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A multi-scale approach to data-driven mass migration analysis

Research output: Contribution to journalConference paper

Mohammed N. Ahmed, Gianni Barlacchi, Stefano Braghin, Francesco Calabrese, Michele Ferretti, Vincent Lonij, Rahul Nair, Rana Novack, Jurij Paraszczak, Andeep S. Toor

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume1831
Publication statusPublished - 2016

King's Authors

Abstract

A system for scenario analysis and forecasting of mass migration is presented. The system consists of a family of multi-scale models to address the need of responding agencies for better situational awareness, short and medium-term forecasts of migration patterns, and assess impact of changes on the ground. Such insights allow for better planning and resource allocations to address migrant needs. The analytical framework consists of three separate models (a) a global push-pull model to estimate macro-patterns, (b) a time-series prediction model for estimating future boundary conditions of crisis regions, and (c) a detailed network flow model that models population diffusion within the crisis region and allows for scenario modeling. The paper presents the framework using the European refugee crisis as a case study. In addition, overall system design, practical considerations, end-user applications, and limitations of the modeling approach are discussed.

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