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Quantitative hill-slope stability assessment with a remote sensing & GIS based distributed modeling scheme

As the development of the urbanization and the expansion of the infrastructure of China, landslide is becoming a concern of the people. The commonly-used approaches for landslide disaster warning include (1) field inspection using a check list to identify sites susceptible to landslides; (2) projection of future patterns of instability from analysis of landslide inventories; (3) multivariate analysis of factors characterizing observed sites of slope instability; (4) stability ranking based on criteria such as slope, lithology, land form, or geologic structure; and (5) failure probability analysis based on slope stability models with stochastic hydrologic simulations. Each of these is valuable for certain applications. None, however, takes full advantage of the fact that debris flow source areas are, in general, strongly controlled by surface topography through shallow subsurface flow convergence, increased soil saturation, increased pore pressures and shear strength reduction. Single landslide hazard prediction has achieved quite a few achievements [1-5] , and the results often cannot meet the needs for regional landslide hazard prediction. The hillslope stability refers to the distortion and damage probability of the hill-slope surface under the natural condition. The hill-slope stability is affected by many internal factors such as terrain slope, soil mechanics character, geological structure and external factors such as rainfall, surface water and ground water activities. Moreover, surface vegetation root system increases the sheer strength of soil; structure, texture and soil mechanics character characteristics that affect the strength and scope of the hill-slope stability. All these factors affect each other and different areas have different deformation mechanisms. Some models aims to give reliable prediction of slope disability have been proposed by the researchers, some of which have been successfully applied to the predication of the potential landslide hazard. The article selects the Lueyang County where the landslide develops typically near Hanzhong city of Shanxi province as the study area, SINMAP model was selected to integrate spatial information such as land use/land cover, soil type, vegetation root system development and historic landslide inventory to certify the surface hillslope stability of the study area, then a surface stability index mapping was produced from the statistics on the modeled results. Finally, hillslope stability mapping based on the modeled results were compared with those derived through extensive field observations in the same study area reported by Lu et al. (2003) to validate the validity and applicability of the model, and possible improvement of the model in the future studies are discussed briefly.