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Source- This post is based on the article “IIT Delhi team makes first hi-res landslide risk map for India” published in “The Hindu” on 4th January 2024.
Why in the News?
In the wake of severe monsoon triggered heavy floods and landslides, IIT Delhi team has developed India’s first national landslide susceptibility map.
What are the features of National Landslide Susceptibility Map?
1) The map has been devised using 1.5 lakh known landslides event from sources like Geological Survey of India (GSI) along with 16 landslide conditioning factors such as soil cover, the number of trees covering the area, and how far it is from any roads or mountains, etc.
2) The team used ensemble machine learning methods to analyse the data.
Note- Ensemble machine learning is when multiple machine learning models are used together to average out an oversize impact from any one model.
3) High resolution mapping- The map offers a detailed (100 sqm. resolution) overview of landslide susceptibility across India, including previously unrecognized areas.
4) Revealing new risk zones- It identified high landslide susceptibility in familiar areas like the Himalayan foothills, Assam-Meghalaya region, and Western Ghats. Additionally, it uncovered new high-risk zones, including parts of the Eastern Ghats north of Andhra Pradesh and Odisha.
5) Map available online- The map is accessible to the public, and anyone can engage with the data without requiring technical expertise.
What is National Landslide Susceptibility Mapping (NLSM) Programme ?
1) The Geological Survey of India initiated the Macro Scale (1:50,000) National Landslide Susceptibility Mapping (NLSM) program in 2014.
2) The goal is to map the 0.42 million sq. km landslide-prone areas across the country.
3) Aim and objectives:
a. To create a dynamic National Landslide Susceptibility Geodatabase for India.
b. To prepare GIS – based seamless Landslide Susceptibility Maps of India on 1:50,000 scale.
c. To prepare a nation-wide repository on GIS-based Landslide Inventory.
UPSC Syllabus- Miscellaneous (Disaster Management)
