Map of deep seated gravitational slope deformations susceptibility in central Italy derived from SRTM DEM and spectral mixing analysis of the Landsat ETM + data

Considerable enhancement for morphometric interpretation can be obtained by means of the integration of spectral data with Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM). The effectiveness of topography classification with SRTM DEM is enhanced by the use of optical remote sensing data such as Landsat ETM+ that has undergone Spectral Mixing Analysis (SMA). The SMA uses a linear mixture model to provide a physical basis for a more detailed representation of land surface reflectance as mixture of endmembers. In this work we use these data for deep seated gravitational slope deformation (DSGSD) topography characterization to identify slopes whose morphology is indicative of deep seated phenomena. The final results indicate that when incorporated with optical SMA of the Landsat ETM+, the SRTM analysis should improve our capacity for mapping and identifying DSGSD in specific landscapes.