Abstract:
Landslides can result in enormous casualties and huge economic losses in mountainous regions. In order to mitigate landslide hazard effectively, new methodologies are required to develop a better understanding of landslide hazard and to make rational decisions on the allocation of funds for management of landslide risk. In this project a Geoinformatics based landslide early warning system (GLEWS) has been developed. It is an integrated approach based on GIS (Geographical Information System) and remotely wireless sensor networks. The objectives of the study were: (1) to generate landside susceptibility map of study area using Remote Sensing and GIS techniques; (2) to integrate a wireless sensor network for establishment of real time landslide monitoring and early warning system and (3) to develop a Geospatial web portal for mapping and visualization of real time landslide hazard. The results shows that almost 43 % of study area falls in high and very high susceptible zones with slopes ≥35 degree. Sandy and clayey sand are the major soil types in our study area. Currently the prototype of a single GLEWS sensor uses 1 Arduino UNO, 1 Soil Moisture Sensor, 1 Vibration Sensor, 1 Accelerometer and 1 Radio Frequency (RF) transmitter. The system automatically acquires real time data and update on Geospatial web portal after every 10 seconds. GLEWS is a cost effective early warning system as its prototype is successfully deployed and the result are pretty good.
