Landslide detection and mapping represent fundamental requirements for every hazard and risk evaluation and consequent improvement of the management strategies for such natural hazards. Optical and radar remote sensing can be used to observe landslide-induced ground deformation, ranging from regional to local scales. This work presents a methodology called Landslide HotSpot Mapping; this approach integrates cartographic, thematic and optical data with Persistent Scatterer Interferometry for the identification of extremely slow to very slow moving landslides, and for the evaluation of their state of activity and intensity. This methodology scans wide areas to detect hotspots, which are narrow unstable zones characterized by higher landslide hazard. To these hotspots, priority has to be given when planning field surveys and in situ validation campaigns, so that field work time and effort can be optimized and significantly reduced. The approach is tested in Central Calabria, over a 4,470 km 2 area located in southern Italy. ENVISAT ascending images acquired between 2003 and 2009 and processed with the Persistent Scatterer Pairs (PSP) technique are used to analyse deformation patterns. Combining conventional photo-interpretation with the analysis of PSP data, 64 new landslides are identified and the spatial (boundaries) and temporal (activity) information of 980 pre-mapped phenomena (23.6% of updated inventory) are updated. 1,012 active (continuous or reactivated) landslides are identified and 4 hotspot areas selected: San Fili, Rende, Lago, Catanzaro. Urgent field checks have to be organized for these hotspots to validate the satellite-based observations and to design appropriate mitigation measures to reduce impacts on the elements at risk. © 2012 Springer-Verlag.

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