Robust Assessment of an Operational Algorithm for the Retrieval of Soil Moisture From AMSR-E Data in Central Italy

摘要: In this study, the soil moisture content (SMC) derived from AMSR-E acquisitions by using “HydroAlgo” algorithm, which is based on artificial neural networks (ANN), compared with simulated data obtained application of a water balance model (SWBM) in central Italy. All overpasses available for 9-year lifetime have been considered comparison, was carried out point over grid 91 nodes spaced at 0.1° × 0.1°, roughly corresponding to Umbria region. HydroAlgo includes disaggregation technique (smoothing filter-based intensity modulation), allowed obtaining an SMC product enhanced spatial resolution (0.1°) that expected be more suitable hydrological applications. The main purpose study exploit potential sensors studies, and particular monitoring regional scale heterogeneous landscapes typical Mediterranean environment. Slightly different results were ascending or descending overpasses; however, overall correlation coefficient between retrieved SWBM higher than 0.8 root mean square error less 0.055 m3/m3. Based these successful results, going implemented current multifrequency microwave radiometers (AMSR2) order obtain high-resolution assimilated into flood- landslide-related modeling