Javier Hervás

Recommendations for the quantitative analysis of landslide risk

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

Statistical modelling of Europe-wide landslide susceptibility using limited landslide inventory data

In many regions, the absence of a landslide inventory hampers the production of susceptibility or hazard maps. Therefore, a method combining a procedure for sampling of landslide-affected and landslide-free grid cells from a limited landslide inventory and logistic regression modelling was tested for susceptibility mapping of slide- and flow-type landslides on a European scale. Landslide inventories were available for Norway, Campania (Italy), and the Barcelonnette Basin (France), and from each inventory, a random subsample was extracted. In addition, a landslide dataset was produced from the analysis of Google Earth images in combination with the extraction of landslide locations reported in scientific publications. Attention was paid to have a representative distribution of landslides over Europe. In total, the landslide-affected sample contained 1,340 landslides. Then a procedure to select landslide-free grid cells was designed taking account of the incompleteness of the landslide inventory and the high proportion of flat areas in Europe. Using stepwise logistic regression, a model including slope gradient, standard deviation of slope gradient, lithology, soil, and land cover type was calibrated. The classified susceptibility map produced from the model was then validated by visual comparison with national landslide inventory or susceptibility maps available from literature. A quantitative validation was only possible for Norway, Spain, and two regions in Italy. The first results are promising and suggest that, with regard to preparedness for and response to landslide disasters, the method can be used for urgently required landslide susceptibility mapping in regions where currently only sparse landslide inventory data are available.

Tier-based approaches for landslide susceptibility assessment in Europe

In the framework of the European Soil Thematic Strategy and the associated proposal of a Framework Directive on the protection and sustainable use of soil, landslides were recognised as a soil threat requiring specific strategies for priority area identification, spatial hazard assessment and management. This contribution outlines the general specifications for nested, Tier-based geographical landslide zonings at small spatial scales to identify priority areas susceptible to landslides (Tier 1) and to perform quantitative susceptibility evaluations within these (Tier 2). A heuristic, synoptic-scale Tier 1 assessment exploiting a reduced set of geoenvironmental factors derived from common pan-European data sources is proposed for the European Union and adjacent countries. Evaluation of the susceptibility estimate with national-level landslide inventory data suggests that a zonation of Europe according to, e.g. morphology and climate, and performing separate susceptibility assessments per zone could give more reliable results. To improve the Tier 1 assessment, a geomorphological terrain zoning and landslide typology differentiation are then applied for France. A multivariate landslide susceptibility assessment using additional information on landslide conditioning and triggering factors, together with a historical catalogue of landslides, is proposed for Tier 2 analysis. An approach is tested for priority areas in Italy using small administrative mapping units, allowing for relating socioeconomic census data with landslide susceptibility, which is mandatory for decision making regarding the adoption of landslide prevention and mitigation measures. The paper concludes with recommendations on further work to harmonise European landslide susceptibility assessments in the context of the European Soil Thematic Strategy.

New Developments in Harmonized Landslide Susceptibility Mapping over Europe in the Framework of the European Soil Thematic Strategy

In the context of the European Soil Thematic Strategy, and the formulation of a draft of a European framework directive devoted to the sustainable use of soil, landslides are recognized as one of the eight soil threats requiring harmonized spatial hazard assessments over the EU territory. The general framework for such assessments consists of a nested geographical approach based on “Tiers”, where a low-resolution (1:1 Million) evaluation (“Tier 1”) using already available pan-European datasets should enable the delineation of priority areas requiring more detailed assessments with additional data (“Tier 2”). In this contribution, we present new developments in the elaboration of a “Tier 1” generic landslide susceptibility evaluation based on a heuristic modelling approach exploiting the most important landslide conditioning factors. Extensive landslide locations available at small spatial scales have been collected and harmonized over the EU territory to be used for input parameter specification and model calibration, evaluation and classification. Since the analyzed area is highly complex in terms of climato-physiographic conditions controlling landslide occurrences, a preliminary landslide terrain differentiation is proposed consisting of eight calibration zones where specific predictor class weights have been allocated through a heuristic indexing approach. The spatially combined preliminary pan-European susceptibility estimate classifies 13 % of the EU territory as prone to landslides, thus requiring more detailed, quantitative inventory-based susceptibility evaluations (“Tier 2”).

Synoptic Pan-European Landslide Susceptibility Assessment: The ELSUS 1000 v1 Map

In order to identify areas in Europe susceptible to landslides in the context of the EU Soil Thematic Strategy and the associated Proposal for a Soil Framework Directive, a harmonised approach encompassing geographically-nested susceptibility assessments (“Tiers”) and, where possible, the use of comparable datasets as input criteria for susceptibility modelling was devised. The first version of the 1 km grid size European Landslide Susceptibility Map (ELSUS 1000 v1), covering the EU and neighbouring countries, is derived from “Tier 1” assessment. The mapping approach employed includes first a climate-physiographic regionalisation of the study area. For each region, a spatial multi-criteria evaluation model is established to evaluate landslide susceptibility using commonly available pan-European datasets on slope angle, lithology and land cover, which are considered as the main conditioning factors for all types of landslides at this scale. Factor weights are assigned through pairwise comparisons using analytical hierarchy processes for each region, while region-specific factor class weights are initially established by computing landslide frequency ratios using more than 102,000 landslide locations across Europe. For each model region, a pixel-based susceptibility index is calculated by linear summation of conditioning factor weights and factor class weights. Each index map is then evaluated and classified into five susceptibility levels using true positive ratio breaks derived from receiver operating characteristics curves obtained with the landslide inventory. Finally, the region-specific classified susceptibility maps are spatially combined into the synoptic ELSUS 1000 v1 map. The map is available from the European Soil Data Centre (ESDAC), hosted by the Joint Research Centre, together with ancillary datasets, including a reliability evaluation of the susceptibility map. Further work is in progress to improve the accuracy of the map, mainly by integrating into the assessment a new pan-European lithological dataset and further landslide locations for areas not represented in the current inventory.

