BACKGROUND The Mediterranean region faces serious problems with water management for agriculture because of its susceptibility to prolonged droughts and the possibility to be amplified by climate change. Regular surface soil moisture (SM) sampling is one of the main inputs for hydrological modeling, and can be used to update the model's boundary conditions that drive surface and subsurface partitioning of water and energy fluxes. SM values generated from OPTICAL and SAR imagery could be assimilated into hydrological models. STUDY SITE Intensive field campaigns were undertaken at the Azienda San Michele (4.36 km²), an agricultural research center managed by a government research agency (AGRIS). This research center is situated in the Rio Mannu di San Sperate Basin (472.5 km²) where the average annual precipitation is about 700 mm, with 90% accumulated during the wet season from October to April. The rest of the year, from May to September, Sardinia faces a climate both very dry and very hot. The study site is situated in the Campidano Plain, the most important agricultural area of Sardinia (app. 3000 km²). CONCLUSION The findings at field scale suggest an interesting potential of the method. The comparison of the SAR and the Landsat empirical models, along with meteorological data shows a correlation between measured and retrieved soil moisture values from radar and from optical sensors. In ongoing work, this empirical modeling approach will be tested at the regional scale, for the Campidano Plain.