send mail to support@abhimanu.com mentioning your email id and mobileno registered with us! if details not recieved
Resend Opt after 60 Sec.
By Loging in you agree to Terms of Services and Privacy Policy
Claim your free MCQ
Please specify
Sorry for the inconvenience but we’re performing some maintenance at the moment. Website can be slow during this phase..
Please verify your mobile number
Login not allowed, Please logout from existing browser
Please update your name
Subscribe to Notifications
Stay updated with the latest Current affairs and other important updates regarding video Lectures, Test Schedules, live sessions etc..
Your Free user account at abhipedia has been created.
Remember, success is a journey, not a destination. Stay motivated and keep moving forward!
Refer & Earn
Enquire Now
My Abhipedia Earning
Kindly Login to view your earning
Support
Context: Indian Institute of Technology Delhi has made the first high-resolution landslide susceptibility map for India and the map data is available for free.
In late 2023, torrential rain during the northeast monsoon triggered heavy floods and landslides in multiple States in India, killing hundreds of people.
It highlights the need for a national landslide susceptibility map to identify the most dangerous areas and help allocate resources for mitigation strategies better.
The team from IIT Delhi built a national landslide susceptibility map that uses the latest data and data collection and mapping techniques.
High Resolution: The map, could plot the susceptibility at a resolution of 100 m.
Identified Region: The map acknowledged some high landslide susceptibility, like parts of the foothills of the Himalayas, the Assam-Meghalaya region, and the Western Ghats.
New Insight: It also revealed some previously unknown places with high risk, such as some areas of the Eastern Ghats, north of Andhra Pradesh.
Data Challenges: Unlike floods, landslides in India are more localized and affect only about 1-2% of the country. Tracking and studying them is difficult due to the scarcity of high-quality data.
Data Collection: Graduate students collected data on nearly 1.5 lakh landslide events from sources including the Geological Survey of India (GSI) and other global databases.
Factors Considered: Sixteen landslide conditioning factors were identified, including soil cover, tree density, and proximity to roads or mountains.
Utilizing Latest Techniques: The research aimed to not only use available data but also incorporate state-of-the-art techniques.
Ensemble Machine Learning: Using ensemble machine learning methods, the researchers analyzed 150,000 data points for known landslide events and the 16 identified factors.
Resolution and Coverage: The resulting high-resolution map, named the 'Indian Landslide Susceptibility Map,' covered the entire country with a resolution of 100 m, estimating susceptibility for each 100 sq. m parcel.
Known and Unknown Susceptibility: The map confirmed known high-risk regions like the Himalayan foothills but also revealed previously unknown vulnerable areas, such as parts of the Eastern Ghats.
Policy Implications: The map is expected to assist policymakers in assessing vulnerability and formulating effective mitigation measures.
Early Warning System: Building on the map, the researchers aim to develop a 'Landslide Early Warning System' for India.
Infrastructure Vulnerability Map: In addition to the landslide map, efforts are underway to create an infrastructure vulnerability map depicting areas susceptible to landslides.
Online Availability: The map is available online for public access, providing a user-friendly interface for exploring regions of interest.
Community Engagement: Encouraging people to utilize the data, the researchers emphasize the map's accessibility without requiring technical knowledge.
Definition of Landslide: It is a movement of a mass of rock, earth or debris down a slope.
Landslide Prone Regions: The regions with fewer trees, closer to road-building activity, and steeper local slopes are more unstable and prone to landslides.
Causes: They can occur on many types of terrain given the right conditions of soil, rock, geological structure, drainage and slope.
Natural Causes: Rainfall, undercutting of slopes due to flooding or excavation, earthquakes, snowmelt etc.
Anthropogenic Causes: Overgrazing by cattle, terrain cutting and filling, excessive development, etc.
For example, land use changes lead to deforestation and exposure of slopes cut for the development of a key railway project likely contributed to a deadly landslide in the western Manipur in 2022.
Debris Flow: It is a form of rapid mass movement in which a combination of loose soil, rock, organic matter, and slurry flows downslope. They are commonly caused by intense precipitation or rapid snow melt.
Earth Flow: It is a downslope viscous flow of fine-grained material saturated with water.
Mudflow: A mudflow is a wet or viscous fluid mass of fine and coarse-grained material that flows rapidly along drainage channels.
Creep: Creep is the slow, steady, downward movement of material under gravity that occurs in a large area.
The creation of India's first national landslide susceptibility map represents a significant leap in understanding and addressing the unique challenges posed by landslides.
With applications ranging from early warning systems to infrastructure planning, the map is poised to play a crucial role in mitigating the impact of landslides across the country.
By: Shubham Tiwari ProfileResourcesReport error
Access to prime resources
New Courses