LAUSR

Landslides induced due to monsoon rainfall and earthquakes are very common phenomena in Uttarakhand Himalayas of India. For example, many such landslides got induced and reactivated by the 1999 Chamoli earthquake. In view of above, authors have made an attempt to prepare pre- and post-earthquake landslide susceptibility zonation (LSZ) maps for a part of Chamoli district, Uttarakhand, India. The novelty of this work lies in producing an LSZ map considering peak ground acceleration (PGA) as one of the controlling factors for earthquake-induced landslide occurrences and validating the LSZ map with the post-earthquake landslide inventory. For this purpose, a spatial database of seven controlling factors, i.e., slope angle, slope aspect, slope curvature, geology, distance to drainage, normalized difference vegetation index (NDVI) and peak ground acceleration (PGA) was prepared in Geographic Information System (GIS). Then, relative frequency ratio (RFR) method was adopted for the LSZ maps. The landslide inventory of 276 landslides (220 pre-earthquake and 56 post-earthquake landslides) was prepared for the study area. Firstly, an LSZ map was generated using six controlling factors excluding PGA and the pre-earthquake landslide inventory (Case I). In another attempt, the LSZ map is prepared using seven controlling factors including PGA and pre-earthquake landslide inventory to examine the influence of seismic parameter (PGA) in landslide susceptibility assessment (Case II). Subsequently, pre- and post-earthquake landslide inventory along with seven controlling factors were used to construct another LSZ map (Case III). Finally, these three LSZ maps were validated and compared with the training and testing data. In this study, a spatial predictive model for earthquake-induced landslide is developed.