Together with our staff, volunteers, thesis students, interns and partners, are working hard on research that will improve the speed, quality and cost-effectiveness of humanitarian aid. Below, you can find a non-exhaustive list with scientific publications (peer-reviewed, conference papers and theses) by 510 or about 510. You can also follow our Scientific Lead on ResearchGate.
- Bucherie, A., et al. (2019). On the predictability of flash floods and their impacts in Northern Malawi. – READ HERE
- Westerveld, J. J. L., et al. (2019). Modelling Food Insecurity in Ethiopia: Towards a machine learning model that predicts the transitions in food security using scalable features (MSc thesis). Faculty of Science, Utrecht University. – READ HERE.
- Šakić Trogrlić, R., et al. (2019). Characterising Local Knowledge across the Flood Risk Management Cycle: A Case Study of Southern Malawi. Sustainability 11(6). – READ HERE
- Elenbaas, H., et al. (2018). Characterising the data ecosystem around the SDGs for more efficient reporting. – READ HERE
- Meijerink, C. (2018). Does behaviour impact the vulnerability of the Philippines community to Dengue incidence? : The Epidemic Risk and Priority Project (MSc thesis). Health Sciences MSc, University of Twente – READ HERE
- EUR Tas, A. (2019) Predicting the state of local markets after natural disasters to inform humanitarian cash programs
- Haak, E., et al. (2018). A framework for strengthening data ecosystems to serve humanitarian purposes. Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age. Delft, The Netherlands, ACM: 1-9. – READ HERE
- Van Der Heijden, W., et al. (2018). Combining Open Data and Machine Learning to predict Food Security in Ethiopia. – READ HERE
- Broeken, M., et al. (2018). Exploring vulnerability and impact of floods in Malawi : a first step towards impact-based forecasting (MSc thesis). NIMS – Dissertações de Mestrado em Estatística e Gestão da Informação, Universidade Nova de Lisboa. – READ HERE
- van den Homberg, M. and I. Susha (2018). Characterizing Data Ecosystems to Support Official Statistics with Open Mapping Data for Reporting on Sustainable Development Goals. ISPRS International Journal of Geo-Information 7(12). – READ HERE
- van den Homberg, M., et al. (2018). Bridging the information gap of disaster responders by optimizing data selection using cost and quality. Computers & Geosciences 120: 60-72. – READ HERE