PUBLICATIONS – 510 GLOBAL

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 (scroll over for links) of scientific publications (peer-reviewed, conference papers and theses) by 510 or about 510. You can also follow our Scientific Lead on ResearchGate.

THESES

IMPACT BASED FORECASTING:

TECHNOLOGY, DATA & COMMUNICATIONS:

Information diffusion in complex emergencies

MSc thesis 2019 Meijering, Jasper TU Delft Technology, Policy and Management

The role of data and information sharing when slow-onset natural disasters and conflict collide

MSc thesis 2019 Kuipers, Titia TU Delft Technology, Policy and Management

Finding impact data in humanitarian documents

MSc thesis 2019. Riezenbos, Annelies Leiden University Statistical Science fo rah life and behavioural sciences

Fair Impact-based Forecasting in Manila Bay, Philippines: Integration of the information needs of disaster managers into fair impact-based forecasting to improve emergency management

MSc thesis 2019 Benito Lazaro, Irene TU Delft Civil Engineering and Geosciences

DROUGHT:

Assessing the forecast skill of agricultural drought forecast from satellite-derived products in the Lower Shire River Basin

MSc thesis 2019 Panis, M, et al. Delft University of Technology Faculty of Civil Engineering and Geosciences

Linking Drought Forecast Information to Smallholder Farmer’s Agricultural Strategies and Local Knowledge in Southern Malawi

MSc thesis 2020 Streefkerk, Ileen et al. Delft University of Technology Faculty of Civil Engineering and Geosciences

FLOODS:

Exploring vulnerability and impact of floods in Malawi : a first step towards impact-based forecasting

MSc thesis 2018 Broeken, M., et al. NIMS – Dissertações de Mestrado em Estatística e Gestão da Informação, Universidade Nova de Lisboa.

On the predictability of flash floods and their impacts in North Malawi

MSc thesis 2019 Bucherie, A., et al. 2019 IHE Delft Institute for Water Education

FOOD SECURITY:

Modelling Food Insecurity in Ethiopia: Towards a machine learning model that predicts the transitions in food security using scalable features

MSc thesis 2019 Westerveld, J. J. L., et al. Utrecht University Faculty of Science.

Predicting rice loss due to typhoons in the Philippines

MSc thesis 2019 Boeke, S. Tilburg University. FGW. Cognitive science and artificial intelligence

AUTOMATIC DAMAGE ASSESSMENT:

Automated Building Damage Classification using Remotely Sensed Data

MSc thesis 2018 Kersbergen, Daniël TU Delft Architecture and the Built Environment; TU Delft Urbanism

COMMUNITY RISK ASSESSMENT:

The inclusion of external knowledge into a text classification model for a small dataset

MSc thesis 2019 Baeskow, L. Universiteit van Tilburg. Cognitive science and artificial intelligence 2019

Does behaviour impact the vulnerability of the Philippines community to Dengue incidence? : The Epidemic Risk and Priority Project

MSc thesis 2018 Meijerink, C. University of Twente Health Sciences

Remoteness as a proxy for social vulnerability in Malawian Traditional Authorities

MSc thesis 2017 Wilbrink, Jurg Utrecht University, Geographical Information Management and Applications (GIMA)

CASH BASED AID:

Predicting the state of local markets after natural disasters to inform humanitarian cash programs

MSc thesis Tas, A. 2019 Erasmus University

Self-Sovereign Identities for Scaling up Cash Transfer Projects.

MSc thesis Stevens, L. 2018 TU Delft

Managing registration on the blockchain: the future of identity management in humanitarian cash transfer programs?

MSc thesis Stahli, T. 2018 Graduate Institute Geneva

A Fair Distribution Algorithm for Cash Transfer Programs.

MSc thesis Bijkerk, M. 2018 University of Amsterdam

UM Self-Sovereign Digital Identity for Cash Transfers & KYC requirements in Malawi and Kenya.

MSc thesis Meyling, J.2019 Masterich Graduate School of Governance

SCIENTIFIC PUBLICATIONS

Characterising Data Ecosystems to Support Official Statistics with Open Mapping Data for Reporting on Sustainable Development Goals.

van den Homberg, M. and I. Susha (2018). ISPRS International Journal of Geo-Information 7(12)

Bridging the information gap of disaster responders by optimizing data selection using cost and quality.

van den Homberg, M., et al. (2018). Computers & Geosciences 120: 60-72.

Characterising Local Knowledge across the Flood Risk Management Cycle: A Case Study of Southern Malawi.

Šakić Trogrlić, R., et al. (2019) Sustainability 11(6)

Indigenous knowledge and early warning systems in the Lower Shire Valley in Malawi

Šakić Trogrlić, R., et al. (2019)

Multi-Hazard and Spatial Transferability of a CNN for Automated Building Damage Assessment

Tinka Valentijn, Jacoppo Margutti, Marc Homberg , Jorma Laaksonen (2020)

SCIENTIFIC ABSTRACTS / CONFERENCE PAPERS /JOURNAL PAPERS /BOOK CHAPTERS

Why we can no longer ignore consecutive disasters

Marleen C. de Ruiter Anaïs Couasnon Marc J.C. van den Homberg James E. Daniell Joel C. Gill Philip J. Ward

Towards predicting rice loss due to Typhoons in the Philippines

S. Boeke^1,4, M. J. C. van den Homberg¹, A. Teklesadik¹, J. L. D. Fabila², D. Riquet³, and M. Alimardani⁴

On the predictability of flash floods and their impacts in Northern Malawi.

Bucherie, A., et al. 2019

Combining Open Data and Machine Learning to predict Food Security in Ethiopia.

Van Der Heijden, W., et al. 2018

A framework for strengthening data ecosystems to serve humanitarian purposes.

Haak, E., et al. (2018). Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age. Delft, The Netherlands, ACM: 1-9

Science for Loss and Damage. Findings and Propositions

Reinhard Mechler, et al. 2018

Using a Dynamic Sensor Network to Obtain Spatiotemporal Data in an Urban Environment

Kersbergen, Daniël et al

Technology for Climate Justice: A Reporting Framework for Loss and Damage as Part of Key Global Agreements

Marc van den Homberg et al 2018

Characterising the data ecosystem around the SDGs for more efficient reporting.

Elenbaas, H. et al