"As the world faces an increasing number of complex humanitarian emergencies - driven by conflict, violence, natural hazards, climate change, and other forces - the need for robust early warning systems to prepare and plan for rapid, effective humanitarian responses has never been more critical," said Kelly T. Clements, UN Deputy High Commissioner for Refugees.
This cutting-edge system will leverage advanced AI technologies in combination with Earth observation data to assist humanitarian actors, local authorities, and communities in identifying and assessing risks that could lead to forced displacement, enabling them to receive timely alerts prior to potential crises.
"LIST is pleased to enter this strategic collaboration with the UN Refugee Agency to develop an early warning system for emergency management. Our expertise in natural disaster management and our research outputs estimating the impact of climatic variables on human mobility and infrastructures will help provide timely and actionable insights to better anticipate and respond to critical situations," declared Lucien Hoffmann, Science Director at LIST.
Supported by Luxembourg's Ministry of Foreign and European Affairs, this initiative is designed to directly aid displaced populations by allowing responders to better predict humanitarian needs, streamline resource allocation, and reduce response times, while minimizing redundancy in relief efforts.
The project's initial phase, lasting 15 months, will see the system piloted in selected countries with components including early warning and displacement forecasting, as well as emergency preparedness measures. The second phase will integrate feedback from the rollout to develop a comprehensive global system.
This project aligns with the UN Secretary-General's prevention agenda and the Early Warnings for All initiative, which aims to provide global protection against hazardous weather, water, or climate events through early warning systems by 2027.
Related Links
Luxembourg Institute of Science and Technology
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