Mapping Africa’s Cities Block by Block: A Data Revolution for Sustainable Development
Ten key theses in English
Джерело: phys.org
- Unprecedented dataset – Researchers at the University of Chicago analyzed 415 million buildings across 50 sub-Saharan African countries, creating the most complete urban dataset for the region.
- Focus on infrastructure gaps – The study identifies where nations lack “last mile” infrastructure such as street access, sanitation, and public services, crucial for development.
- Street access as a development marker – Every building in developed cities connects to a street, but in rapidly growing African cities, informal settlements often lack this basic connection.
- Localization approach – The project demonstrates that development can be measured down to the block level, allowing targeted interventions for specific neighborhoods.
- Million Neighborhoods Africa map – An interactive mapping tool combines building census data, OpenStreetMap streets, and demographic statistics, enabling block-level insights for cities from Lagos to Nairobi.
- Complexity metric (k value) – Each block’s “complexity” measures how many buildings separate the least accessible home from the nearest street. Well-planned blocks have k=1–2, but the regional average is k=8.
- Development correlation – Higher block complexity correlates with lower human development indicators across 67 measures, including health, education, housing, and literacy.
- Hidden inequalities – The map reveals not only peri-urban slums but also small, high-complexity pockets inside developed cities, showing overlooked infrastructure deficits.
- Practical applications – Open-source tools and standardized methods allow governments, NGOs, and planners to extend this model globally and guide policies for equitable urban growth.
- Broader vision – The research shows how urban science and big data can accelerate sustainable development, improve prosperity, and integrate disconnected communities while respecting local culture and history.
2025-09-18 12:09:39