The increasing frequency, complexity and interconnectedness of disasters require a shift from hazard-specific approaches towards integrated multi-hazard disaster risk reduction and resilience. Interactions among hazards, exposure, vulnerability, capacity and changing climatic conditions can generate compound, cascading and systemic risks that challenge conventional risk assessment and disaster management approaches.
This session will explore how geospatial intelligence, Earth Observation, Remote Sensing, GIS, Geospatial Artificial Intelligence (Geo-AI), machine learning, digital twins, cloud computing and real-time geospatial analytics can strengthen the understanding, assessment and management of multi-hazard risks. Contributions are encouraged across the disaster risk management cycle, including hazard and risk assessment, prevention and mitigation, early warning and impact-based forecasting, preparedness, emergency response, recovery and resilience building.
The session welcomes research on multi-hazard and multi-risk assessment, hazard-exposure-vulnerability-capacity modelling, compound and cascading hazards, urban flood and drainage resilience; heatwave and climate-risk assessment, geophysical and geological hazard monitoring including landslides, permafrost and high-mountain hazards, geospatial approaches for environmental health risk assessment, multi-source Earth Observation and geospatial data fusion, multispectral, hyperspectral and InSAR-based monitoring, AI/ML and explainable AI, digital twins and decision-support systems, impact-based early warning, rapid disaster mapping and damage assessment and operational applications supporting disaster risk governance and decision-making.
The session aligns with the Sendai Framework for Disaster Risk Reduction 2015-2030, EU Disaster Resilience Goals and the UN 2030 Agenda for Sustainable Development, promoting science and technology-enabled approaches to understanding and reducing disaster risk, strengthening resilience, enhancing early warning and preparedness, and supporting risk-informed and sustainable development globally.
The session aims to connect researchers and practitioners from natural hazards, geoinformatics, Earth observation, AI/data science, climate science and disaster risk management, with emphasis on translating scientific advances into actionable, risk-informed decision support for resilient communities and infrastructure.