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Influence Area of Transit-Oriented Development for Individual Delhi Metro Stations Considering Multimodal Accessibility

Author

Listed:
  • Sangeetha Ann

    (Department of Civil Engineering, Nagoya University, Nagoya 464-8603, Japan)

  • Meilan Jiang

    (Institutes of Innovation for Future Society, Nagoya University, Nagoya 464-8603, Japan)

  • Toshiyuki Yamamoto

    (Institute of Materials and Systems for Sustainability, Nagoya University, Nagoya 464-8603, Japan)

Abstract

Understanding the influence areas for transit stations in Indian cities is a prerequisite for adopting transit-oriented development (TOD). This study provides insights into the last mile patterns for selected Delhi Metro Rail (DMR) stations, specifically, Karkardooma, Dwarka Mor, Lajpat Nagar, and Vaishali, and the extent of the influence area based on different access modes. The variation in the extent of the influence areas based on various modes and the locational characteristics of stations have been considered in this study. The last mile distances reported in the conducted survey involved the problems of rounding and heaping, and they were subjected to multiple imputation to remove the bias. The spatial extent of the influence areas for various modes was estimated based on the compound power exponential distance decay function. Further, the threshold walking distances were calculated using the receiver operating characteristic (ROC) curves. The variations were noted in the last mile distances among stations. The walking distances (mean and 85th percentile) among stations did not vary considerably; however, large variations were noted when comparing other modes. These differences in accessibility must be taken into account when considering multimodal accessibility and multimode-based TOD. The study can provide useful inputs for planning and implementing TOD in New Delhi.

Suggested Citation

  • Sangeetha Ann & Meilan Jiang & Toshiyuki Yamamoto, 2019. "Influence Area of Transit-Oriented Development for Individual Delhi Metro Stations Considering Multimodal Accessibility," Sustainability, MDPI, vol. 11(16), pages 1-23, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:16:p:4295-:d:255948
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    References listed on IDEAS

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    2. Ahmed El-Geneidy & Michael Grimsrud & Rania Wasfi & Paul Tétreault & Julien Surprenant-Legault, 2014. "New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas," Transportation, Springer, vol. 41(1), pages 193-210, January.
    3. repec:cdl:uctcwp:qt2c01z5hw is not listed on IDEAS
    4. Sangeetha Ann & Meilan Jiang & Ghasak Ibrahim Mothafer & Toshiyuki Yamamoto, 2019. "Examination on the Influence Area of Transit-Oriented Development: Considering Multimodal Accessibility in New Delhi, India," Sustainability, MDPI, vol. 11(9), pages 1-20, May.
    5. Drechsler, Jörg & Kiesl, Hans, 2014. "Beat the heap - an imputation strategy for valid inferences from rounded income data," IAB-Discussion Paper 201402, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
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    Cited by:

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    2. Jianke Cheng & Liyang Hu & Da Lei & Hui Bi, 2024. "How Bike-Sharing Affects the Accessibility Equity of Public Transit Systems—Evidence from Nanjing," Land, MDPI, vol. 13(12), pages 1-30, December.
    3. Yingqun Zhang & Rui Song & Rob van Nes & Shiwei He & Weichuan Yin, 2019. "Identifying Urban Structure Based on Transit-Oriented Development," Sustainability, MDPI, vol. 11(24), pages 1-21, December.

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