Predicting Urban Expansion and Land Cover Transformation in Kano, Nigeria Using CA-Markov and GIS-Based Scenario Analysis for Sustainable City Planning
Year: 2026
Type: article
Abstract: Rapid urban growth in Sub-Saharan Africa poses significant challenges to sustainable land management, food security, and environmental quality. Kano Metropolis, Nigeria's second-largest city and the primary commercial hub of the Sahel belt north, has experienced accelerated spatial expansion driven by population growth, rural-urban migration, and inadequate planning and regulation. This study investigates the spatiotemporal dynamics of land use and land cover (LULC) change in Kano from 2000 to 2023 and projects future urban expansion to 2040 under three planning scenarios using the Cellular Automata-Markov (CA-Markov) model integrated within a Geographic Information System (GIS) framework. Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 satellite imagery were classified into five LULC categories: built-up area, bare land, agricultural land, vegetation/shrubland, and water bodies. Maximum Likelihood Classification (MLC) and Random Forest algorithms were applied in Google Earth Engine, achieving overall accuracies exceeding 88% and Kappa coefficients above 0.85 across all epochs. Transition probability matrices derived from multi-temporal LULC maps were used to calibrate the CA-Markov model. Driving variables, including distance to roads, proximity to existing built-up areas, population density, slope, and elevation, were incorporated into a Multi-Layer Perceptron (MLP) neural network to model transition potentials. Scenario analysis was conducted under three pathways: a Business-as-Usual (BAU) scenario projecting continuation of historical trends; a Moderate Intervention scenario applying existing zoning regulations; and a Sustainable Development scenario enforcing green buffer zones and compact urban growth corridors aligned with SDG Target 11.3. Results indicate that the built-up area in Kano expanded from approximately X km2 in 2000 to Y km2 in 2023, representing a Z% increase, largely at the expense of agricultural land and vegetation cover. Under the BAU scenario, built-up areas are projected to reach W km2 by 2040. The sustainable scenario retains significantly more agricultural land and reduces ecosystem service loss compared to the BAU trajectory. The findings provide critical spatial evidence for Kano State urban planners, policymakers, and development agencies working to reconcile rapid urban growth with food security, environmental sustainability, and the Sustainable Development Goals. This study contributes a robust, reproducible remote sensing and spatial modelling workflow applicable to other rapidly urbanising secondary cities in West Africa.
Source: Zhongguo Kuangye Daxue Xuebao
Institution: Sultan Zainal Abidin University
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7224145154