Modelling urban expansion of a south-east Asian city, India: comparison between SLEUTH and a hybrid CA model

Abstract

Accurate identification of the dominant driving factors in the expansion of a city is essential for cellular automata (CA)-based urban expansion modelling. The current study aimed at analyzing the drivers of change for Vijayawada city, a tier-II developing city in south-east Asia, India and then applies them to model the future scenario of the city in a CA-based environment. Furthermore, the study also aims at comparing the efficiency of the renowned CA-based urban growth model, SLEUTH (Slope, Land use, Exclusion, Urban extent, Transportation, Hill shade), and a self-designed CA-based hybrid model developed in combination with genetic algorithm (GA) for developing future scenario of the city. The models were built, calibrated, and validated for the city using land use maps derived from temporal Landsat satellite images. Analysis of the statistical significance of the driving factors shows that the terrain and population density are the two dominant factors influencing expansion of the city. Both the models output on predicting the urban growth indicate that the available open spaces within the existing city extent gets further converted to built-up indicating infill development, and more growth occurs along the fringes of the existing city. Also, emergence of new urban centers merged with the existing city areas for predictions till 2050 and extended into the dense vegetation on the north resulting in further reduction of green cover around the city. Validation of both the models showed overall accuracy higher than 85%. The inclusion of the demographic variable and utilization of the GA ensured that the hybrid model performs better than the SLEUTH model. Analysis on the built-up densification of the cityscape showed a shift in the pattern of built-up dynamics over time. The built urban expansion scenario for Vijayawada informs urban modelers and policymakers the possible evolution of the city.