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  • 标题:Developing Participatory Analytics Techniques to Inform the Prioritisation of Cycling Infrastructure
  • 本地全文:下载
  • 作者:Oliver Lock ; Christopher Pettit
  • 期刊名称:ISPRS International Journal of Geo-Information
  • 电子版ISSN:2220-9964
  • 出版年度:2022
  • 卷号:11
  • 期号:2
  • 页码:78
  • DOI:10.3390/ijgi11020078
  • 语种:English
  • 出版社:MDPI AG
  • 摘要:The planning of bicycle infrastructure across our cities remains a complex task involving many key stakeholders, including the community, who traditionally have had limited involvement in the planning process. This research develops an interactive bicycle prioritisation index tool which includes participatory spatial and textual citizen feedback. The research involves three components. Firstly, results of a survey of current cyclists in Sydney (n = 280), their current level of participation, priorities in investment in cycling and preferred locations for cycling infrastructure. This survey was undertaken between May and June 2020. Secondly, it documents the development of an interactive, digital bicycle planning tool which is informed through citizen feedback. Thirdly, it evaluates the approach in conversation with potential end-users, including government, planning practitioners, and advocacy group members. A clear preference for active participation mechanisms (86%) was articulated by current cyclists, as opposed to a reliance on the existing data available and passive data. The resulting tool was understood by interview participants and documented both existing utility and future work needed for practical implementation of similar systems. The research proposes the combination of multiple passive and active data traces with end-user evaluation to legitimise the citizen co-design of bicycle investment prioritisation initiatives. A case study approach was taken, focusing on the city of Sydney, Australia. The bicycle planning support system can be used by cities when engaging in cycle prioritisation initiatives, particularly with a focus on integrating citizen feedback and navigating the new and complex data landscapes introduced through recent, passively collected big data sets.
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