Modelling the Spatial Dynamics of Informal Urban Settlement Growth Using Agent-Based Simulation and Remote Sensing in Kano Metropolis

Informal settlements in Nigerian cities grow through complex spatial processes shaped by the decisions of individual actors including migrants, landlords, community leaders, and local government officials. Understanding these dynamics is essential for developing evidence-based informal settlement upgrading and prevention policies. This study develops an agent-based simulation model integrated with remote sensing data to model the spatial dynamics of informal settlement growth in Kano metropolis. Landsat and Sentinel-2 imagery from 2005 to 2023 provide an 18-year record of informal settlement expansion used to calibrate and validate the model. Agent behavioural rules are derived from in-depth interviews with 160 residents, landlords, and local government officials across three informal settlement typologies. The model simulates interactions between individual household location choices, infrastructure provision decisions, land tenure security perceptions, and regulatory enforcement capacity. Simulation outcomes over a 10-year projection period demonstrate that tenure regularisation combined with incremental infrastructure investment reduces uncontrolled expansion by 34 percent compared to the business-as-usual scenario. Keywords: agent-based model, informal settlement, Kano, remote sensing, urban dynamics