Urban transportation systems are among the key aspects of infrastructure in cities. Greenery positively influences urban environments and the experience of residents during transportation. However, existing studies have not yet established a substantial connection between the greenery visible at street level and urban transportation. In our study, we focus on the integration of social science disciplines and information technology in the context of transportation. We prioritize people’s experiences of the transportation process, placing foremost importance on the comfort of passengers themselves. We use a human perspective concept, supported using street view images, to propose a new index, the Green View Index – Urban Transportation (GVI-UT). The GVI-UT highlights the crucial role of transportation routes and modes in street greenery evaluation. It is defined according to a passenger’s ability to see greenery on the street while being transported. The GVI-UT calculation comprises four steps: obtaining street view panoramic photographs; calculating green views based on these photographs; route planning using Web application programing interfaces; and overlay analysis. This study provides a theoretical framework and a range of innovative ideas for achieving a person-centered perspective on the experience of the transportation process. Through quantitative evaluation of the green-view status of residents’ transportation options, policy recommendations for urban transportation planning and green construction are provided to promote green visibility during urban transportation. Through extracting greater information from existing street view data, we allow such data to play a more valuable role in the construction of urban transportation systems.


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    Title :

    A green view index for urban transportation: How much greenery do we view while moving around in cities?


    Contributors:
    Wu, Jie (author) / Cheng, Liang (author) / Chu, Sensen (author) / Xia, Nan (author) / Li, Manchun (author)


    Publication date :

    2020-10-01


    Size :

    18 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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