A Simplified Approach for Modeling Urban Growth in Siguiri-Centre, Guinea

Background and Objective: Rapid urbanization is transforming West African landscapes, yet few studies have quantitatively assessed its spatial dynamics at the local scale. This study analyzes and models urban growth in Siguiri-Centre, Guinea, using multi-temporal Landsat imagery (1990-2020) and spatial modeling. The objective is to forecast future urban expansion by 2030 using a compact-growth framework suitable for data-scarce contexts. Materials and Methods: Landsat imagery from 1990, 2000, 2010, and 2020 was processed in Google Earth Engine for -use classification. Urban and non-urban areas were extracted and analyzed in R and ArcGIS Pro. Temporal models (linear, exponential, and compound annual growth rate) were used to project urban extent to 2030. Spatial allocation was guided by proximity-based suitability and neighborhood contiguity metrics to promote compact growth. Results: Findings indicate a fivefold increase in urban land from 1990 to 2020, primarily driven by mining and population growth. The linear trend model predicted ~170 km² of urban area by 2030. Spatial simulations revealed that growth is likely to occur contiguously along existing urban edges, reinforcing a compact development pattern. Conclusion: The results highlight the importance of proximity-driven expansion models for realistic urban forecasts in developing regions. Integrating such models into planning frameworks can help balance urban development with sustainable land management.