Quick Search:    advanced search

GSW Home   GeoRef Home   My GSW Alerts   Contact GSW   About GSW   Journals List   Help

This Article Résumé Figures Only Full Text Full Text (PDF) Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Web of Science (2) Citing Articles via Google Scholar Google Scholar Articles by Grandjean, G. Articles by Méric, O. Search for Related Content GeoRef GeoRef Citation

Geophysical data fusion by fuzzy logic for imaging the mechanical behaviour of mudslides

¹ ‘Bureau de Recherches Géologiques et Minières’ (BRGM), Aménagement et Risques Naturels, BP 6009, F-45060 Orléans, France. Tel. + 33 (0)238 643 524 / Fax. +33 (0)238 643 361 / E-mail : g.grandjean{at}brgm.fr
² ‘Faculty of Geosciences’, UCEL, Utrecht University, Po.Box 80.115, NL-3508 TC Utrecht, Netherlands.
³ ‘Laboratoire Interdisciplinaire de Recherche Impliquant la Géologie et la Mécanique’ (LIRIGM), EA 3111 UJF, Maison des Géosciences, BP 53, F-38041 Grenoble cedex 9, France.

Geophysical methods such as seismic surveying or electrical resistivity imaging appear to be well adapted to investigate landslide structure and understand related mechanisms. They allow direct and non-intrusive measurements of acoustic (P), shear (S) waves velocity and electrical resistivity, three physical parameters considered as essential to define the properties of reworked moving materials. Both methods were applied at the "Super-Sauze" site, in the French South Alps, where a typical example of an intra-material mudslide can be observed. Measurements were taken simultaneously along a profile of 325 m in length, perpendicularly to the axis of the mudslide. The P and S-wave velocity fields, as well as the electrical resistivity field, were inverted from recorded data according to suitable algorithms. P and S-wave velocities as well as resistivity tomographies are presented and discussed in term of reliability. Preliminary interpreted results show a correlation between the seismic velocities and electrical resistivity data, confirming that the simultaneous use of both methods gives complementary information on the geomechanical behaviour of the landslide. The seismic data provide information on the variations of fissure density and on the presence of deformed material whereas the electrical resistivity data provide information on the variations of water content within the mudslide. In order to go deeper into the interpretation of the geomechanical behaviour of the mudslide from geophysical data, a data fusion strategy based on fuzzy subsets theory is developed. The computed fuzzy cross-sections show the possibility of geomechanical hypotheses to be realized in specific areas of the tomographic cross-sections highlighting the places where plastic or solid-body deformations could occur. This information is consistent with the geotechnical data and the borehole inclinometer measurements available for the mudslide.

Key Words: Landslide • Geophysics • Tomography • Spectral analysis of surface waves • Data fusion • Fuzzy logic • Geomechanics