LaSaRiZ: A Software for Landslide Susceptibility Zonation and Risk Assessment using Neural Network and Fuzzy Set Approaches

Availability of accurate and objective landslide susceptibility maps depicting zones defined on the basis of probability of occurrence of landslides is one of the critical inputs in assessing risk to property and lives in any mountainous region, particularly in the Himalayas. The aim of this study is to portray the usage of an in-house developed indigenous software, acronymmed as Landslide Susceptibility and Risk Zonation (LaSaRiZ), for landslide susceptibility zonation and risk assessment. The software incorporates the implementation of three recently proposed objective approaches for Landslide Susceptibility Zonation (LSZ) and two new approaches for Landslide Risk Assessment (LRA). The efficacy of the software was examined through a case study in Western Himalayan region of India. The results from the software indicate that LSZ map based on combined neural network and fuzzy approach performed exceedingly better than those produced from neural network black box approach and fuzzy relation based approaches. The landslide risk assessment maps obtained through the two new approaches implemented in this software were able to clearly depict the resource categories, which were under risk due to landslides in the region.