Combined use of socio economic analysis,remote sensing and GIS data for landslide hazard mapping using ANN

The term landslide includes a wide range of ground movements, such as slides, falls, flows etc. mainly based on gravity with the aid of several conditioning and triggering factors. Particularly in the last two decades, there has been an increasing international interest in the landslide susceptibility, hazard or risk assessments. In this paper we present a combined use of socioeconomic, remote sensing and GIS data for developing a technique for landslide susceptibility mapping using artificial neural networks and then to apply the technique to the selected study areas at Nilgiris district in Tamil Nadu and to analyze the socio economic impact in the landslide locations.