Deciphering climate-induced displacement in Somalia: A remote sensing perspective

factors’ societal effects amplify, forcing people to relocate. As a result, these individuals first experience displacement within their own countries before eventually seeking refuge elsewhere. Indeed, the global population of internally displaced persons (IDPs) has steadily increased, with the 2021 Internal Displacement Index Report indicating that by the end of 2020, the num- ber of IDPs worldwide had surpassed 55 million, double the number of refugees [6]. By devel- oping a nuanced understanding of the root causes behind irregular migration and forced displacement, we can better anticipate patterns of human mobility. More importantly, we can enhance protection measures for migrants and refugees, providing them with the safety and support they need in these challenging circumstances. The field of climate-induced migration has seen significant advances in contemporary pre- dictions compared to earlier efforts, spurred by growing interest in studying environmental dynamics and mobility decisions [7–12]. Harnessing innovative data sources and cutting-edge analytics has enormous potential for data collection, consequently enhancing our understand- ing of human mobility [13, 14]. This improved knowledge can be instrumental in the develop- ment of predictive models [15, 16], understanding slow-onset processes of climate change [17], and advancing socio-economic indicator development [18]. Particularly, remote sensing technologies offer unique capacities to study the relationship between the climate change and human mobility. These technologies provide critical environ-

mental data at varying scales, elucidating the impacts of climatic indicators, such as droughts and floods, on population movements [19]. Satellite-derived data offer insights into climatic trends, including rainfall variability and temperature anomalies, alongside visualising land use changes and environmental degradation [20, 21]. The integration of these datasets with socio- economic variables can reveal patterns and hotspots of climate-induced migrations [22]. Moreover, remote sensing data, coupled with machine learning algorithms, can be used to pre- dict future migration patterns under various climate scenarios [23]. With this study, we will assess how to maximise the potential of these technologies in understanding the intricate inter- play of climate change and human displacement. Accordingly, the primary objective of this paper is to scrutinise the relationship between cli- matic factors and IDPs within the context of Somalia from 2016 to 2019. Our approach employs advanced remote sensing analytics to construct sophisticated climate indicators at a granular, district level. The structure of this article unfolds as follows: We begin with a comprehensive examination of the case of Somalia, elucidating both the environmental conditions and the historical narra- tive of migration. Subsequently, we delineate our data sources and the methodological frame- work used for creating climate indicators. In the section analysing our results, we discuss our investigation and visualise the indicators through maps to elucidate the relationship between

environmental factors and IDPs. In the conclusion, we summarise our findings and offer insights and recommendations aimed at enhancing current practices in this research domain. Environmental change and displacement in Somalia Our study focuses on Somalia due to its vulnerability to extreme climatic events, which have triggered considerable internal migration. The nation’s fragility and susceptibility stem from a combination of enduring conflicts, protracted epidemic outbreaks, erratic climatic conditions and shocks adversely affecting agriculture, livestock, and rural livelihoods, which are funda- mental for food security. Simultaneously, weak social protection systems further exacerbate the situation. The World Bank classifies Somalia as one of the world’s most impoverished countries, with approximately 70% of its population living below the poverty line, subsisting PLOS ONE Deciphering Climate-induced Displacement in Somalia: A Remote Sensing Perspective PLOS ONE | https://doi.org/10.1371/journal.pone.0304202 August 9, 2024 2 / 27 sensing analysis) can be found under the link: https://osf.io/kg9zd/ Funding: MR, BT, KR This research is supported by the European Commission through the Horizon2020 European project: “HumMingBird – Enhanced migration measures from a multidimensional perspective” (GA: 870661). https://research-and-innovation.ec.europa.eu/ funding/funding-opportunities/funding- programmes-and-open-calls/horizon-europe_en The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.