecosystems. Optical satellite imagery can be used to estimate canopy cover, but provides limited information about the structure of savannas, and is restricted to daytime and clear-sky captures. Active remote sensing can potentially overcome this. We explore the utility of C-band synthetic aperture radar imagery for mapping both grassland and woody vegetation structure in savannas. We calibrated Sentinel-1 VH (σ0 vh) and VV (σ0 vv) backscatter coefficients and their ratio (σ0 vh=σ0 vv) to ground-based estimates of grass biomass, woody canopy volume (\50 000 m3 /ha) and tree basal area (\15 m2 / ha) in the Greater Serengeti-Mara Ecosystem, and simultaneously explored their sensitivity to soil moisture. We show that σ0 vh in particular can be used to estimate grass biomass (R2 = 0.54, RMSE = 630 kg/ha, %range = 20.6), woody canopy volume (R2 = 0.69, RMSE = 4188 m3 /ha, %range = 11.8) and tree basal area (R2 = 0.44, RMSE = 2.03 m2 /ha, %range = 18.6) in the dry season, allowing for the extrapolation to regional scale vegetation structure maps. We also introduce new proxies for soil moisture as an option for extending this approach to the wet season using the 90-day preceding bounded running averages of the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and the Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) datasets. We discuss the potential of Sentinel-1 imagery for better understanding of the spatio-temporal dynamics of vegetation structure in savannas.