Landslides are unforeseen natural disasters that have an impact on the infrastructure objects, geological, morphological, environment and human lives. Researchers claim that mountainous regions are highly vulnerable to landslide due to geo-climatic conditions along with drainage, Land Use and Land Cover (LULC) and other factors such as topography and slope stability. Thus it is vital to predict landslides to reduce loss due to hazards. The present work has been carried out for the rain-fed regions of Brahmur, Chamba and Dalhousie which are most prone to landslide incident especially during the monsoon seasons. The factors of interest include slope, rainfall intensity and LULC from Landslide Disaster Management Bhuvan dataset. The data is converted into binary format using Retrofit Hypertext Transfer Protocol (HTTP) library, for calibration using Google Script Object Notation (GSON). The calibrated values are plotted on a graph using MP Android Chart Library to determine the saturation points. Each saturation point representing the vulnerable regions is notified to Rescue Task Force (RTF) for evacuation via Short Message Service (SMS) and visualization of the vulnerable regions on the Google map.
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