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GIS Based Spatial Analysis of Landslide Hazard in Tehsil Balakot, KP, Pakistan
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The Himalayan region is highly susceptible to landslides due to intense rainfall and seismic activity, posing significant risks to slope stability. Due to landslides, Tehsil Balakot valley has suffered substantial damage to infrastructure, roads, and the tourism sector. This research aims to develop a landslide susceptibility map and identify hazard-prone areas to support sustainable development and mitigate risks in Balakot valley. The study employs a weighted overlay analysis using primary and secondary data raster layers, including slope, aspect, precipitation, and seismic raster maps. The slope and aspect maps are derived from a 30-meter ASTER digital elevation model, while precipitation maps are generated using Inverse Distance Weighted (IDW) interpolating data from the Pakistan Meteorological Department. Seismic data is acquired from the Geological Survey of Pakistan (GSP). The resulting landslide susceptibility map classifies the region into five hazard classes: very high, high, medium, low, and very low. The landslide susceptibility maps provide valuable insights for identifying areas at varying levels of landslide risk.
Center for Research on Poverty and Attitude (Pvt) Ltd
Title: GIS Based Spatial Analysis of Landslide Hazard in Tehsil Balakot, KP, Pakistan
Description:
The Himalayan region is highly susceptible to landslides due to intense rainfall and seismic activity, posing significant risks to slope stability.
Due to landslides, Tehsil Balakot valley has suffered substantial damage to infrastructure, roads, and the tourism sector.
This research aims to develop a landslide susceptibility map and identify hazard-prone areas to support sustainable development and mitigate risks in Balakot valley.
The study employs a weighted overlay analysis using primary and secondary data raster layers, including slope, aspect, precipitation, and seismic raster maps.
The slope and aspect maps are derived from a 30-meter ASTER digital elevation model, while precipitation maps are generated using Inverse Distance Weighted (IDW) interpolating data from the Pakistan Meteorological Department.
Seismic data is acquired from the Geological Survey of Pakistan (GSP).
The resulting landslide susceptibility map classifies the region into five hazard classes: very high, high, medium, low, and very low.
The landslide susceptibility maps provide valuable insights for identifying areas at varying levels of landslide risk.
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