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News18
2 days ago
- Science
- News18
GSI plans to use AI to develop robust landslide forecasting model: DG
Kolkata, Jul 20 (PTI) The Geological Survey of India (GSI) is conducting a research programme to develop a more robust landslide forecasting model and expert system leveraging artificial intelligence (AI), an official said. This was stated by GSI Director General Asit Saha at a workshop held here on Friday to commemorate the first anniversary of the National Landslide Forecasting Centre (NLFC). 'There is ongoing research underway to develop a more robust landslide forecasting model and expert system leveraging artificial intelligence (AI)," Saha said. He also reiterated the institution's long-term vision of operationalising a nationwide Regional Landslide Early Warning System (LEWS) by 2030. The DG also said that the GSI would soon begin issuing operational landslide early warning bulletins for Rudraprayag district in Uttarakhand. Saha commended the NLFC team for expanding its landslide early warning coverage — from 16 districts across six states at its inception to 21 districts across eight states in 2025. He also highlighted NLFC's pioneering efforts in integrating global best practices into forecasting systems and the successful upgrades of the NLFC dashboard, Bhusanket portal, and Bhooskhalan App, enhancing real-time monitoring and public access to critical landslide forecasts. PTI SCH RG Disclaimer: Comments reflect users' views, not News18's. Please keep discussions respectful and constructive. Abusive, defamatory, or illegal comments will be removed. News18 may disable any comment at its discretion. By posting, you agree to our Terms of Use and Privacy Policy.
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Business Standard
2 days ago
- Science
- Business Standard
GSI plans to use AI to develop robust landslide forecasting model: DG
The Geological Survey of India (GSI) is conducting a research programme to develop a more robust landslide forecasting model and expert system leveraging artificial intelligence (AI), an official said. This was stated by GSI Director General Asit Saha at a workshop held here on Friday to commemorate the first anniversary of the National Landslide Forecasting Centre (NLFC). "There is ongoing research underway to develop a more robust landslide forecasting model and expert system leveraging artificial intelligence (AI)," Saha said. He also reiterated the institution's long-term vision of operationalising a nationwide Regional Landslide Early Warning System (LEWS) by 2030. The DG also said that the GSI would soon begin issuing operational landslide early warning bulletins for Rudraprayag district in Uttarakhand. Saha commended the NLFC team for expanding its landslide early warning coverage from 16 districts across six states at its inception to 21 districts across eight states in 2025. He also highlighted NLFC's pioneering efforts in integrating global best practices into forecasting systems and the successful upgrades of the NLFC dashboard, Bhusanket portal, and Bhooskhalan App, enhancing real-time monitoring and public access to critical landslide forecasts. (Only the headline and picture of this report may have been reworked by the Business Standard staff; the rest of the content is auto-generated from a syndicated feed.)
Time of India
2 days ago
- Business
- Time of India
GSI plans to use AI to develop robust landslide forecasting model: DG
The Geological Survey of India ( GSI ) is conducting a research programme to develop a more robust landslide forecasting model and expert system leveraging artificial intelligence (AI), an official said. This was stated by GSI Director General Asit Saha at a workshop held here on Friday to commemorate the first anniversary of the National Landslide Forecasting Centre (NLFC). Explore courses from Top Institutes in Select a Course Category Healthcare Degree PGDM Others Data Science Finance Artificial Intelligence Data Analytics others Management Data Science Project Management Digital Marketing healthcare MBA Leadership Public Policy MCA Product Management Cybersecurity Design Thinking Technology CXO Operations Management Skills you'll gain: Financial Analysis in Healthcare Financial Management & Investing Strategic Management in Healthcare Process Design & Analysis Duration: 12 Weeks Indian School of Business Certificate Program in Healthcare Management Starts on Jun 13, 2024 Get Details "There is ongoing research underway to develop a more robust landslide forecasting model and expert system leveraging artificial intelligence (AI)," Saha said. He also reiterated the institution's long-term vision of operationalising a nationwide Regional Landslide Early Warning System (LEWS) by 2030. The DG also said that the GSI would soon begin issuing operational landslide early warning bulletins for Rudraprayag district in Uttarakhand . Live Events Saha commended the NLFC team for expanding its landslide early warning coverage - from 16 districts across six states at its inception to 21 districts across eight states in 2025. He also highlighted NLFC's pioneering efforts in integrating global best practices into forecasting systems and the successful upgrades of the NLFC dashboard, Bhusanket portal , and Bhooskhalan App, enhancing real-time monitoring and public access to critical landslide forecasts.
Time of India
4 days ago
- Climate
- Time of India
On first anniv, GSI's landslide-forecast unit promises nation-wide cover by '30
Kolkata: From sudden flash floods to fast-moving boulders cascading down mountain slopes, the Geological Survey of India's (GSI) National Landslide Forecasting Centre (NLFC) has been quietly making a life-saving difference. Marking its first anniversary, the centre on Friday celebrated a year of critical interventions at a workshop held at the Dharitri Building in Salt Lake, Kolkata. With India witnessing one of the highest rates of rainfall-induced landslides globally, NLFC's efforts are increasingly vital. GSI's long-term vision includes establishing a fully operational, nationwide Regional Landslide Early Warning System (LEWS) by 2030. The NLFC now regularly issues early-warning bulletins for landslide-prone regions, like Darjeeling and Kalimpong in Bengal, and the Nilgiris in Tamil Nadu, significantly enhancing the safety of both residents and tourists. Inaugurating the workshop, GSI director general Asit Saha announced that the system will soon be operational in Rudraprayag district of Uttarakhand, further extending its coverage in vulnerable Himalayan regions. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like No annual fees for life UnionBank Credit Card Apply Now Undo "In just one year, NLFC grew from covering 16 districts in six states to 21 districts in eight states. This is a remarkable leap in our mission to protect lives and property from landslide hazards," said Saha. He lauded the NLFC's pioneering work in integrating global best practices and upgrading digital tools, like the NLFC dashboard, Bhusanket portal, and Bhooskhalan app, to enhance real-time monitoring and public accessibility. You Can Also Check: Kolkata AQI | Weather in Kolkata | Bank Holidays in Kolkata | Public Holidays in Kolkata Priyanka Singla, special secretary of the West Bengal State Disaster Management Authority (WBSDMA), underscored the need for robust inter-agency coordination. She commended GSI's role in operationalising forecast systems in Kalimpong and Darjeeling, and affirmed the state's commitment to integrate scientific forecasts into ground-level disaster response. While highlighting the importance of predictive alerts, geologists also raised a crucial concern: "If the system issues a red alert in a densely populated hilly town like Darjeeling, are we ready with evacuation plans? Where will people go?" Their worry pointed to the need for comprehensive evacuation strategies to follow timely warnings. The event brought together senior officials from NDMA, IMD, ISRO's NRSC, state disaster management bodies, academic institutions, and industry experts. Technical sessions showcased recent advancement in landslide sensor technology, AI-based forecasting models, and strategic roadmaps for risk mitigation.
