Walking Through Complex Spatial Patterns of Climate and Conflict-Induced Displacements
David Carranza, Devansh Sharma, Francisco Malveiro, Gustavo Kohlrausch, Jisha Mariyam John, Kaloyan Danovski, Malvina Bozhidarova, Rui Zheng, Sandro Sousa

TL;DR
This paper introduces a hybrid diffusion-based method to analyze and predict complex displacement patterns caused by climate and conflict, demonstrated through a case study in Somalia.
Contribution
It presents a novel approach combining statistical diffusion processes with real displacement data to reconstruct likely migration routes and hazard exposures.
Findings
Displaced individuals mainly face droughts and conflicts along their routes.
Conflict exposure decreases as displacements progress.
No single typical exposure pattern dominates across all trajectories.
Abstract
Extreme weather events are projected to intensify global migration, increase resource competition, and amplify socio-spatial phenomena, including intergroup conflicts, socioeconomic inequalities, and unplanned displacements, among others. Addressing these challenges requires consolidating heterogeneous data to identify, estimate, and predict the dynamical process behind climate-induced movements. We propose a novel hybrid approach to reconstruct hazard-induced displacements by analysing the statistical properties of a diffusion process (walks) that explores the spatial network constructed from real displacements. The likely trajectories produced by the walks inform the typical journey of individuals, identifying potential hazards that may be encountered when fleeing high-risk areas. As a proof of concept, we apply this method to Somalia's detailed displacement tracking matrix,…
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Taxonomy
TopicsClimate Change, Adaptation, Migration · African Studies and Geopolitics · Hydropower, Displacement, Environmental Impact
