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Abstract. Automatic subdivision of landscapes into terrain units remains a challenge. Slope units are terrain units bounded by drainage and divide lines, but their use in hydrological and geomorphological studies is limited because of the lack of reliable software for their automatic delineation. We present the r.slopeunits software for the automatic delineation of slope units, given a digital elevation model and a few input parameters. We further propose an approach for the selection of optimal parameters controlling the terrain subdivision for landslide susceptibility modeling. We tested the software and the optimization approach in central Italy, where terrain, landslide, and geo-environmental information was available. The software was capable of capturing the variability of the landscape and partitioning the study area into slope units suited for landslide susceptibility modeling and zonation. We expect r.slopeunits to be used in different physiographical settings for the production of reliable and reproducible landslide susceptibility zonations.

Abstract. We present the results of the application of a recently proposed model to determine landslide hazard. The model predicts where landslides will occur, how frequently they will occur, and how large they will be in a given area. For the Collazzone area, in the central Italian Apennines, we prepared a multi-temporal inventory map through the interpretation of multiple sets of aerial photographs taken between 1941 and 1997 and field surveys conducted in the period between 1998 and 2004. We then partitioned the 79 square kilometres study area into 894 slope units, and obtained the probability of spatial occurrence of landslides by discriminant analysis of thematic variables, including morphology, lithology, structure and land use. For each slope unit, we computed the expected landslide recurrence by dividing the total number of landslide events inventoried in the terrain unit by the time span of the investigated period. Assuming landslide recurrence was constant, and adopting a Poisson probability model, we determined the exceedance probability of having one or more landslides in each slope unit, for different periods. We obtained the probability of landslide size, a proxy for landslide magnitude, by analysing the frequency-area statistics of landslides, obtained from the multi-temporal inventory map. Lastly, assuming independence, we determined landslide hazard for each slope unit as the joint probability of landslide size, of landslide temporal occurrence, and of landslide spatial occurrence.

Abstract. We present a geomorphological method to evaluate landslide hazard and risk. The method is based on the recognition of existing and past landslides, on the scrutiny of the local geological and morphological setting, and on the study of site-specific and historical information on past landslide events. For each study area a multi-temporal landslide inventory map has been prepared through the interpretation of various sets of stereoscopic aerial photographs taken over the period 1941-1999, field mapping carried out in the years 2000 and 2001, and the critical review of site-specific investigations completed to solve local instability problems. The multi-temporal landslide map portrays the distribution of the existing and past landslides and their observed changes over a period of about 60 years. Changes in the distribution and pattern of landslides allow one to infer the possible evolution of slopes, the most probable type of failures, and their expected frequency of occurrence and intensity. This information is used to evaluate landslide hazard, and to estimate the associated risk. The methodology is not straightforward and requires experienced geomorphologists, trained in the recognition and analysis of slope processes. Levels of landslide hazard and risk are expressed using an index that conveys, in a simple and compact format, information on the landslide frequency, the landslide intensity, and the likely damage caused by the expected failure. The methodology was tested in 79 towns, villages, and individual dwellings in the Umbria Region of central Italy.

Abstract.A high resolution Digital Elevation Model with a ground resolution of 2 m×2 m (DEM 2 ) was obtained for the Collazzone area, central Umbria, through weighted linear interpolation of elevation points acquired by Airborne Lidar Swath Mapping. Acquisition of the elevation data was performed on 3 May 2004, following a rainfall period that resulted in numerous landslides. A reconnaissance field survey conducted immediately after the rainfall period allowed mapping 70 landslides in the study area, for a total landslide area of 2.7×10 5 m 2 . Topographic derivative maps obtained from the DEM 2 were used to update the reconnaissance landslide inventory map in 22 selected sub-areas. The revised inventory map shows 27% more landslides and 39% less total landslide area, corresponding to a smaller average landslide size. Discrepancies between the reconnaissance and the revised inventory maps were attributed to mapping errors and imprecision chiefly in the reconnaissance field inventory. Landslides identified exploiting the Lidar elevation data matched the local topography more accurately than the same landslides mapped using the existing topographic maps. Reasons for the difference include an incomplete or inaccurate view of the landslides in the field, an unfaithful representation of topography in the based maps, and the limited time available to map the landslides in the field. The high resolution DEM 2 was compared to a coarser resolution (10 m×10 m) DEM 10 to establish how well the two DEMs captured the topographic signature of landslides. Results indicate that the improved topographic information provided by DEM 2 was significant in identifying recent rainfallinduced landslides, and was less significant in improving the representation of stable slopes.