Highlights This paper establish a measuring method in terms of urban rail system performance based on built environment within station catchment area. This paper determined the impacting factor from built environment to urban rail ridership in Kuala Lumpur. This paper shows the spatial heterogeneity characteristic in urban rail system from built environment in Kuala Lumpur. There are limited articles to identify Kuala Lumpur urban rail system from quantitative method, which this paper supplement it and provide efficient method. This paper shows future study direction as this limitation, which will inspire myself or others continue do it.

    Abstract The urban rail system is significant for the urban transport system due to its faster, dedicated lane and mass capacity feature. Many countries or cities devout build it to relieve urban traffic pressure. In an urban rail system, the station is one of the most vital elements because directly relative to station availability and user’s accessibility. This paper identifies the urban rail station spatial heterogeneity from the built environment for passenger flow under five variables that select Kuala Lumpur as a case study. Under this foundation, this paper measures and typologies the spatial heterogeneity based on the built environment by Geographic Weighting Regression (GWR). The result indicates that selecting indicator will impact the ridership but has an apparent spatial heterogeneity because the impacting situation is different in various station catchment areas even measuring variables are the same. According to this outcome, we could tangibly recognize the urban rail system station’s built environment and the impacting factor and the specific impacting ability distribution. That benefits improving or optimizing this system more efficiently from the micro-level, generating more ridership to enhance urban rail operating performance and relieve urban traffic stress.


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    Titel :

    Identify impacting factor for urban rail ridership from built environment spatial heterogeneity


    Beteiligte:
    Yu Li, Xiang (Autor:in) / Krishna Sinniah, Gobi (Autor:in) / Li, Ruiwei (Autor:in)

    Erscheinungsdatum :

    2022-04-06


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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