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Comparison of Existing and Modified Landslides Risk Algorithms by Development of Landslide Susceptibility Models Using GIS: A Case Study of Balakot, Pakistan

This research study highlights two different existing and modified landslide risk algorithms for the development of landslide susceptibility models. The modified algorithm based landslide risk susceptibility model has highlighted such slope failures which possess the rate of very high velocity of the triggering at the local scale. The case study of this research is Balakot, one of the ruined city by the terrible earthquake induced landslide fissuring there in 2005. One of the previous landslide risk algorithm, developed by Varnes in 1984, was selected was modified by introducing additional parameters and criteria along with the modified landslide risk algorithm. The both algorithms entitled as mathematical models were incorporated in GIS (Geographical Information Systems) and were tested, compared and validated by the previous landslide occurred data, called as landslide inventory data. The statistical tests were applied to quantify various predicted regions in accordance of the verification of the predicted models. This comparison portrayed the significant difference in both models due to the notable difference due to significant control event parameters. It is assured that this research will help the decision makers by applying the modified algorithm based landslide susceptibility models in the field to avoid the landslide hazards for the future.
- Mehran University of Engineering and Technology Pakistan
- GIIS Finland
- GLOBAL INTERCONNECTION SERVICES VOF Netherlands
- Genome Institute of Singapore Singapore
- Global Inkjet Systems (United Kingdom) United Kingdom
Technology, T, Science, Q, Landslide Susceptibility, GIS, Engineering (General). Civil engineering (General), Landslide Inventory, TA1-2040, Risk Algorithm.
Technology, T, Science, Q, Landslide Susceptibility, GIS, Engineering (General). Civil engineering (General), Landslide Inventory, TA1-2040, Risk Algorithm.
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