A method for retrieving both agricultural biomass and soil moisture starting from simultaneous observations at L and X band is described in this paper. The research was carried out within the framework of the SIASGE (Italian-Argentine System of Satellites for Emergency Management) project, funded by the Italian Space Agency (ASI), for the definition and development of X and L products oriented towards applications for risk and emergency management. SAR data at L (ALOS/PALSAR) and X (COSMO/SkyMed) bands were used for producing maps of Soil Moisture Content (SMC) and Plant Water Content (PWC) using inversion algorithms based on Artificial Neural Networks sssand on empirical relationships based on previous experiments. SMC obtained in an agricultural area in Lombardy showed average values in agreement with monthly rainfall. The corresponding maps of PWC were produced for the same area, and in this case the result was in agreement with the season, the classification, and the related agricultural practices.
Journal articles from the Grassland Society of Southern Africa (GSSA) African Journal of Range and Forage Science as well as related articles and reports from throughout the southern African region.