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Urban Expansion Simulation Based on Various Driving Factors Using a Logistic Regression Model: Delhi as a Case Study

Author

Listed:
  • Muhammad Salem

    (Faculty of Urban and Regional Planning, Cairo University, Giza 12613, Egypt
    Faculty of Human-Environment Studies, Kyushu University, Fukuoka 819-0395, Japan)

  • Arghadeep Bose

    (Department of Geography & Applied Geography, University of North Bengal, Raja Rammohunpur 734013, West Bengal, India)

  • Bashar Bashir

    (Department of Civil Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Debanjan Basak

    (Department of Geography & Applied Geography, University of North Bengal, Raja Rammohunpur 734013, West Bengal, India)

  • Subham Roy

    (Department of Geography & Applied Geography, University of North Bengal, Raja Rammohunpur 734013, West Bengal, India)

  • Indrajit R. Chowdhury

    (Department of Geography & Applied Geography, University of North Bengal, Raja Rammohunpur 734013, West Bengal, India)

  • Abdullah Alsalman

    (Department of Civil Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Naoki Tsurusaki

    (Faculty of Human-Environment Studies, Kyushu University, Fukuoka 819-0395, Japan)

Abstract

During the last three decades, Delhi has witnessed extensive and rapid urban expansion in all directions, especially in the East South East zone. The total built-up area has risen dramatically, from 195.3 sq. km to 435.1 sq. km, during 1989–2020, which has led to habitat fragmentation, deforestation, and difficulties in running urban utility services effectively in the new extensions. This research aimed to simulate urban expansion in Delhi based on various driving factors using a logistic regression model. The recent urban expansion of Delhi was mapped using LANDSAT images of 1989, 2000, 2010, and 2020. The urban expansion was analyzed using concentric rings to show the urban expansion intensity in each direction. Nine driving factors were analyzed to detect the influence of each factor on the urban expansion process. The results revealed that the proximity to urban areas, proximity to main roads, and proximity to medical facilities were the most significant factors in Delhi during 1989–2020, where they had the highest regression coefficients: −0.884, −0.475, and −0.377, respectively. In addition, the predicted pattern of urban expansion was chaotic, scattered, and dense on the peripheries. This pattern of urban expansion might lead to further losses of natural resources. The relative operating characteristic method was utilized to assess the accuracy of the simulation, and the resulting value of 0.96 proved the validity of the simulation. The results of this research will aid local authorities in recognizing the patterns of future expansion, thus facilitating the implementation of effective policies to achieve sustainable urban development in Delhi.

Suggested Citation

  • Muhammad Salem & Arghadeep Bose & Bashar Bashir & Debanjan Basak & Subham Roy & Indrajit R. Chowdhury & Abdullah Alsalman & Naoki Tsurusaki, 2021. "Urban Expansion Simulation Based on Various Driving Factors Using a Logistic Regression Model: Delhi as a Case Study," Sustainability, MDPI, vol. 13(19), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10805-:d:645780
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    References listed on IDEAS

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