GIS-Based Multi-Temporal Analysis of Urban Expansion Dynamics in the Federal Capital Territory (FCT), Nigeria Using Sentinel-2 Imagery and Google Earth Engine

Rapid urbanisation has altered land use and land cover (LULC) in many emerging cities. This has posed issues for sustainable urban planning and environmental management. The study examined the dynamics of land use and land cover change and urban expansion of the Federal Capital Territory (FCT), Nigeria, using multi-temporal Sentinel-2 satellite images acquired for the years 2016, 2018, 2020, 2022 and 2025. Image processing and classification was done using Random Forest algorithm on Google Earth Engine (GEE) platform using spectral indices like Normalised Difference Vegetation Index (NDVI), Normalised Difference Built-up Index (NDBI), Modified Normalised Difference Water Index (MNDWI), Bare Soil Index (BSI) and Digital Elevation Model (DEM) as predictor variables. Five land cover classes were established (built-up, vegetation, agricultural land, bare land and water). The classification accuracy was tested using Overall Accuracy, Kappa Coefficient, Producer's Accuracy and User's Accuracy. The overall accuracy of the classification was 75.43%, and the Kappa coefficient was 0.693, showing a good agreement between the classified and reference data. The results revealed that vegetation was still the major land-cover class, but decreased from 4,543.49 km² in 2016 to 3,486.20 km² in 2025, whereas, agricultural land rose from 1,718.50 km² to 3,039.07 km² in the same period. The built-up land area increased from 780.67 km2 in 2016 to 1269.04 km2 in 2022 and then decreased to 572.78 km2 in 2025. However, the analysis of urban expansion found that there was about 228.48 km2 of new urban land, indicating that urban growth still existed despite classification uncertainty in the last year. The results also showed that the urban sprawl was mostly centred around the metropolitan core and the main transportation corridors and this led to changes in vegetation and agricultural land. The study concluded that the multi-temporal remote sensing approach with cloud-based geospatial analysis is a robust approach in monitoring urban expansion and landuse changes. It recommended institutionalisation of geospatial monitoring systems, better land use planning and protection of environmentally sensitive regions to assist sustainable urban development within the FCT.