Geostationary satellites are capable of resolving the diurnal cycle by providing time sequence of observations with a very high temporal resolution. A Kalman filter methodology was developed to exploit such time continuity in order to simultaneously retrieve surface temperature and emissivity from SEVIRI (Spinning Enhanced Visible and Infrared Imager) data. The methodology was applied and tested over a geographic region in Southern Italy characterized by different surface features: arid, cultivated, vegetated and urban areas, and sea water. The objective is to implement a real-time continuous monitoring of surface parameters, which could be used for the various purposes of tourism and agronomy, land surveillance, natural hazards and risk assessment analysis. The retrieval of surface parameters was performed for the whole of 2013 and the results were compared to other similar satellite observations such as those derived from AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer). Comparisons with ECMWF (European Centre for Medium range Weather Forecasts) analyses for sea surface are provided as well.