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Landslide Susceptibility Mapping at 1:1M Scale Over France: Exploratory Results with a Heuristic Model

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Landslide Susceptibility Mapping at 1:1M Scale Over France: Exploratory Results with a Heuristic Model Landslide susceptibility mapping at 1:1M scale over France: exploratory results with a heuristic model J.-P. Malet & Y. Thiery CNRS UMR 7516, School and Observatory of Earth Sciences, University of Strasbourg, Strasbourg, France J. Hervàs Institute for Environment and Sustainability, Joint Research Centre, European Commission, Ispra, Italy A. Günther BGR, Federal Institute for Geosciences and Natural Resources, Hannover, Germany A. Puissant CNRS UMR 7011, Laboratory Image, Ville et Environnement, University of Strasbourg, Strasbourg, France G. Grandjean BRGM, Bureau des Recherches Géologiques et Minières, Orléans, France ABSTRACT: In the framework of the European Soil Thematic Strategy, a project to map landslide suscepti- bility at the scale of Europe (i.e.1:1 Million) was suggested in 2007 by the European Soil Bureau Network (ESBN). The methodology consists to identify the potential areas subject to landslide types by expert knowl- edge using available thematic and environmental data. The choice of the 1:1 M scale allows the use of har- monized data sets for all Member States as input to the susceptibility model. Since a coherent landslide inven- tory map or geographical database does not exist at the European level, a pan-European landslide susceptibility map can only be prepared without inventory data, e.g. through heuristic modelling using Euro- pean level landslide conditioning- and (optionally) triggering- data. In a first step, the performance of the sus- ceptibility model is tested with some landslide inventory maps (density of landslides per administrative unit) available for France, Italy, Great Britain, Czech Republic and some Spanish regions. This work presents the susceptibility map created for France which quality is evaluated over six departments known for their numer- ous slope instabilities. This project is part of the European Expert Group on ‘Guidelines for Mapping Areas at Risk of Landslides in Europe’ coordinated by the JRC since October 2007. 1 INTRODUCTION Consequently, the Soil Information Working Group (SIWG) of the European Soil Bureau Net- In the framework of the European Soil Thematic work (ESBN) proposed some criteria for harmo- Strategy, and the associated preparation of a direc- nized risk area delineation which adopts a nested tive on the protection and sustainable use of soil, geographical approach based on ‘Tiers’ (Eckelmann landslides were recognized as a soil threat requiring et al., 2006) and exploit thematic data of different specific strategies for risk assessment and manage- type, quality, and resolution using a variety of meth- ment. For instance, a Pan-European hazard map odological and technological approaches (Hervás et based on quantitative criteria is available for water al., 2008; Fig. 2): erosion (Kirkby et al., 2003) or is being developed ● The ‘Tier 1’ assessment is aimed at the general for soil compaction and soil organic matter decline. (i.e., synoptic) identification of areas potentially For landslide, the only Pan-European hazard map subject to landslides, providing a low-resolution available is the one produced in 2005 within the (1:1 M scale) evaluation of landslide threats using ESPON Hazards Project based on national expert existing thematic and environmental data. opinion of the European Geological Surveys. This ● The ‘Tier 2’ assessment is intended to perform map was constructed by asking some experts to more detailed analyses in the areas identified by mark the NUTS 3 level areas of their respective Tier 1, and should provide results at a higher spa- country or region that have the possibility of land- tial resolution using existing and new data cur- slide hazards in general terms (Fig. 1). The process rently not available in all European countries. was based on available data and willingness of the The objective of this work is to present preliminary national expert to participate, and thus the proposed results obtained for the creation of the landslide sus- map is very uncertain in some regions or/and misses ceptibility map for France, which quality is evalu- some relevant information in other regions. Analysis ated over six departments known for their numerous of this map also pinpointed that the NUTS 3 level is slope instabilities. The aim is to pinpoint the limita- too coarse to highlight landslide prone areas. tions, data needs, practical selection of criteria (classes, parameter values) and adjustments to the -315- general methodology to carry out the global assess- ment at the European scale. The same preliminary analysis is currently performed in Germany, Italy, Hungary and Great Britain, as part of the European Expert Group on ‘Guidelines for Mapping Areas at Risk of Landslides in Europe’ coordinated by the JRC. Figure 2. Proposed methodology and input data for the Pan- European landslide susceptibility assessment (Hervás et al., 2007). 