luyiiw/urban-sprawl-nairobi

This project uses machine learning and satellite imagery to map and analyze urban sprawl in Nairobi, Kenya. # Exploring Urban Sprawl in Nairobi, Kenya This project uses machine learning and satellite imagery to map and analyze urban sprawl in Nairobi, Kenya. As one of East Africa's fastest-growing cities, Nairobi faces challenges from rapid and unregulated expansion, especially in informal settlements like Kibera and Korogocho. In this project, we apply a supervised classification model (Random Forest) to Landsat imagery and land use maps to: - Detect and quantify urban growth - Differentiate between formal and informal settlements - Track spatial development trends over time Our goal is to support data-driven planning efforts focused on public health, infrastructure, and environmental management. **Data sources**: Landsat-5, Landsat-7, Landsat-8, and Nairobi Land Use Map **Classes**: Informal settlements, formal settlements, vegetation