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In this paper, the soil moisture content (SMC) estimated from Advanced Microwave Scanning Radiometer 2 (AMSR2) through the ANN-based “HydroAlgo” algorithm is firstly compared with the outputs of the Soil Water Balance hydrological model (SWBM). The comparison is performed over Italy, by considering all the available overpasses of AMSR2, since July 2012. The SMC generated by Hydroalgo is then considered...
In this work, the surface soil moisture (SMC) derived from the AMSR-E acquisitions by using Artificial Neural Networks (ANN) is compared with simulated data obtained from the application of a soil water balance model in central Italy. All the overpasses available for the 9-years lifetime of AMSR-E have been considered for the comparison, which was carried out point by point over a grid of 91 nodes...
An algorithm for retrieving soil moisture (SMC) from SMAP acquisitions is presented in this paper. The algorithm is based on Artificial Neural Network (ANN) techniques and takes advantage of the synergy between active and passive SMAP acquisitions. The training was carried out by using both electromagnetic forward models based on the Radiative Transfer Theory (RTT) and experimental data from SMEX02...
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