A data-driven framework for natural feature profile of public transport ridership: Insights from Suzhou and Lianyungang, China

Tang, T. orcid.org/0000-0003-2182-6525, Gu, Z. orcid.org/0000-0002-2059-4809, Yang, Y. orcid.org/0000-0002-7970-2544 et al. (3 more authors) (2024) A data-driven framework for natural feature profile of public transport ridership: Insights from Suzhou and Lianyungang, China. Transportation Research Part A: Policy and Practice, 183. 104049. ISSN 0965-8564

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Item Type: Article
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© 2024 Elsevier Ltd. This is an author produced version of an article published in Transportation Research Part A: Policy and Practice. Uploaded in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.

Keywords: Natural features, Big data analytics, Public transport operation, Policy-making support, Green transport mode
Dates:
  • Published: 25 March 2024
  • Published (online): 25 March 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Sustainable Transport Policy (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 03 Apr 2024 09:32
Last Modified: 25 Mar 2025 01:13
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.tra.2024.104049
Open Archives Initiative ID (OAI ID):

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