后 COVID 工作偏好的城市空间质量和效用权衡评估:香港案例研究。

Qiwei Song, Zhiyi Dou, Waishan Qiu, Wenjing Li, Jingsong Wang, Jeroen van Ameijde, Dan Luo
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摘要

城市区域的形成和人口稠密地区的吸引力反映了一种空间平衡,即工人向城市活力更强但环境质量下降的地方迁移。然而,大流行病和相关的健康问题加速了远程和混合工作模式,改变了人们的地方感和对城市密度的欣赏,并改变了人们对理想生活和工作场所的看法。本研究提出了一种系统的方法,通过分析疫情过后的城市居住偏好,评估人们对城市环境质量和城市便利设施之间的权衡。通过评估街区街景图像(SVI)和城市设施数据(如公园大小),该研究从调查中收集了两种工作条件(办公室工作或在家工作)的主观意见。在此基础上,对多个机器学习(ML)模型进行了训练,以预测两种工作模式的偏好分数。鉴于在家工作偏好的复杂性,结果表明该方法能更精确地预测办公室工作模式的得分。在后流行病时代,这项研究旨在阐明如何开发一种有价值的工具,用于根据指定社区中工作-生活模式和社会概况的潜在自组织情况,推动和评估城市设计战略。
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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The evaluation of urban spatial quality and utility trade-offs for Post-COVID working preferences: a case study of Hong Kong

The formation of urban districts and the appeal of densely populated areas reflect a spatial equilibrium in which workers migrate to locations with greater urban vitality but diminished environmental qualities. However, the pandemic and associated health concerns have accelerated remote and hybrid work modes, altered people's sense of place and appreciation of urban density, and transformed perceptions of desirable places to live and work. This study presents a systematic method for evaluating the trade-offs between perceived urban environmental qualities and urban amenities by analysing post-pandemic urban residence preferences. By evaluating neighbourhood Street View Imagery (SVI) and urban amenity data, such as park sizes, the study collects subjective opinions from surveys on two working conditions (work-from-office or from-home). On this basis, several Machine Learning (ML) models were trained to predict the preference scores for both work modes. In light of the complexity of work-from-home preferences, the results demonstrate that the method predicts work-from-office scores with greater precision. In the post-pandemic era, the research aims to shed light on the development of a valuable instrument for driving and evaluating urban design strategies based on the potential self-organisation of work-life patterns and social profiles in designated neighbourhoods.

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