Assessing internal displacement patterns in Ukraine during the beginning of the Russian invasion in 2022

Yuya Shibuya · Nicholas K.W. Jones · Yoshihide Sekimoto

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Human Mobility and Location-Based Analysis Migration and Exile Studies Evacuation and Crowd Dynamics

Abstract

Given the worldwide increase of forcibly displaced populations, particularly internally displaced persons (IDPs), it's crucial to have an up-to-date and precise tracking framework for population movements. Here, we study how the spatial and temporal pattern of a large-scale internal population movement can be monitored using human mobility datasets by exploring the case of IDPs in Ukraine at the beginning of the Russian invasion of 2022. Specifically, this study examines the sizes and travel distances of internal displacements based on GPS human mobility data, using the combinations of mobility pattern estimation methods such as truncated power law fitting and visualizing the results for humanitarian operations. Our analysis reveals that, although the city of Kyiv started to lose its population around 5 weeks before the invasion, a significant drop happened in the second week of the invasion (4.3 times larger than the size of the population lost in 5 weeks before the invasion), and the population coming to the city increased again from the third week of the invasion, indicating that displaced people started to back to their homes. Meanwhile, adjacent southern areas of Kyiv and the areas close to the western borders experienced many migrants from the first week of the invasion and from the second to third weeks of the invasion, respectively. In addition, people from relatively higher-wealth areas tended to relocate their home locations far away from their original locations compared to those from other areas. For example, 19 % of people who originally lived in higher wealth areas in the North region, including the city of Kyiv, moved their home location more than 500 km, while only 9 % of those who originally lived in lower wealth areas in the North region moved their home location more than 500 km..

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References

2009Power-Law Distributions in Empirical Data 2008Understanding individual human mobility patterns 2017United Nations High Commissioner for Refugees 2012A universal model for mobility and migration patterns 2011Migration as adaptation 2020Economic and social consequences of human mobility restrictions under COVID-19 2006International Organization for Migration (IOM)2012Predictability of population displacement after the 2010 Haiti earthquake

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2025Mobile phone data for anticipating displacements: practices, opportunities, and challenges 2025Estimating internal displacement in Ukraine from high-frequency GPS mobile phone data

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