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The compendium compiles practical case studies on the use of Geospatial Artificial Intelligence (GeoAI) to enhance disaster risk reduction and emergency response across diverse geographic and institutional contexts.
The compendium features selected case studies submitted by twenty-seven Regional Su
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pport Offices (RSOs) working across Asia, Africa, Latin America, and Europe. These examples highlight how GeoAI, is being used to forecast floods, map wildfire risk, assess landslide susceptibility, monitor droughts, and support emergency response. Each project demonstrates how cloud-based platforms and machine learning tools help governments act faster and more precisely when disaster strike.
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e risk levels, propose control measures, and guide communications
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ons plan that brings together all relevant sectors, public health experts, civil society and the international community under government leadership and facilitate ownership, adoption, testing through simulation and finally successful implementation in responding to emergencies and disasters from multiple hazards.
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The manual elaborates on a wide rang of logistics management issues such as carrying assessements, procurement, storing, transporting and distribution of emergency supplies
