AI enabled detection and warning of landslide hazard and community risk
AI enabled detection and warning of landslide hazard and community risk
Session ID#: 282484
Session Description:
Landslide detection is the first step in identifying the hazard in vulnerable slopes. While detection is the first step, going beyond detection and informing the vulnerable communities on the hazard and risk are equally important. Artificial intelligence (AI) enabled tools and methods are highly successful in warning the communities. Disaster preparedness and awareness are supported by such firsthand information that can early warn and save lives. This session aims to promote the importance of AI in detecting, identifying, estimating and early warning vulnerable settlements on landslide hazards. Abstracts that address this topic in all environments such as tropical, equatorial and cryosphere are invited. More prominence will be given to fully automated workflow that requires very little or no human intervention in hazard estimation.
Co-Sponsor(s):
- NH - Natural Hazards
Index Terms:
4313 Extreme events [NATURAL HAZARDS]
4333 Disaster risk analysis and assessment [NATURAL HAZARDS]
4337 Remote sensing and disasters [NATURAL HAZARDS]
4341 Early warning systems [NATURAL HAZARDS]
Primary Convener: Sansar Raj Meena, National Institute of Oceanography and Applied Geophysics OGS, Trieste, Italy
Conveners: Filippo Catani, University of Padova, Padova, Italy, Mr. Aadityan Sridharan, PhD, Department of Physics, Amrita Vishwa Vidyapeetham, Amritapuri, India, Kollam, India, Hemalatha Tirugnanam, Amrita University, Kollam, India and Xiaochuan Tang, CDUT Chengdu University of Technology, Chengdu, China
See more of: Earth and Planetary Surface Processes