Website:

Researcher(s):
- Sabine Vanhuysse
- Stefanos Georganos

DynEO4SLUMS

Space-time dynamics of slums and vulnerable communities exposed to multiple hazards


Description
As the growing global slum population now exceeds 1 billion, with a significantly higher prevalence in low- and middle-income countries (LMICs), there is a crucial need for monitoring the dynamics of slums, vulnerable slum communities and their exposure to multiple hazards. However, there is currently a massive spatial data gap in this domain. 'The overall scientific objective of this research project is to leverage the potential of Earth Observation (EO) and AI, and to develop innovative scalable methods to monitor and improve our understanding of the spatial evolution of slums, slum population, and exposure to multiple hazards through time. We study how EO and AI can contribute to the measurement and progress of SDG indicator 11.1.1 (Percentage of people living in Slum/Informal Settlements households (SISH)) and the priorities for action of the Sendai Framework for Disaster Risk Reduction.

Period
2025-2026

Partners
LISA-IA (ULB Laboratory of Image Synthesis and Analysis), University of Karlstad

Funding
BELSPO (STEREO IV)


 
Mis à jour le 6 janvier 2025