Ivan Marchesini

A method for the assessment of the influence of bedding on landslide abundance and types

Bedding planes are a known factor that controls the type, abundance and pattern of landslides. Where layered rocks crop out, the geometrical relationships between the attitude of the bedding and the geometry of the terrain is crucial to understand landslide phenomena. Obtaining information on bedding attitude for large areas through field surveys is time-consuming, and resource intensive, hampering the possibility of quantitative investigations on the control of bedding planes on landslides. We propose a GIS-based method to extract information on bedding planes from the analysis of information captured through the visual interpretation of stereoscopic aerial photographs and a digital representation of the terrain. We tested the method in the Collazone study area, Umbria, Central Italy, where we used spatially distributed information on beddings and terrain information obtained from a 10 × 10-m DEM to determine morpho-structural domains. We exploited the morpho-structural terrain zonation, in combination with landslide information for the same area, to investigate the role of beddings in controlling the distribution and abundance of landslides in the study area. We found that beddings condition the location and abundance of relict and deep-seated landslides, most abundant in cataclinal slopes, and do not condition significantly the shallow landslides. We expect the method to facilitate the production of maps of morpho-structural domains in layered geological environments. This will contribute to a better understanding of landslide phenomena and to foster the preparation of advanced landslide susceptibility and hazard models.

A GIS Method for Obtaining Geologic Bedding Attitude

Landslide susceptibility assessment at different scales and in different physiographic environments requires quantitative information on multiple thematic environmental data. Information on bedding attitude proves necessary to define the structural and geological setting of an area. In this study, we developed a procedure to obtain bedding attitude data exploiting aerial photo-interpretation and a GRASS GIS script. Results show that our procedure provides bedding attitude information in good agreement with data acquired during field surveys. We foresee the possibility to generate dense spatial distributions of bedding attitude data, useful for spatial interpolation and landslide susceptibility assessments.

A New Digital Catalogue of Harmful Landslides and Floods in Italy

Landslides and floods are widespread and recurrent in Italy, where they cause damage and pose a threat to the population. To estimate geo-hydrological risk in Italy, catalogues of landslide and flood events that have caused damage to the population were compiled from a variety of sources. The catalogues covers the 1,943-year period from 68 A.D. to 2010, and list 3,310 landslide events and 2,624 flood events that have resulted in deaths, missing persons, injured people, and homeless. For each event in the catalogue, different types of information were collected and organized in a database. We describe the Spatial Data Infrastructure (SDI) we have implemented to collect, store, analyze, and disseminate the historical information, and results of the analysis of landslide and flood risk to the population.

GIS-Based Deterministic Analysis of Deep-Seated Slope Stability in a Complex Geological Setting

The r.slope.stability computer model evaluates the slope stability for large areas making use of a modification of the three-dimensional sliding surface model proposed by Hovland and revised and extended by Xie and co-workers. The initial version of the model was modified both to reduce computing time (parallel processing of tiles) and to explore the possibilities to perform slope stability modelling in a complex geological setting. The model was applied to the 10 km2 Ripoli area in Umbria, central Italy to demonstrate the importance of the setting of the geological layers as well as of the seepage direction of the groundwater for the model outcome of deep-seated slope stability modelling. Parallel processing allows reducing the computing time by approx. one order of magnitude.

Assessing the influence of morpho-structural setting on landslide abundance

Knowing the factors that influence landslide abundance and distribution is important to evaluate landslide susceptibility and hazard. Visual interpretation of aerial photographs (API) can be used to collect spatially distributed information on bedding attitude (BA), in an area. Where a map of the location of bedding traces (BTs), i.e. lines showing the intersection of bedding planes with the local topography, is available, the map can be used to obtain BA point data and to prepare maps showing morpho-structural domains. The possibility of using BA maps to investigate the influence of morpho-structural settings on landslide abundance is hampered by the lack of understanding of the influence of the length of the BTs, and of the parameters used to interpolate the BA data on the structural zonation. To investigate the problem, we used information on 207 BTs obtained through API in the Collazzone area, Central Italy, and we prepared 150 maps showing BA information. This was accomplished using 15 different values for the segmentation length of the BTs (S), and 10 different values for the tension parameter (T) used for the interpolation. We compare the results against previous results obtained for the same area adopting a heuristic approach to the segmentation of the same set of BTs. Next, we compare the geographical distribution of old deep-seated, deep-seated and shallow landslides in five morpho-structural domains in the study area, and we analyse the influence of the structural settings on the abundance of the different types of landslides.

