Modelling Urban Growth Scenarios in Lagos Megacity Using Cellular Automata and GIS

Lagos is one of Africa's fastest-growing megacities, and projecting its future spatial growth pattern is critical for infrastructure investment and environmental planning. This study models alternative urban growth scenarios for Lagos megacity to 2040 using a Cellular Automata-Markov chain model integrated within a GIS framework. Land use and land cover data for 2005, 2013, and 2022 derived from Landsat imagery serve as model inputs for calibrating transition probability matrices. Three scenario simulations representing business-as-usual, planned containment, and accelerated growth are produced. Spatial metrics including patch density, mean patch size, and landscape shape index quantify fragmentation under each scenario. Results project that under the business-as-usual scenario, built-up land will expand by 71 percent by 2040, consuming most remaining agricultural land in the Ibeju-Lekki, Badagry, and Alimosho peri-urban zones. The planned containment scenario demonstrates that transit-oriented densification could reduce land consumption by 28 percent. Model validation against 2022 reference data achieves a Kappa coefficient of 0.81. The study provides a decision-support framework for the Lagos State Physical Planning Authority. Keywords: urban growth modelling, cellular automata, Lagos, land use change, scenario analysis