Modelling differential urban growth dynamics for growth decentralisation: a study on Tiruchirappalli metropolitan and sub-tier towns, India

K. Prakash (), R. Jegankumar () and R. S. Libina ()
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K. Prakash: Bharathidasan University
R. Jegankumar: Bharathidasan University
R. S. Libina: Bharathidasan University

Asia-Pacific Journal of Regional Science, 2023, vol. 7, issue 4, No 7, 1221 pages

Abstract: Abstract Urbanisation requires careful planning and monitoring to overcome challenges like overpopulation, inadequate housing, and sanitation. Significant investments are necessary to reorganise urban areas or promote sub-tier urban centres as an approach of growth decentralisation. This study examined urban growth dynamics in Tiruchirappalli and surrounding sub-tier urban centres within a 40-km radius between 1996, 2008, and 2020. Researchers produced highly accurate land use/cover maps using unsupervised classification techniques and simulated these maps using a CA–Markov model powered by an Artificial Neural Network (ANN) that uses Multi-Layer Perceptron (MLP) algorithm to predict land use changes for the years 2035 and 2050. Statistical methods have quantified land use/cover change rate, growth deviation, and degree of freedom/diversity to explain urban built-up growth dynamics. The CA-Markov simulations show that urban built-up areas are likely to remain the major land use for potential growth, with 174.9 sq. km and 209.3 sq. km in 2035 and 2050, respectively. Urban built-up was the leading class in terms of growth between 1996–2008 and 2008–2020, and growth deviation was high in multiple zones of Tiruchirappalli and Thiruverumbur, indicating significant variation between observed and expected growth rates. The degree of disparity showed a decreasing trend between 1996–2008 and 2008–2020, with higher disparity values recorded in Tiruchirappalli and Thiruverumbur than other urban centres due to the global recession and fiscal policies. At the current rate of growth, Tiruchirappalli urban may experience a significant loss of agricultural land and environmental damage from urban pollutants in surrounding water bodies and fertile lands. The study emphasizes mutual growth of sub-tier urban centres, as suggested by the Indian planning body (NITI Aayog), is a significant intervention to address the negative impacts of urban spatial growth.

Keywords: Hierarchical classification; Differential urbanisation; Machine learning; CA-Markov chain; Spatial statistics (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s41685-023-00301-x

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