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Exploring interactions between socioeconomic context and natural hazards on human population displacement

Environmental Studies and Forestry

Exploring interactions between socioeconomic context and natural hazards on human population displacement

M. Ronco, J. M. Tárraga, et al.

This research, conducted by Michele Ronco, José María Tárraga, Jordi Muñoz, María Piles, Eva Sevillano Marco, Qiang Wang, Maria Teresa Miranda Espinosa, Sylvain Ponserre, and Gustau Camps-Valls, delves into the intricate connections between socioeconomic factors, natural hazards, and internal displacement, harnessing the power of explainable machine learning to drive impactful insights and recovery strategies.

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Playback language: English
Abstract
This paper investigates the impact of socioeconomic factors and natural hazards on internal displacement using explainable machine learning. A global database of disaster-induced displacement (2016-2021) is presented, incorporating environmental, societal, and economic factors to predict displacement per event. The study finds that displacement is primarily driven by poor household conditions and intense precipitation, highlighting differential vulnerability and providing a means for its quantification to inform mitigation and adaptation strategies.
Publisher
Nature Communications
Published On
Dec 04, 2023
Authors
Michele Ronco, José María Tárraga, Jordi Muñoz, María Piles, Eva Sevillano Marco, Qiang Wang, Maria Teresa Miranda Espinosa, Sylvain Ponserre, Gustau Camps-Valls
Tags
internal displacement
socioeconomic factors
natural hazards
machine learning
vulnerability
precipitation
mitigation strategies
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