Above-ground biomass estimates based on active and passive microwave sensor imagery in low-biomass savanna ecosystems

Abstract

Although many studies exist on the estimation and monitoring of above-ground biomass (AGB) of forest ecosystems by methods of remote sensing, very little research has been carried out for ecosystems of low primary production, such as grasslands, steppes, or savannas. Our study intends to approach this gap and investigates the correlation between space-borne radar information and AGB at the scale of 10 tons per hectare and below. Additionally, we introduce the integration of passive brightness temperature as an additional covariate for biomass estimation, based on the hypothesis that it contains information complementary to microwave backscatter of the active sensors. Our findings show that large-scale estimates of AGB can be conducted for grasslands and savannas at high accuracy (R2 up to 0.52). Additionally, we found that the integration of passive radar can increase the quality of AGB estimates in terms of explained variance for selected cases. We hope that these indications are a starting point for more integrated approaches toward biomass estimations based on Earth observation methods.