Dwelling size and usability in London: a study of floor plan data using machine learning
Dwelling size and usability in London: a study of floor plan data using machine learning
复制标题
伦敦的住宅面积和可用性：使用机器学习对平面图数据进行研究
DOI：
--
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Sam Jacoby
中科院分区：
文献类型：
--
作者：
Seyithan Özer;Sam Jacoby
摘要基于基于机器学习的开放获取平面图数据的详细维度的住宅单元平面图(n = 2283)数据集，分析了伦敦住宅的大小和可用性。伦敦一半的住房是在第二次世界大战之前建造的，但经过了广泛的改造。由于住房市场面临更大的压力和住房规模的问题，伦敦是英格兰第一个在2011年重新引入所有住房部门空间标准的地方当局。数据显示，61%的伦敦住宅没有达到《伦敦住房设计指南》(2010)推荐的最小住宅面积标准，51%的住宅没有达到卧室标准，88%的住宅至少满足一项尺寸要求。本文量化了住宅不符合现代和历史空间标准的程度，并讨论了它们在住宅可用性和设计问题上的有效性。
ABSTRACT Based on a dataset of dwelling unit plans (n = 2283) with detailed dimensions derived from open-access plan data using machine learning, this paper analyses the size and usability of dwellings in London. Half of London’s housing stock was built before the Second World War but has been extensively modified. Due to greater pressure on the housing market and problems with dwelling size, London was the first local authority in England to reintroduce space standards for all housing sectors in 2011. Providing a first comprehensive analysis of space standards and dwelling size in London at room level and across all built periods, the data shows that 61% of London homes fail the recommended minimum dwelling sizes of the London Housing Design Guide (2010), 51% a bedroom standard and 88% at least one of the dimensional requirements. The paper quantifies the extent to which homes fail both recent and historical space standards and discusses their effectiveness in relation to dwelling usability and issues of design.