In this study, several methods to compute land surface temperatures (LST) from Landsat TM5 data are compared. Two different approaches are considered. An image based approach that takes into account atmospherically corrected data by using a dark object subtraction model (DOS-1) and computes the emissivity as NDVI function. The emissivity of a surface is controlled by such factors as water content, chemical composition, structure and roughness; it can be determined as the contribution of the different components that belong to the pixels according to their proportions. NDVI method takes into account that vegetation and soils are the main surface cover for the terrestrial component. This emissivity is used to compute the LST by the inversion of Planck function. The other approach applies atmospheric correction to thermal infrared band and considers a constant emissivity of 0.95. Furthermore, the land surface temperature is computed by hybrid methods that result from the merger of the two initially considered approaches. These results are compared with the surface temperature measured by airborne Multispectral Infrared and Visible Imaging Spectrometer (MIVIS). The LST measured by MIVIS sensor can be considered closer to the real surface temperature because the data are acquired at an altitude of 1500 m and are not affected by significant atmospheric effects such as for satellite data, acquired at 705 km from the Earth's surface. The best results are obtained by considering variable emissivity.

Italian coasts are subjected to morphological modifications that in the last decades have, in many cases, been the cause of considerable coast-line withdrawal. A detailed cognizance on dynamics and relative consequences on territory and environment is necessary to plan actions for limiting these events and their impacts. Reconstruction of temporal shoreline changes can be realized using historical and recent maps, remote sensed images and topographic survey results.

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