Associating refugee populations with climate exposure
A data analytics approach
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Abstract
Currently, the number of refugees is increasing, while the effects of climate events are worsening. Given this context, it is becoming increasingly important to understand the potential relationships between refugee movements and climate exposure, particularly at the origin and destination locations of refugees. This understanding is crucial for predicting future movements of climate-related refugees and identifying effective climate adaptation measures at both origin and destination locations.
Research on the global relationships between refugee movements and climate exposure is lacking in the current literature, especially in terms of data-driven, analytical approaches. This research addresses this gap.
The main research question of this thesis is: How is climate exposure associated with global refugee movements? To answer this, a literature review and data analytics are employed. The literature review identifies climate-related hazards that serve as inputs for the data analysis. The hazards considered in this study include droughts, sea-level rise, coastal flooding, riverine flooding, and cyclones. Various types of (possible) associations are examined using correlation analyses, regression analyses, spatial cluster identifications, and bivariate choropleth maps. All analyses consider changes over the years, specifically from 2003 to 2022.
As one of the results, this research presents an equation for relatively accurate predictions of refugees fleeing from countries in recent years, based on climate indicators while also incorporating social factors.
Moreover, the results of the study indicate that sea-level rise and riverine flooding are significantly associated with refugees fleeing from a country. Future research should explore whether this relationship could potentially be causal.
Additionally, the study identifies hotspots for different climatic conditions as well as for refugee movements (both fleeing to and from countries). The hotspots for climatic indicators and refugee movements align relatively well. Generally, climate exposure and large refugee movements are concentrated in Central-East Africa, the Middle East, and South-East Asia. These hotspots have not changed significantly over the last 20 years.
Lastly, the thesis compares top origin-destination locations of refugees at both generic (statistical) and individual (visual) levels. While statistical differences between top origin and destination locations are sometimes inconclusive, individual comparisons of countries within the same regions provide key insights into the differences in climatic exposure for refugees.
More effective climate adaptation measures can be implemented at refugee destination locations by tailoring them to specific climatic exposures, taking into account the conditions at their origin locations. Specific investments regarding adaptation measures have been identified for particular regions and countries, and these are recommended to policymakers.
The procedures and tests developed in this research can be applied to similar studies using different or newer climate and refugee data.