Climate-Induced Migration in Africa and Beyond: Big Data and Predictive Analytics (CLIMB)

What is the project about?

Climate change (interlinked with humanitarian crises and other economic and health factors) could lead to internal resettlements, international migration, and other (new) forms of human mobility. However, the empirical link between various climatic conditions and migration outcomes is highly contested, and, to date, no unified theoretical approach can adequately capture the complexity and contextual dependency of climate-induced migration. To address this gap, CLIMB seeks to develop a holistic approach which will allow us to better understand the mechanisms and pathways underlying the climate-migration nexus, and to predict temporal-spatial mobility patterns in Africa and beyond. Specifically, we will investigate how climate change may intersect with conflicts, poverty, and epidemics, among other adversities, and how these forces may operate in tandem in driving human migration, with a special focus on Africa.

The project's research questions

Climate risks are more likely to affect mobility within administrative areas/countries than cross-border migration. As a result, macro analyses of cross-country migration flows tend to find small and very uncertain climate impact on human mobility. Rather than aiming for a global study, CLIMB will adopt a bottom-up approach: collecting timely and granular data on specific cases where the climate-migration nexus can be more apparent, both conceptually and empirically. As a starting point, our first case study will focus on Senegal for two reasons. First, the country is projected to experience more extreme weather events which could force up to one million people to move by 2050. It also suffers from poverty, inequality, conflict and epidemics. Second, call data records (CDR) data provided through partnership with Sonatel (the principal telecommunications provider of Senegal) offers a unique opportunity to study mobility patterns at a high resolution.

In addition to leveraging CDR, CLIMB will also make use of earth observation (EO) and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process from a multi-stage perspective (e.g. from initial displacement to onward/return migration), hence gain more insights about the temporality of climate-induced migration. It will also allow us to better understand how migratory processes are shaped by multi-level (macro, meso, and micro) factors: climate risks, socio-economic crises, public opinion, social networks, and human perceptions, aspirations and capabilities, among others.

Participating institutions/universities

Consortium Lead: Malmö University (MAU), SWE

Consortium Partner:

• Harvard University (HU), USA
• Paris-Lodron-University Salzburg (PLUS), AUT
• IDEMA, TUR
• Data-Pop Alliance (DPA), USA
• Initiative Prospective Agricole et Rurale (IPAR), SEN

The CLIMB consortium consists of world leading scholars from data science, statistics, geography, earth observation, sociology, political science, and demography. The consortium also comprises top research institutes, including the department of Geoinformatics Z_GIS at the Paris Lodron University of Salzburg (PLUS), and the Institute for Quantitative Social Science (IQSS) and Center for Geographic Analysis (CGA) at Harvard University (HU). These institutes will contribute to the project with their state-of-the-art technologies and infrastructures. For example, Z_GIS will deploy the cutting-edge geospatial technologies for disaster risk reduction, climate change adaptation, humanitarian response, as well as hybrid AI approaches to foster the exploitation of Big EO data. CGA will process a dedicated Twitter data collection and Meta (formerly Facebook) data using Harvard’s High-Performance Computing (HPC) cluster. IQSS will bring a state-of-the-art forecasting system for asylum-related migration. It will also offer a world’s leading repository platform (Harvard Dataverse), which will be a key infrastructure to store and share CLIMB’s codes, datasets, papers, among other research outputs.

Links to the project participants' websites

Data-Pop Alliance External link.

Harvard University External link.

Ipar External link.

Malmö University External link.

Der Fachbereich Geoinformatik – Z_GIS External link.