Mass-Movement Causes: Overloading

Overloading or the excessive addition of a surcharge load or external load on a hillslope section is one of the external factors influencing slope stability. Although overloading occurs under natural conditions such as vegetation growth, persistent precipitation, and volcanic activity, it is very commonly the result of human activities such as filling for construction works or dumping of waste material. Geotechnical models, generally based on the calculation of the factor of safety ( F ), allow evaluation of the impact of a fill or a cut at different locations on the slope on F . External loading on the upper part of a slope usually decreases slope stability where the slope gradient is higher than the angle of internal friction, whereas external loading on the lower part of the slope stabilizes the slope. However, as parameters controlling the weight resting on a potential surface of rupture affect both shear stress and shear strength, the changes in stability are generally relatively small and decrease with increasing surface of rupture depth. Comparison of the influence of changes in the different parameters on the F by means of a sensitivity analysis indeed shows that changes in the weight on the rupture surface have only a minor impact compared to changes in slope gradient, cohesion, and angle of internal friction. Yet, overloading as a causal factor of landsliding cannot be neglected as it is the cumulative effect of all causal factors that will finally determine the slope stability.

Mapping of Landslides Under Dense Vegetation Cover Using Object-Oriented Analysis and LiDAR Derivatives

Light Detection and Ranging (LiDAR) and its wide range of derivative products have become a powerful tool in landslide research, particularly for landslide identification and landslide inventory mapping. In contrast to the many studies that use expert-based analysis of LiDAR derivatives to identify landslides, only few studies, all pixel-based, have attempted to develop computer-aided methods for extracting landslides from LiDAR. So far, it has not been tested whether object-oriented analysis (OOA) could be an alternative. Therefore, this study focuses on the application of OOA using LiDAR derivatives such as slope gradient, curvature, and difference in elevation (2m resolution). More specifically, the focus is on the possible use for segmentation and classification of slow-moving landslides in densely vegetated areas, where spectral data do not allow accurate landslide inventory mapping. The test areas are the Flemish Ardennes (Belgium) and Vorarlberg (Austria). In a first phase, a relatively qualitative procedure based on expert-knowledge and basic statistical analysis was developed for a test area in the Flemish Ardennes. The procedure was then applied without further modification to a validation area in the same region. The results obtained show that OOA using LiDAR derivatives allows recognition and characterization of profound morphologic properties of deep-seated landslides, because approximately 70% of the landslides of an expert-based inventory were also included in the object-oriented inventory. For mountain areas with bed rock outcrops like Vorarlberg, on the other hand, it is more difficult to create a transferable model.

Pan-European landslide susceptibility mapping: ELSUS Version 2

ABSTRACT We present an updated version of the European landslide susceptibility map ELSUS 1000 released through the European Soil Data Centre in 2013. The ELSUS V2 map shows the landslide susceptibility zonation for individual climate-physiographic zones across Europe. ELSUS V2 covers a larger area of Europe than ELSUS 1000 at a higher spatial resolution (200 × 200 m). The updated map was prepared using the same semi-quantitative method as for ELSUS 1000, combining landslide frequency ratios information with a spatial multi-criteria evaluation model of three thematic predictors: slope angle, shallow subsurface lithology and land cover. However, the new map was prepared using also: (i) an extended landslide inventory, containing 30% of additional locations for model calibration, map validation and classification and (ii) a new lithological data set derived from the International Hydrogeological Map of Europe (IHME). The new version of the map increases the overall predictive performance of ELSUS by 8 %.

Index-Oriented Methodologies for Landslide Consequence Analysis: An Application to a Mountain Community in the French Alps

Consequence analysis is a key aspect of anchoring assessment of landslide impacts to present and long-term development planning. Although several approaches have been developed over the last decade, some of them are difficult to apply in practice, mainly because of the lack of valuable data on historical damages or on damage functions. In this paper, two possible consequence indicators based on a combination of descriptors of the exposure of the elements at risk are proposed in order to map the potential impacts of landslides and highlight the most vulnerable areas. The first index maps the physical vulnerability due to landslide; the second index maps both direct damage (physical, structural, functional) and indirect damage (socio-economic impacts) of landslide hazards. The indexes have been computed for the 200 km2 area of the Barcelonnette Basin (South French Alps), and their potential applications are discussed.

Landslide Databases in Europe: Analysis and Recommendations for Interoperability and Harmonisation

Landslide inventories, usually including digital inventory maps and linked alphanumeric attributes, are the most important input for further landslide zoning. However, to allow landslide susceptibility, hazard and risk assessment the inventory databases should contain information on the location of landslide phenomena, types, history, state of activity, magnitude or size, causal factors and the damage caused. Yet, in Europe it is not known which national (or regional) landslide databases contain all this information, and thus allow landslide risk assessment. Therefore this study presents a review of existing national landslide databases in Europe together with a number of regional databases, and proposes improvements in agreement with the EU Soil Thematic Strategy, and with INSPIRE Directive.