Comparison of spatial modelling approaches to simulate urban growth: a case study on Udaipur city, India

Abstract

Assessment of past and future urban growth processes helps the decision makers to evaluate and formulate the policy documents. In an attempt to make such assessments, this study compares three commonly used urban growth models: Multicriteria Cellular Automata-Markov Chain (MCCA-MC), Multi-Layer Perception Markov Chain (MLP-MC), and the Slope, Land use, Exclusion, Urban Extent, Transportation and Hillshade (SLEUTH). This study has taken into account the land use and land cover data for the years, 1977, 1992, 2000, 2008, 2016 and prepared driving variables for urban growth. The KAPPA index of agreement indicates that the MCCA-MC, MLP-MC and SLEUTH models avoid errors by 94%, 93%, and 92% respectively. Models forecast that about 156.96 km₂, 157.43 km² and 142.43 km² built-up areas will emerge through the process of urbanization by 2031 in the city of Udaipur. However, this assessment identified that all the models are embodied with their own advantages and disadvantages while serving specific purposes. While the MCCA-MC and MLP-MC provides a good account of the urban spread, the SLEUTH identifies the new isolated growth centres more accurately.

Keywords:

• Urban expansion
• cellular automata
• multi-layer perception
• SLEUTH
• India

Acknowledgments

BM, SC, MP and SM are thankful to UGC NET-JRF fellowship for continuous financial support. SC and BM would like to acknowledge Andrew Vincent Bradley for his continuous help to run the SimiVal tool. SC is thankful to Anushna Banerjee for her support in manuscript editing. We would like to thank Keith C. Clarke and Mahesh Kumar Jat for the training of SLEUTH. The authors are grateful to the anonymous reviewers and the editor for their constructive comments to improve the quality of the manuscript.