Forecasting Long-Term Urban Growth Patterns and Drivers in West African Secondary Cities: A Case Study of Uyo, Nigeria (2025–2050) - Nnam, V. C.; Ikwueze, U. H.; Okon, G. J. (Journal of Spatial Information Sciences, 2026)
Secondary cities in West Africa are the new frontiers of global urbanization, yet they often lack the long-term spatial foresight needed for sustainable growth. In Uyo, Nigeria, rapid demographic shifts are putting unprecedented pressure on land resources, necessitating a shift toward predictive urban modeling. This study utilizes an integrated MLP-Markov chain model to simulate urban growth for the years 2035 and 2050. A Logistic Regression model was first employed to identify spatial drivers, revealing that proximity to major roads and elevation were the primary determinants of expansion. The resulting projections were then evaluated using the SDG 11.3.1 (Land Use Efficiency) framework, comparing projected built-up expansion against a UN-validated population growth rate of 4.32%. The simulation predicts that Built-up areas will expand to 106.58 km² (58.06%) by 2035 and 118.47 km² (64.54%) by 2050. The LCRPGR ratio is projected to drop to 0.20 by 2050, indicating that while land use is "efficient" in per-capita terms, the city is facing extreme hyper-densification. The findings serve as a spatial early-warning system, advocating for a transition from horizontal sprawl management to inclusive vertical densification and the preservation of remaining ecological corridors to ensure Uyo’s long-term resilience.
Keywords: Urban Forecasting; MLP-Markov; Land Use Efficiency; Logistic Regression; Hyper-densification