Application of Space-Derived Data for Population Monitoring and Estimation in Nigeria: A Case Study of Kwara State

Abstract

planning, and sustainable socioeconomic development. In Nigeria, conventional census methodologies are characterised by high costs, lengthy implementation timelines, and recurring controversies, resulting in extended inter-censal intervals without reliable demographic data. The most recent comprehensive national census was conducted in 2006, nearly two decades ago. This study investigates the efficacy of integrating remote sensing and Geographic Information System (GIS) technologies for continuous population monitoring and estimation, using Ilorin East Local Government Area (LGA) in Kwara State as a case study. High-resolution QuickBird satellite imagery, combined with GIS-based building footprint extraction and systematic field enumeration, was employed to classify residential zones into high-, medium-, and low-density categories. Stratified sampling across 35, 25, and 15 households respectively determined average household sizes per density stratum. Population estimates were derived using an empirically validated counting formula. Results indicate estimated populations of 4,024, 1,610, and 904 inhabitants for high-, medium-, and low-density areas respectively, demonstrating a consistent positive correlation between building concentration and population density. Validation yielded an overall R² of 0.90 and a mean relative error of approximately 1.8%. The findings confirm that remote sensing and GIS provide a cost-effective, scientifically reliable framework for inter-censal demographic monitoring. The methodology offers a replicable foundation for spatial planning and urban development in Nigeria and comparable data-scarce environments.