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Joint EUAA, IOM and OECD report provides new insights on displacement from and within Ukraine
The European Union Agency for Asylum (EUAA), the International Organization for Migration (IOM) and the Organisation for Economic Co-operation and Development (OECD) have published a Joint Report on profil
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es, experiences, and aspirations of forcibly displaced people by the Russian invasion of Ukraine.
The Joint Report provides an in-depth study of the scale of displacement to EU countries and people seeking protection there, by building on initial findings derived from a June EUAA-OECD Survey.
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This report assesses the impact of the conflict in Ukraine and its implications for organized crime and security-related issues for neighbouring countries, with a focus on Moldova.
These include:
Organized crime and illicit trafficking (including trafficking in persons, drugs, arms, illicit toba
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cco, and other goods); Cybercrimes and fraud; Disinformation and propaganda; and Chemical, Biological, Radiological, and Nuclear (CBRN) threats.
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This guide aims to provide an overview of successful practice from the field for the disaster risk reduction/management practitioner interested in EWS. It presents guiding principles that will build a strong foundation for the design or strengthening of EWS at any level. It is not an operational, bu
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t a strategic, guide that insists on asking the right questions and exploring all perspectives prior even to deciding whether or not early warning is the appropriate tool for a given context.
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Data presentation is the basis for describing data and generating hypotheses for further testing. It consists of a number of methods for summarising data in order to support the identification of patterns. Data can be summarised in a number of forms, including tables or graphical representations s
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uch as graphs or maps. Effective data presentation requires an understanding of the principles introduced in this guide.
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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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