| Project Detail |
Spatial machine learning for vulnerable children monitoring
The Horizon Europe initiative is in alignment with the UN Sustainable Development Goals (SDGs). The WHO-UNICEF-Lancet Commission places special emphasis on children, recognising their pivotal role in achieving these goals, as they constitute one of the most vulnerable and marginalised groups globally. Relying solely on survey data to calculate child indicators has its limitations, as surveys may require periodic updates or may cover only specific regions within a country. The MSCA-funded SMALACI project employs satellite imagery and machine learning techniques to identify vulnerable children in countries with outdated or incomplete survey information. The overall aim is to develop tools for monitoring progress towards achieving the SDGs, crafting targeted interventions, and reducing the costs associated with poverty reduction programmes.
Horizon Europe seeks to achieve the UN’s Sustainable Development Goals (SDGs). The WHO–UNICEF–Lancet Commission suggests placing children at the center of the SDGs, because children are among the world’s most vulnerable and marginalized population. Child indicators calculated with surveys are limited because surveys can be outdated and do not cover all the regions of a country. In this context, the objective of the project is to develop a methodology to overcome this limitation and identify vulnerable young children in countries with outdated, incomplete, and low-quality survey information. The methodology is based on a spatial machine-learning analysis of child indicators and integrates 3 disciplines: child development, spatial analysis of satellite images, and machine-learning. Satellite images and households’ simulations will complement the missing or outdated information of surveys, and machine learning will identify children that could be left behind during the development process due to the intersectionality of gender with biological diversities, ethnicity, socio-economic status, and geographical location. The project will create new tools for monitoring the progress towards the SDGs and will help to formulate targeted interventions that increase the social impact and reduce the economic costs of poverty-reduction and development programs. If the project is funded, Dr. Rolando Gonzales Martinez will carry out the fellowship at the University of Groningen, under the supervision of Prof. Dr. Hinke Haisma and with support from Prof. Dr. Dimitris Ballas. A short visit to UNICEF is planned as a secondment for Dr. Gonzales Martinez, so he can work with UNICEF on improving the policy impact of the project. The transfer of knowledge between the research fellow and the host organization, the teaching activities, and the short visit to UNICEF will increase the career prospects and employability of Dr. Gonzales Martinez within and outside academia. |
