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This issue focuses on the urgency of local, inclusive, and knowledge-driven responses to extreme heat, as the region faces rising temperatures and unprecedented climate risks.

This study refines landslide risk mapping in Spiti Valley, India, using machine learning and improved sampling. It identifies high-risk zones with greater accuracy, crucial for disaster preparedness in this earthquake-prone, mountainous region.

The authors summarise a major new open-access contribution to disaster risk reduction in mountain regions, i.e., 'HiFlo-DAT' (Himalayan Flood Database for Disaster Risk Reduction), which focusses on the Kullu District, Himachal Pradesh, India.

A study in the Himalayas maps debris flow probabilities using AI models, assessing risks from rainfall, glaciers, and glacial lakes. It highlights climate-driven multi-hazard dynamics, aiding disaster planning across diverse high-altitude terrains.

This issue highlights how India is deploying parametric insurance to protect vulnerable communities from extreme heat. With rising climate risks, it stresses urgent innovation in risk transfer mechanisms, especially for women and informal sector workers.

HiFlo-DAT compiles 175 years of flood data in Kullu, India, improving DRR through historic analysis. It reveals monsoon-driven flood trends, key impact zones, and vulnerable groups, promoting data-based planning across the Himalayan region.

Study in India assessed aging bridge resilience to natural hazards. Four regions analyzed to define survival limits amid worsening conditions. Bridges’ structural safety found crucial to disaster response and infrastructure integrity.

The study adopts a multi-hazard assessment approach for telecommunications and its interconnected infrastructure systems across various geographies vis-avis mountains, plains and coasts.