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World’s Leading Landslide Experts to Gather in India for Seventh World Landslide Forum

October 9, 2026 - 6:00
World’s Leading Landslide Experts to Gather in India for Seventh World Landslide Forum

From Florence to Faridabad, the global landslide science community comes to India to advance landslide science and practice for safer, more resilient communities

India will host the World Landslide Forum for the first time, with the seventh edition of the global gathering scheduled to be held from 23–27 November 2026 in Faridabad (Delhi NCR).

Amrita Vishwa Vidyapeetham will be the host institution, placing India at the centre of an international conversation on landslide science, early warning and disaster-risk reduction. The university’s role in hosting WLF7 builds on two decades of pioneering and award-winning work in landslide detection, monitoring and early warning.

Held every three years since 2008, the World Landslide Forum (WLF) brings together scientists, engineers, practitioners and policymakers from around the world to share scientific and technical advances, exchange knowledge and strengthen collaboration in landslide disaster risk reduction. The previous edition, WLF6, was held in Florence, Italy, in 2023.

Organised under the aegis of the International Consortium on Landslides (ICL), WLF7 is being organised in collaboration with leading national and international organisations working in landslide science, disaster-risk reduction and resilience. Collaborating institutions include the Geological Survey of India (GSI), National Disaster Management Authority (NDMA), Department of Science & Technology (DST), National Institute of Disaster Management (NIDM), Indian Space Research Organisation (ISRO) and other national and international organisations.

WLF7 at a Glance

  • 700+ abstracts and full papers
  • 1,900+ authors
  • 75+ countries and regions
  • 760+ institutions
  • 1,280+ international participants

Key Dates

  • 20 October 2026 — Second Call for Abstracts deadline
  • 22 November 2026 — Pre-conference workshops
  • 23–27 November 2026 — World Landslide Forum 7, Faridabad

Global Science, Indian Context

Under the theme “Landslide Science and Practice for Safe and Resilient Communities,” WLF7 spans 6 thematic areas:

  1. Reducing landslide disaster risk
  2. Remote sensing, site investigation, monitoring and early warning
  3. Testing, modelling and mitigation techniques
  4. Landslide hazard mapping, risk assessment and management
  5. Progress in landslide science and applications
  6. Regional landslide case studies

The forum will also feature pre-conference workshops on 22 November, offering focused sessions on emerging technologies and approaches for landslide risk reduction, including AI for landslides, satellite-based monitoring from Sentinel-1 to NISAR, InSAR, digital twins, landslide prediction, early-warning systems and geospatial modelling.

Why Amrita?

Amrita brings to WLF7 two decades of pioneering work in landslide detection, monitoring and early-warning systems. Its research programme, developed since 2006, integrates deep-earth sensing, IoT networks, artificial intelligence and machine learning, field deployments, laboratory experimentation and community-based risk communication.

The University successfully deployed the world’s first wireless sensor network system for landslide detection and early warning, which was subsequently upgraded to an AI-integrated Internet of Things (IoT) system in Munnar, Kerala. At the request of the Government of India, Amrita subsequently deployed a similar system in Sikkim in the Northeast Himalayas. The applied research was initiated by the University Chancellor, Sri Mata Amritanandamayi Amma, with the aim of developing low-cost technologies for wide-area landslide monitoring and early warning to help save lives.

Amrita’s work has received national and international recognition. It has been recognised as a World Center of Excellence on Landslide Disaster Reduction under the International Program on Landslides for three consecutive periods—2017–2020, 2020–2023 and 2023–2026. Its Center for Wireless Networks and Applications also received the 2023 ADA Award for Exceptional Disaster Risk Management Intervention.

Led by Dr. Maneesha V. Ramesh, Pro Vice Chancellor, Amrita Vishwa Vidyapeetham and Director, Amrita Centre for Wireless Networks and Applications, the programme has developed IoT-enabled deep-earth sensing systems designed to detect changes within vulnerable slopes. More than 300 sensors are associated with its monitoring and early-warning work. The programme has impacted more than 5,000 lives, with researchers having visited more than 70 landslide sites across India.

“Every advancement in landslide science must ultimately help protect a life, a home or a livelihood. Inspired by our Chancellor Sri Mata Amritanandamayi Devi’s (Amma’s) vision of compassion in action, Amrita’s work in landslide early warning since 2006 has focused on bringing science, technology and community knowledge together to serve that purpose. Bringing the World Landslide Forum 7 to India for the first time gives Amrita and the International Consortium on Landslides (ICL) an opportunity to connect researchers, students, governments, industry, NGOs and communities to share knowledge, strengthen collaboration and translate science and technology into timely warnings, effective action and lasting resilience,” said Dr. Maneesha V. Ramesh.

Why Landslide Risk Reduction Matters

Landslide risk poses challenges to communities as well as critical infrastructure, including roads, railways, settlements, power infrastructure and other essential services. WLF7 will provide a platform for scientists, governments, technology providers, practitioners and other stakeholders to exchange knowledge and advance practical approaches to landslide risk reduction and resilience.

For India, WLF7 provides an opportunity to bring global expertise to the country while placing India’s growing capabilities in landslide science, early-warning technology, disaster-risk reduction and resilience on an international platform.

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