Predicting Urban Expansion Using A Patch-Generating Land Use Simulation (PLUS) Model: A Case Study of Bangalore City, India

Urban area expansion and its impact on landscape dynamics are fundamental considerations in the context of sustainable urban development. This study focuses on analyzing land use changes and predicting urban expansion in and around Bangalore City. We implement a Patch-generating Land Use Simulation (PLUS) model, which combines a land expansion analysis strategy (LEAS) and cellular automata based on multi-type random patch seeds (CARS). Through detailed simulations of various land use types, the model provides insights into land expansion dynamics. The influence of various driving factors on land use changes is determined. The model utilized land use maps from 2006 to 2016, along with associated factors to project 2022 land use demand and then employed Linear Regression method to predict short-term (2026) land use expansion/prediction map. Findings show that urban population, metro train stations and road proximity influence the urban expansion compared to other factors. With over 83% accuracy and more than 74% kappa coefficient, the model’s precision highlights its significance in comprehending the dynamics of urban land use for prospective sustainable planning.