Modelling urban dynamics in rapidly urbanising Indian cities

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Abstract

Metropolitan cities in India are emerging as major economic hubs with an unprecedented land use changes and decline of environmental resources. Globalisation and consequent relaxations of Indian markets to global players has given impetus to rapid urbanisation process. Urbanisation being irreversible and rapid coupled with fast growth of population during the last century, contributed to serious ecological and environmental consequences. This necessitates monitoring and advance visualisation of spatial patterns of landscape dynamics for evolving appropriate management strategies towards sustainable development approaches. This study visualises the growth of Indian mega cities Delhi, Mumbai, Pune, Chennai and Coimbatore, through Cellular Automata Markov model considering the influence of agent(s) of urban growth through soft computing techniques. CA Markov model is considered to be one of most effective algorithm to visualise the growth of urban spatial structures. Prediction of growth using agent based modelling considering the spatial patterns of urbanisation during the past four decades has provided insights to the urban dynamics. The industrial, infrastructural, socio-economic factors significantly influence the urban growth compared to the biophysical factors. Visualisation of urban growth suggest agents driven growth in the cities and its surroundings with large land use transformations in urban corridors and upcoming Industrial and ear marked developmental zones. Integrating local agents of urban growth help in identifying specific regions of intense growth, likely challenges and provide opportunities for evolving appropriate management strategies towards sustainable cities during the 21st century.

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Bharath, H. A., Chandan, M. C., Vinay, S., & Ramachandra, T. V. (2018). Modelling urban dynamics in rapidly urbanising Indian cities. Egyptian Journal of Remote Sensing and Space Science, 21(3), 201–210. https://doi.org/10.1016/j.ejrs.2017.08.002

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