Digital Participatory Model as Part of a Data-Driven Decision Support System for Urban Vibrancy

IF 1.7 Q3 URBAN STUDIES Urban Planning Pub Date : 2023-11-22 DOI:10.17645/up.7165
Gülce Kırdar, G. Çağdaş
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Abstract

Digital participation relies on computational systems as the instruments for expert engagement, data-driven insight, and informed decision-making. This study aims to increase expert engagement with the Bayesian-based decision support model in evaluating urban vibrancy decisions. In this study, urban vibrancy parameters are defined using “economic, use, and image value” measures. This article focuses on the visual aspect of vibrancy, defined as the image value of place. The image value is evaluated through likability and likability features. The case study area is the Eminönü Central Business District in the Istanbul Historic Peninsula due to its distinctive urban dynamics derived from the duality of being a cultural and cosmopolitan city center. This research presents a method as a decision support system (DSS) model based on the Bayesian belief network (BBN) and spatial BBN for supporting urban vibrancy decisions. The spatial BBNs monitor spatial outcomes of variables’ dependencies that form through the BBN relationship network. Spatial BBN tools monitors the spatial impact of decisions for informed urban interventions. The results demonstrate that urban greening, pedestrianization, and human-scaled streetscapes should be prioritized to make streets more likable. The most significant intervention areas are Tahtakale for signboard regulation, Sultanahmet and Vefa for cultural landscape improvement, and Vefa and Mahmutpaşa for planning building enclosures. The participation is achieved by evaluating urban vibrancy with what-if scenarios using BBN. The developed DSS model addresses which parameters should be prioritized, and what are their spatial consequences. The use of spatial BBN tools presents certain limitations in terms of interoperability and user interaction. Overall, this research contributes to participatory urban planning by incorporating both conditional and spatial dependencies. This unique approach not only promotes a more holistic understanding of urban vibrancy but also contributes to the advancement of digital participation in urban planning decisions.
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数字参与式模型作为数据驱动的城市活力决策支持系统的一部分
数字参与依赖于计算系统作为专家参与、数据驱动的洞察力和知情决策的工具。本研究旨在通过基于贝叶斯的决策支持模型,提高专家在评估城市活力决策中的参与度。在本研究中,城市活力参数是通过 "经济、使用和形象价值 "来定义的。本文重点关注活力的视觉方面,即地方的形象价值。形象价值通过宜人性和宜人性特征进行评估。案例研究区域是伊斯坦布尔历史半岛的埃米诺努中央商务区,因为该区域具有文化和国际都会城市中心的双重身份,具有独特的城市活力。本研究提出了一种基于贝叶斯信念网络(BBN)和空间贝叶斯信念网络的决策支持系统(DSS)模型方法,用于支持城市活力决策。空间贝叶斯信念网络监测通过贝叶斯信念网络关系网络形成的变量依赖关系的空间结果。空间 BBN 工具可监测决策的空间影响,以采取明智的城市干预措施。结果表明,应优先考虑城市绿化、步行街和人性化的街道景观,以使街道更受欢迎。最重要的干预领域是塔赫塔卡莱(Tahtakale)的招牌管理、苏丹阿梅特(Sultanahmet)和维法(Vefa)的文化景观改善,以及维法和马赫穆特帕萨(Mahmutpaşa)的建筑围墙规划。这种参与是通过使用 BBN 评估城市活力和假设情景来实现的。开发的 DSS 模型解决了应优先考虑哪些参数及其空间后果的问题。空间 BBN 工具的使用在互操作性和用户互动方面存在一定的局限性。总之,这项研究通过纳入条件和空间依赖关系,为参与式城市规划做出了贡献。这种独特的方法不仅促进了对城市活力更全面的理解,还有助于推动数字参与城市规划决策。
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来源期刊
Urban Planning
Urban Planning URBAN STUDIES-
CiteScore
3.60
自引率
5.60%
发文量
124
审稿时长
12 weeks
期刊介绍: Urban Planning is a new international peer-reviewed open access journal of urban studies aimed at advancing understandings and ideas of humankind’s habitats – villages, towns, cities, megacities – in order to promote progress and quality of life. The journal brings urban science and urban planning together with other cross-disciplinary fields such as sociology, ecology, psychology, technology, politics, philosophy, geography, environmental science, economics, maths and computer science, to understand processes influencing urban forms and structures, their relations with environment and life quality, with the final aim to identify patterns towards progress and quality of life.
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