STUDY AND MODELING OF TEMPERATURE SPATIAL VARIABILITY BY NOAA-AVHRR THERMAL IMAGERY

Several land management activities require the spatially continuous es timation of environmental parameters which are usually measured locall y (temperature, rainfall, radiation, etc.). Numerous interpolation met hods have been developed for this aim, among which the kriging approac h is one of the most widely known and utilized. The approach is based on the experimental definition of spatial semi-variograms, which is of ten a difficult operation due to the insufficient coverage of the meas urement points in the study areas. A typical example of this situation is the interpolation of maximum daily temperature in a topographicall y complex Italian region (Tuscany). Since NOAA-AVHRR measures surface temperature daily with a relatively high spatial resolution (1.1 km), it is here proposed that these data can be used for a better definitio n of the semi-variograms of maximum temperature. Following this approa ch, satellite thermal estimates from six scenes were first compared to ground measurements of maximum daily temperature. Experimental semi-v ariograms were then derived from both data sets as well as from the wh ole thermal infrared images. The results show that the estimated model parameters from the various methods are quite different and the fitti ng of the experimental points to the theoretical model is much better when using continuous satellite data. This finding has interesting imp lications for the more general problem of defining standard optimum in terpolation methods.