Prediction of locust outbreaks from RADARSAT-1 multi-angle data

Locust infestations of semiarid areas are preceded by well defined soil moisture conditions. Therefore the potential of outbreaks can be partially predicted by accurate mapping of soil moisture on the field-scale (∼100 m). In this manner, Radarsat International has run a successful locust outbreak prediction campaign in Kazakhstan (LIMIS). This was based on Radarsat-1 backscatter images combined with simultaneous soil moisture ground truth. Although, as shown by LIMIS, soil moisture maps can be successfully derived from RADARSAT-1 imagery using high quality ground measurements, this method has disadvantages. The main problem is the high cost and difficulty associated with collecting sufficient ground measurements. To overcome this problem, soil moisture maps can be derived without the use of ground measurements from multiple RADARSAT-1 images, each with a different incidence angle. This work presents encouraging research results towards an automated ground-measurement free system based on multi-angle SAR data inversion.