Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
NH6.8 | Accelerating Early Response to Natural Hazards from Space: Leveraging Digital Twins of the Earth
Accelerating Early Response to Natural Hazards from Space: Leveraging Digital Twins of the Earth
Convener: Panagiotis Elias | Co-conveners: Salvatore Stramondo, Arnau Folch, Claudia Corradino
Multi-hazards —simultaneous or successive natural and anthropogenic events—cause escalating human, economic, and environmental losses, threatening societal resilience. Within this context near-real-time monitoring via satellite Earth Observation (EO) is critical for effective crisis management. Currently the low repeatability/reoccurrence of EO satellites combined with latency due in data downlink, processing, analysis and delivery currently limits their explotability during crises
To address these challenges, the emerging trend of deploying EO satellite swarms to reduce revisit times highlights the need to address critical gaps and accordingly enhance various components by integrating advanced technological solutions
This session invites studies presenting innovative approaches to optimize Earth Observations (EO) using satellite swarms and near future microwave (SAR) geostationary satellites for rapid, dense, continuous data streams. Explainable AI accelerates human intervention and automates decision making for satellite tasking and acquisition, processing methodologies, product scalability and customization for proper target groups. Additionally, quantum-centric computing, though not yet practical, holds significant promise for impactful reducing processing latency in the near future.
Digital Twins of the Earth complement these advancements by enabling proactive risk assessment, scenario modeling, and optimized resource allocation, thereby improving early response strategies.
The session fosters collaboration among geoscientists, engineers and disaster managers. It aims to revolutionize multi-hazard resilience through integrated, AI-enhanced space with dynamic, high-fidelity virtual models of the planet targeted on early response.