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Estimating urban growth in peri-urban areas and its interrelationships with built-up density using earth observation datasets

Author

Listed:
  • Dipanwita Dutta

    (Vidyasagar University)

  • Atiqur Rahman

    (Jamia Millia Islamia)

  • S. K. Paul

    (Indian Institute of Technology)

  • Arnab Kundu

    (P.R.M.S. Mahavidyalaya, Bankura University)

Abstract

Understanding the complex nature of urban dynamics, especially in the fast-growing cities of developing countries, has become crucial to the urban planners and researchers. It is also relevant from the viewpoint of smart city projects as the foundation of successful smart city lies in proper planning and urban growth analysis. In this context, the present study attempts to assess the urban expansion and land-change dynamics in and around Delhi. Multi-temporal Landsat data of 1977, 2003 and 2014 were used for analyzing the spatio-temporal pattern of built-up density, urban expansion, spatial change and their interrelationships. The annual urban expansion index of the study area reveals that it was comparatively high in Delhi National Capital Territory (NCT) during 1977–2003, but the expansion was much higher in peri-urban centers in the later period. However, the growth was not happened homogeneously across the peri-urban zones; instead, it occurred around few urban centers of peri-urban area. The annual urban expansion of Delhi NCT (2.52) was significantly less than peri-urban centers like Gurgaon (6.19) in the period, 2003–2014. Since the areas with high built-up density have little or no space for new settlement, the expansion of built-up area took place in the less dense areas. The correlation between urban expansion index and annual rate of change in built-up area shows that there is a good agreement and significant positive relationship (r ≥ 0.62) present between them. A negative correlation (r ≥ 0.92) between built-up density and urban expansion index indicates that areas with high built-up density have less potentiality to expand and vice versa.

Suggested Citation

  • Dipanwita Dutta & Atiqur Rahman & S. K. Paul & Arnab Kundu, 2020. "Estimating urban growth in peri-urban areas and its interrelationships with built-up density using earth observation datasets," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(1), pages 67-82, August.
  • Handle: RePEc:spr:anresc:v:65:y:2020:i:1:d:10.1007_s00168-020-00974-8
    DOI: 10.1007/s00168-020-00974-8
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    Cited by:

    1. Suresh Chandra & Swatantra Kumar Dubey & Devesh Sharma & Bijon Kumer Mitra & Rajarshi Dasgupta, 2022. "Investigation of Spatio–Temporal Changes in Land Use and Heat Stress Indices over Jaipur City Using Geospatial Techniques," Sustainability, MDPI, vol. 14(15), pages 1-30, July.
    2. Milad Asadi & Amir Oshnooei-Nooshabadi & Samira-Sadat Saleh & Fattaneh Habibnezhad & Sonia Sarafraz-Asbagh & John Lodewijk Van Genderen, 2022. "Urban Sprawl Simulation Mapping of Urmia (Iran) by Comparison of Cellular Automata–Markov Chain and Artificial Neural Network (ANN) Modeling Approach," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    3. Magdalena Wilkosz-Mamcarczyk & Barbara Olczak & Barbara Prus, 2020. "Urban Features in Rural Landscape: A Case Study of the Municipality of Skawina," Sustainability, MDPI, vol. 12(11), pages 1-24, June.

    More about this item

    JEL classification:

    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

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