Analyzing the Feasibility of Integrating Urban Sustainability Assessment Indicators with City Information Modelling (CIM)

IF 3.8 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Applied System Innovation Pub Date : 2023-03-27 DOI:10.3390/asi6020045
Adriana Salles, Maryam Salati, L. Bragança
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Abstract

Sustainability assessment methods have gained the attention between urban planners and policymakers since they promote a comprehensive view of the cities. Intelligent solutions, enabled by advances in information technologies, can accelerate progress in achieving sustainability goals. In this context, City Information Modelling (CIM) emerges as a tool to facilitate urban sustainability assessment implementation. Accordingly, the main question aimed to address in this article is whether conventional sustainability assessment tools can be adapted to the CIM framework. In this regard, this study extracts the most consensual list of indicators from four sustainability assessment methods: BREEAM-C, LEED-ND, SNTool, and SBToolPT Urban, to identify a clear set of key sustainability priorities. The selected sustainability assessment methods are pioneering and often used for performance assessment at the urban scale. Furthermore, the indicators extracted from the assessment methods are measurable and can present accurate results. The study analyses the potential of the selected indicators to be calculated in CIM. The final product of the article is identifying the indicators that are adaptable to be used in the CIM approach.
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城市可持续性评价指标与城市信息模型整合的可行性分析
可持续性评估方法促进了对城市的全面了解,因此受到了城市规划者和决策者的关注。通过信息技术的进步,智能解决方案可以加速实现可持续发展目标。在这种背景下,城市信息建模(CIM)成为促进城市可持续性评估实施的一种工具。因此,本文旨在解决的主要问题是,传统的可持续性评估工具是否可以适应CIM框架。在这方面,本研究从四种可持续性评估方法中提取了最一致的指标列表:BREEAM-C、LEED-ND、SNTool和SBToolPT Urban,以确定一套明确的关键可持续性优先事项。选定的可持续性评估方法是开创性的,经常用于城市规模的绩效评估。此外,从评估方法中提取的指标是可衡量的,可以提供准确的结果。该研究分析了CIM中计算的选定指标的潜力。文章的最终成果是确定可用于CIM方法的指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Applied System Innovation
Applied System Innovation Mathematics-Applied Mathematics
CiteScore
7.90
自引率
5.30%
发文量
102
审稿时长
11 weeks
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