3 APPLICATION TO FRANCE: METHOD A tentative application of the methodology for France is presented in order to test the method and identify some possible limitations. For the France landslide susceptibility model, a minimum set of conditioning factors has been selected: (1) a slope gradient map, which is derived from the Figure 1. Areas with landslide hazards, based on national ex- pert opinion of the European Geological Surveys. In order to NASA SRTM (Shuttle Radar Topographic Mis- keep the comparability of simply displaying the landslide haz- sion) DEM acquired from X and C-band Interfer- ard, probability and risk factors are excluded from the map. ometric Synthetic Aperture Radar (Reuter et al., 2007). The DEM has a resolution of 3 arc sec- onds (approx. 90 m); the horizontal accuracy is 2 METHODOLOGY FOR ‘TIER1’ ANALYSIS lower than ± 20 m for more than 90% of the The main requirement for a ‘Tier 1’ assessment of DEM cells, and the vertical accuracy is ±16 m in areas prone to generic landslide types is the free absolute elevation and ± 6 m in relative elevation. availability of relevant conditioning and triggering A slope gradient map has been computed and 13 factor data. This could allow all Member State to use classes (interval of 5°) are used for the analysis. common data sets as input to the methodology to (2) a soil parent map, derived from the geological produce a harmonized landslide susceptibility map database of the French Geological Survey across Europe. Making a landslide hazard map for (BRGM) at 1:1M scale. The original map has the whole Europe has been considered not feasible been classified in 24 lithological classes, repre- because of the frequent lack of historical records sentative of the main geological units observed in about the temporal occurrence of landslides in most terms of lithology, structure and age. countries. (3) a landcover map, derived from the Corine Land Consequently, the methodology proposed by the Cover (CLC) dataset available for Europe. The JRC Landslide European Expert Group (Hervás et database is obtained by combination of Landsat al., 2007) is to adopt a qualitative evaluation tech- MSS and Spot XS imageries. An update with nique using a reduced set of data, including common Landsat ETM+ imageries from 2000 has been information on the instability conditioning factors performed in 2004. Each objects with an area lar- (e.g. soil/bedrock, slope angle and land cover). ger than 25ha are represented. Level 1 (10 Adoption of an index-based evaluation method can classes) of the CLS database is used in this work allow the production of a continent-wide landslide at 1:1M scale. susceptibility map for Europe, provided it is cali- brated with representative landslide data (Fig. 2). -316- Figure 3. Thematic maps of the landslide conditioning factors used for the Tier 1 susceptibility analysis for France, and departments selected for testing the performance of the model. First, the spatial and semantic consistency of all the input data and the landslide types. The thematic data have been controlled, and second, the weights can be assigned by different approaches data have been rasterized to a grid-based mapping (directly by expert knowledge, or indirectly by unit of 90 m corresponding to the resolution of the pairwise comparison matrix and/or by ranking; DTM. The thematic maps of the landslide condition- Castellanos Abella & van Westen, 2008). For ing factors at the France scale are presented on Fig- this research, we selected a direct weighting pro- ure 3. cedure. First, a value between 0 and 100 is as- The susceptibility analysis has been carried out signed for each class of variable, and second the with a spatial multi-criteria evaluation (SMCE) values are standardized by the maximum. technique available in ILWIS®. The multi-criteria model is based on the decision support-system and an analytic hierarchy process (AHP). A tree-shaped structure is used in order to associate the thematic variables and weighting factors for each class of variables. The methodological framework of this work is detailed in Figure 4, and can be subdivided in six steps: (1) A distinction of the input data in two distinct areas, e.g. the plain and the mountain areas, in order to take into account differences in the to- pographical conditions favourable to slope. The criteria used to define the plain areas and the mountain areas are based on the European crite- ria proposed by Nordregio (2004). (2) A distinction between the different landslide types in order to take into account specific set of conditioning factors for each landslide type; the analysis has been carried out for four landslide types, eg. topples and rock-falls, collapses and subsidence, slides, and flows. Figure 4. Methodological framework. (3) The calibration of weighs for each class of variables according to the relationship between -317- (4) The creation of a landslide susceptibility map in the plain areas are used in order to consider spe- for each landslide type. For each simulation, the cific processes such as subsidence observed in flat total weights are analyzed by expert judgement: areas, or falls, slide and flows observed along soft or the susceptibility classes are defined according hard rocks sea cliffs, as for instance in Calvados.
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