Estimating herbage biomass in semi-arid regions is essential, but remote sensing techniques are problematic for this purpose due to sparse vegetation cover and the strong effect that soil background has on signals. In order to minimize this problesm, the synergy of unmixed soil and vegetation data within the water-cloud model is presented in this study. Results show that the modified model estimations are in agreement with actual field measurements from the semi-arid zone of central Israel. These results may imply that the water-cloud model could be implemented in areas of sparse herbaceous canopies using ERS-2 SAR data when combined with additional information about vegetation cover.
ASJC Scopus subject areas
- Earth and Planetary Sciences (all)