Landslides are one of the most hazardous threats worldwide, posing significant geo-environmental challenges including loss of life, destruction of infrastructure, damage to properties, degradation of agricultural lands and impacting human society. An attempt has been made to prepare the Landslide Susceptibility Zonation (LSZ) map with the help of nineteen geospatial thematic layers using the Geospatial Frequency Ratio (GSFR) model at Idukki district of Kerala, India. The landslide inventory dataset of 1,850 landslide points was identified from historical records (NASA-Co-operative Open Online Landslide Repository (COOLR) and Google Earth dataset divided into training (1,295-70%) and testing (555-30%). The inventory data and landslide conditioning parameters are used to establish a prediction model of landslide susceptibility. The results showed that 6.22% of the district area falls under very high susceptibility while 17.9 % is categorised as having high susceptibility. Receiver operating characteristic curve (ROC) and area under the curve (AUC) are used to validate the success rate and prediction rate of landslide susceptibility. The FR model achieved the accuracy with a success rate of 0.827 and a prediction rate of 0.835 in the current study.
Chitikela et al. (Thu,) studied this question.
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