Suchergebnisse

Abstract. Identification and mapping of landslide deposits are an intrinsically difficult and subjective operation that requires a great effort to minimise the inherent uncertainty. For the Staffora Basin, which extends for almost 300 km2 in the northern Apennines, three landslide inventory maps were independently produced by three groups of geomorphologists. In comparing each map with the others, large positional discrepancies arise (in the range of 55–65%). When all three maps are overlain, the locational mismatch of landslide deposit polygons increases to over 80%. To assess the impact of these errors on predictive models of landslide hazard, for the study area discriminant models were built up from the same set of geological-geomorphological factors as predictors, and the occurrence of landslide deposits within each terrain-unit, derived from each inventory map, as dependent variable. The comparison of these models demonstrates that statistical modelling greatly minimises the impact of input data errors which remain, however, a major limitation on the reliability of landslide hazard maps.

Abstract. We tested a high-quality laser rangefinder binocular coupled with a GPS receiver connected to a Tablet PC running dedicated software to help recognize and map in the field recent rainfall-induced landslides. The system was tested in the period between March and April 2010, in the Monte Castello di Vibio area, Umbria, Central Italy. To test the equipment, we measured thirteen slope failures that were mapped previously during a visual reconnaissance field campaign conducted in February and March 2010. For reference, four slope failures were also mapped by walking the GPS receiver along the landslide perimeter. Comparison of the different mappings revealed that the geographical information obtained remotely for each landslide by the rangefinder binocular and GPS was comparable to the information obtained by walking the GPS around the landslide perimeter, and was superior to the information obtained through the visual reconnaissance mapping. Although our tests were not exhaustive, we maintain that the system is effective to map recent rainfall induced landslides in the field, and we foresee the possibility of using the same (or similar) system to map landslides, and other geomorphological features, in other areas.

Abstract. A high resolution Digital Elevation Model with a ground resolution of 2 m×2 m (DEM2) 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 2.7×105 m2. Topographic derivative maps obtained from the DEM2 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 DEM2 was compared to a coarser resolution (10 m×10 m) DEM10 to establish how well the two DEMs captured the topographic signature of landslides. Results indicate that the improved topographic information provided by DEM2 was significant in identifying recent rainfall-induced landslides, and was less significant in improving the representation of stable slopes.

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. The Umbria Region of Central Italy has a long history of mass movements. Landslides range from fast moving rock falls and debris flows, most abundant in mountain areas, to slow moving complex failures extending up to several hectares in the hilly part of the Region. Despite landslides occurring every year in Umbria, their impact remains largely unknown. We present an estimate of the impact of slope failures in the Umbria region based on the analysis of a catalogue of historical information on landslide events, a recent and detailed regional landslide inventory map, and three event inventories prepared after major landslide triggering events. Emphasis is given to the impact of landslides on the population, the transportation network, and the built-up areas. Analysis of the available historical information reveals that 1488 landslide events occurred at 1292 sites in Umbria between 1917 and 2001. In the same period 16 people died or were missing and 31 people were injured by slope movements. Roads and railways were damaged by slope failures at 661 sites, and 281 built-up areas suffered landslide damage. Three event inventories showing landslides triggered by high intensity rainfall events in the period 1937–1941, rapid snow melting in January 1997, and earthquakes in September–October 1997, indicate the type, abundance and distribution of damage to the population, the built-up areas and the transportation network caused by typical landslide-triggering events. Analysis of a geomorphological landslide inventory map reveals that in some of the municipalities in the region total landslide area exceeds 25%. Of the more than 45 700 landslide areas shown in the geomorphological inventory map, 4115 intersect a road or railway, and 6119 intersect a built-up area. In these areas slope failures can be expected during future landslide triggering events.

Abstract. Landslide inventory maps (LIMs) show where landslides have occurred in an area, and provide information useful to different types of landslide studies, including susceptibility and hazard modelling and validation, risk assessment, erosion analyses, and to evaluate relationships between landslides and geological settings. Despite recent technological advancements, visual interpretation of aerial photographs (API) remains the most common method to prepare LIMs. In this work, we present a new semi-automatic procedure that makes use of GIS technology for the digitization of landslide data obtained through API. To test the procedure, and to compare it to a consolidated landslide mapping method, we prepared two LIMs starting from the same set of landslide API data, which were digitized (a) manually adopting a consolidated visual transfer method, and (b) adopting our new semi-automatic procedure. Results indicate that the new semi-automatic procedure (a) increases the interpreter's overall efficiency by a factor of 2, (b) reduces significantly the subjectivity introduced by the visual (manual) transfer of the landslide information to the digital database, resulting in more accurate LIMs. With the new procedure, the landslide positional error decreases with increasing landslide size, following a power-law. We expect that our work will help adopt standards for transferring landslide information from the aerial photographs to a digital landslide map, contributing to the production of accurate landslide maps.

Abstract. The autumn of 2004 was particularly wet in Umbria, with cumulative rainfall in the period from October to December exceeding 600 mm. On 4–6 December and on 25–27 December 2004, two storms hit the Umbria Region producing numerous landslides, which were abundant near the town of Orvieto where they affected volcanic deposits and marine sediments. In this work, we document the type and abundance of the rainfall-induced landslides in the Orvieto area, in south-western Umbria, we study the rainfall conditions that triggered the landslides, including the timing of the slope failures, we determine the geotechnical properties of the failed volcanic materials, and we discuss the type and extent of damage produced by the landslides. We then use the recent event landslide information to test a geomorphological assessment of landslide hazards and risk prepared for the village of Sugano, in the Orvieto area. Based on the results of the test, we update the existing landslide hazards and risk scenario for extremely rapid landslides, mostly rock falls, and we introduce a new landslide scenario for rapid and very rapid landslides, including soil slides, debris flows and debris avalanches.

To achieve the UN 2030 Agenda Goals, and considering their complexity and multidisciplinary, Multi-criteria analysis appears to be a suitable approach to give a true support to public decision makers in defining policy lines. This study focuses on the application of the Multiple Reference Point Weak-Strong Composite Indicators (MRP-WSCI) and its partially compensatory version (MRP-PCI), to assess, in the framework of the UN 2030 Agenda, the sustainability of the 28 members of the European Union (pre-Brexit). Countries were analyzed and compared according to their conditions and progress against the 17 Sustainable Development Goals, considering three reference years: 2007, 2012 and 2017. The analysis shows that Nordic countries reach a good level of global sustainability, with values of the indicators, W-W-W and S-W-W, between 2 and 3; while the States of east Europe, in particular Romania, Bulgaria and Greece, stay at the worst levels, having overall indicators values less than 1.5. Furthermore, the results highlight how countries in the lower group have difficulties especially in social and economic sustainability. On the other hand, states with a good overall condition record the worst results in the environmental dimension, such as the Netherlands, which shows, for the year 2017, a value for this sphere less than 2, while in the other two show a good value (over 2.5).

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. We present an approach to measure 3-D surface deformations caused by large, rapid-moving landslides using the amplitude information of high-resolution, X-band synthetic aperture radar (SAR) images. We exploit SAR data captured by the COSMO-SkyMed satellites to measure the deformation produced by the 3 December 2013 Montescaglioso landslide, southern Italy. The deformation produced by the deep-seated landslide exceeded 10 m and caused the disruption of a main road, a few homes and commercial buildings. The results open up the possibility of obtaining 3-D surface deformation maps shortly after the occurrence of large, rapid-moving landslides using high-resolution SAR data.