Ensuring Humanitarian Safety through Real-time Situational Awareness for Efficient Management of
Migration Movements

A challenging aspect of the HUMAN+ project is to differentiate whether movement data at hand is indicative of migration or something else. Part of the project is to understand this essential difference and to relate the findings back to the data. This aspect also ties into other research questions. Because once migration patterns patterns are identified, the next steps are to use them as a basis for future movement estimations. Finally, the resulting spatiotemporally complex information has to be visualised comprehensively, so that it can be used productively by others.
Over the last years, migration movements from areas struck by war, economical or other humanitarian crises towards Europe have intensified. These developments pose major challenges to authorities, municipalities, relief organizations, NGOs, as well as the police. Current events, including the migration wave in 2015/16 in Austria and Germany, have shown that established methods in migration management have reached their limits because rapidly available data and user-centred information for decision support to ensure humanitarian security is oftentimes lacking. The HUMAN+ project aims to remedy this situation by providing comprehensive, objective data and information about migration movements to decision makers in near real-time. As the topic at hand is not only very complex from a technical perspective, but also from social, political and ethical points of view, HUMAN+ also includes ethical, sociological and legal guidelines for the use of the highly sensitive data and information that it concerns.

The project aims to achieve three goals:

  1. Detection and prediction of migration movements, as well as identification of areas that are frequently passed during migrations.
  2. Creation of near real-time overviews about current migration movements including data analyses and short-term forecasting.
  3. Information and decision support in form of user dependent interactive information visualisation, (semi-) automated assessment of quality and interoperability.

The results of the HUMAN+ project will help to mitigate the problems that arise in the wake of large migration movements, and thus make such events more manageable for all parties involved by giving them tools which allow them to plan ahead when and where resources will be needed the most.

Key Publications
Kounadi, O., Resch, B., Petutschnig, A. (2018) Privacy Threats and Protection Recommendations for the Use of Geosocial Network Data in Research Social Sciences 7(10), 191, DOI: https://doi.org/10.3390/socsci7100191.

Petutschnig, A., Havas, C., Resch, B., Krieger, V., Ferner, C. (2020) Exploratory Spatiotemporal Language Analysis of Geo-Social Network Data for Identifying Movements of Refugees GI_Forum 2019, Volume 7, Issue 2, 137 – 152, DOI: https://doi.org/10.1553/giscience2020_01_s137.

Havas C, Wendlinger L, Stier J, Julka S, Krieger V, Ferner C, Petutschnig A, Granitzer M, Wegenkittl S, Resch B. (2021) Spatio-Temporal Machine Learning Analysis of Social Media Data and Refugee Movement Statistics ISPRS International Journal of Geo-Information, 10(8), 498, DOI: https://doi.org/10.3390/ijgi10080498.