Remote-sensing and GIS-based landslide-susceptibility zonation using the landslide index method in Igo River Basin, Eastern Himalaya, India

A remote-sensing and geographical information sysytem (GIS)-based quantitative methodology for landslide-susceptibility zonation is described in a stepwise manner with its application in the Igo River Basin in the West Siang District of Arunachal Pradesh, Eastern Himalaya, India. Parameters such as geology, physiography, slope angle, slope length, slope aspect, slope type, generic land-forms, lineament distance, road distance, drainage distance, altitudinal zones and land cover are used for landslide-susceptibility zonation. The quantitative relation between landslides and the selected parameters is established through the landslide index method of the International Institute for Geo-Information Science and Earth Observation (ITC), The Netherlands, by assigning weights. A weight value for a certain parameter class is defined as the natural logarithm of the landslide density in the class divided by the landslide density in the entire map. The final layer containing the composite index is divided into seven landslide-susceptibility categories. The maximum portion of the study area experiences moderately low to moderate landslide susceptibility, and each portion occupies an area of 91 km(2), representing 30% of the total area. High concentrations of very high and extremely high-susceptibility landslide areas are noticed in the steep slope areas, especially in the Sub-Himalayas. The settlements are found in the safe areas of very low, low and moderately low landslide-susceptibility categories. About 9% and 1.99% of the roads are exposed to high and very high landslide-susceptibility areas, respectively. About 15% of the slash-and-burn cultivation (jhum) is found along the high-susceptibility areas, 3.89% is found in very high-susceptibility areas and 0.19% is prone to extremely high susceptibility. The high-susceptibility zones are also found under dense and moderately dense forests.