Application of geo-spatial techniques and cellular automata for modelling urban growth of a heterogeneous urban fringe

Abstract

Urban growth monitoring and assessment are essential for the sustainable natural resources planning & optimum utilization and reducing the risk of problems arising from unplanned urban growth like pollution, urban heat island and ecological disturbances. Cellular Automata (CA) based modelling techniques have become popular in recent past for simulating the urban growth. Present study is aimed to evaluate the performance of the CA based SLEUTH model in simulating the urban growth of a complex and relatively more heterogeneous urban area, Ajmer city of Rajasthan (India) which is quite different as compared to areas where SLEUTH has been tested in developed countries. Seven multispectral satellite imageries spanning over 21 years have been processed and used for SLEUTH parameterisation. Results of urban growth predicted by SLEUTH has been compared with other methods of land use/land cover extraction. The study has been proved to be successful in giving significant insight into issues contributing uncertainties in forecasting of urban growth of heterogeneous urban areas.