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Climate-Induced Migration: Big Data & Predictive Analytics - CLIMB

CLIMB seeks to address this gap by leveraging multi-level big data: from satellite imageries to mobile phone records, and social media, among other digital traces. We will also combine Big Data and traditional survey and official statistics. This holistic data-driven approach will allow us to better understand the multi-stage process of human migration (from initial displacement to onward/return migration), and to conduct a predictive analysis of climate-induced migration.

As climate risks are more likely to affect internal mobility, we will adopt a bottom-up approach: instead of aiming for a global study, CLIMB will collect timely and granular data on specific cases where the climate-migration nexus is more apparent. As a starting point, our first case study will focus on Senegal whereby more frequent onset extreme weather is expected in the coming decades. Such deteriorating climate conditions coupled with poverty, inequality, and conflict, are likely to cause millions of people forcibly displaced.

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