Landslide hazard mapping using a GIS and a Fuzzy Neural Network

The aim of this work is to use information from various sources, including remote sensing images from which land use change may be identified, in order to produce landslide hazard maps. We designed a fuzzy neural network which allows us to incorporate all the levels of uncertainty in the informations used in order to draw conclusions about the severity of the landslide hazard. The scale of operation of such a system is at the regional level rather than the local microlevel where ground local measurements may be performed and detailed geotechnical mathematical models may be applied to calculate soil stresses. It is not possible to apply such accurate detailed models for large scale hazard assessment. The proposed system is expected to be less accurate but more widely applicable than what is currently used in geotechnics.