Topography-driven satellite imagery analysis for landslide mapping

ABSTRACT We describe a semi-automatic procedure for the classification of satellite imagery into landslide or no landslide categories, aimed at preparing event landslide inventory maps. The two-steps procedure requires knowledge of the occurrence of a landslide event, availability of a pre- and post- event pseudo-stereo pair and a digital elevation model. The first step consists in the evaluation of a discriminant function, applied to a combination of well-known change detection indices tuned on landslide spectral response. The second step is devoted to discriminant function classification, aimed at distinguishing the only landslide class, through an improvement of the usual ‘thresholding’ method. We devised a multi-threshold classification, in which thresholding is applied separately in small subsets of the scene. We show that using slope units as topographic-aware subsets produces best classification performance when compared to the ground truth of a landslide inventory prepared by visual interpretation. The method proved to be superior to the use of a single threshold and to any multi-threshold procedure based on topography-blind subdivisions of the scene, especially in the validation stage. We argue that the improved classification performance and limited training requirements represent a step forward towards an automatic, real-time landslide mapping from satellite imagery.

Considering parameter uncertainty in a GIS-based sliding surface model for large areas

The GIS-based open source software r.slope.stability computes broad-scale spatial overviews of shallow and deep-seated slope stability through physically-based modelling. We focus on the landslide-prone 90 km2 Collazzone area, central Italy, exploiting a comprehensive set of lithological, geotechnical and landslide inventory data available for that area. Inevitably, the geotechnical and geometric parameters are uncertain, particularly for their three-dimensional variability. Considering the most unfavourable set of geotechnical parameters (worst case scenario, appropriate for engineering purposes) is less useful to obtain an overview of the spatial probability (susceptibility) of landslides over tens of square kilometres. Back-calculation of the parameters based on topographic and geotechnical considerations would better suit for such a purpose, but obtaining one single parameter combination would require information on one of the parameters. Instead, we estimate the slope failure probability by testing multiple combinations of the model parameters sampled deterministically. Our tests indicate that (i) the geotechnical parameterization used allows to reproduce the observed landslide distribution partly (a challenge consists in the appropriate treatment of the variation of the geotechnical parameters with depth); (ii) the evaluation outcome depends strongly on the level of geographical aggregation; and (iii) when applied to large study areas, the approach is computing-intensive, and requires specific strategies of multi-core computing to keep computational times at an acceptable level.

Slope Dynamics and Climatic Change Through Indirect Interactions

The rapid variation of climate can cause direct changes in slope dynamics due to a modified rainfall regime. Variations in evapotranspiration regime determines changes in soil moisture, modifies shrinking-swelling cycles, creeping, surface mass movement, and soil erosion, including gully erosion. All these effects can be considered as direct consequences of any climate modification. Besides them, other indirect effects should be considered to fully determine climate change impact on slope dynamics. This is the case of the effects of climate change on vegetation, that strongly controls slope instability phenomena. Here we will concentrate on the effect of increased danger due to forest fire, and in particular we discuss the changes in the hydrogeological hazard linked to the effect of drought on wild fires in a case-study in Umbria (Italy), mainly considering field observations and simulations with LANDPLANER (LANDscape, Plant, LANdslide and ERosion) model. This study shows that when discussing of climate changes particular emphasis must be put on side effects that can influence slope dynamics and basin behavior. In particular the understanding of where threats can come, requires the identification of complex framework describing the dynamic interaction of all the elements coexisting in a slope.

A GIS Approach to Analysis of Deep-Seated Slope Stability in Complex Geology

We demonstrate the computer model r.rotstab.layers to explore the possibilities of GIS for catchment-scale deep-seated slope stability modelling in complex geology. This model makes use of a modification of the three-dimensional sliding surface model proposed by Hovland and revised and extended by Xie and co-workers. It evaluates the slope stability for a large number of ellipsoidal random slip surfaces which may be truncated at the interfaces between geological layers. This results in a spatial overview of potentially unstable regions. After demonstrating the functionality of the model with an artificial cone-shaped terrain, we test r.rotstab.layers for the 10 km2 Ripoli area in Umbria, central Italy. According to field observations in the Ripoli area, morpho-structural settings play a crucial role for deep-seated landslide distribution. We have prepared a model of the geological layers based on surface information on the strike and dip of each layer, and we use this model as input for r.rotstab.layers. We show that (1) considering the geological layers is essential for the outcome of deep-seated slope stability modelling, and (2) the seepage direction of the groundwater is a major source of uncertainty.

TXT-tool 3.039-1.1: Landslide-Related WPS Services

Researchers have developed and implemented software tools for a number of geospatial algorithms to support the analysis of the slope movements at different spatial scales. Frequently, these tools are implemented using Open Source software and are based on specific combinations of software libraries, programming languages and operating systems. This often limits the portability of these tools and hampers their sharing with a large community of potential users. To overcome these limitations, some researchers have started to make available their software tools through the Web Processing Service standard. This work introduces the reader to the WPS usage and explains how to take advantage of some existing WPS processes dealing with landslide size probability, bedding attitude estimation, morpho-structural domain definition, slope-units delineation.