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Titel: Estimation of internal displacement in Ukraine from satellite-based car detections
VerfasserIn: Rufener, Marie-Christine
Ofli, Ferda
Fatehkia, Masoomali
Weber, Ingmar
Sprache: Englisch
Titel: Scientific Reports
Bandnummer: 14
Heft: 1
Verlag/Plattform: Springer Nature
Erscheinungsjahr: 2024
Freie Schlagwörter: Car Detection
Satellite Imagery
Convolutional Neural Network
Crisis Response
Migration
Societal Computing
DDC-Sachgruppe: 004 Informatik
Dokumenttyp: Journalartikel / Zeitschriftenartikel
Abstract: Estimating the numbers and whereabouts of internally displaced people (IDP) is paramount to providing targeted humanitarian assistance. In conflict settings like the ongoing Russia-Ukraine war, on-the-ground data collection is nevertheless often inadequate to provide accurate and timely information. Satellite imagery may sidestep some of these challenges and enhance our understanding of the IDP dynamics. Our study thus aimed to evaluate whether internal displacement patterns can be estimated from changes in car counts using multi-temporal satellite imagery. We collected over 1000 very-high-resolution images across Ukrainian cities between 2019 and 2022, to which we applied a state-of-the-art computer vision model to detect and count cars. These counts were then linked to population data to predict displacements through ratio or non-linear models. Our findings suggest a clear East-to-West movement of cars in the first months following the war’s onset. Despite data sparsity hindered fine-grained evaluation, we distinguished a clear positive and non-linear trend between the number of people and cars in most cities, which further allowed to predict the subnational people dynamics. While our approach is resource-saving and innovative, satellite imagery and computer vision models present some shortcomings that could mask detailed IDPs dynamics. We conclude by discussing these limitations and outline future research opportunities.
DOI der Erstveröffentlichung: 10.1038/s41598-024-80035-8
URL der Erstveröffentlichung: https://www.nature.com/articles/s41598-024-80035-8
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-443932
hdl:20.500.11880/39654
http://dx.doi.org/10.22028/D291-44393
ISSN: 2045-2322
Datum des Eintrags: 14-Feb-2025
Bezeichnung des in Beziehung stehenden Objekts: Supplementary Information
In Beziehung stehendes Objekt: https://static-content.springer.com/esm/art%3A10.1038%2Fs41598-024-80035-8/MediaObjects/41598_2024_80035_MOESM1_ESM.pdf
Fakultät: MI - Fakultät für Mathematik und Informatik
Fachrichtung: MI - Informatik
Professur: MI - Prof. Dr. Ingmar Weber
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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