Dwelling size and usability in London: a study of floor plan data using machine learning. Issue 6 (18th August 2022)

• Record Type: Journal Article
• Authors: Özer, Seyithan; Jacoby, Sam
• Is Part Of: Building research and information. Volume 50:Issue 6(2022)
• Page Start: 694
• Page End: 708
• Publication Date: 2022-08-18
• Subjects: Dwelling size -- space standards -- machine learning -- floor plans; Building -- Periodicals; Building -- Research -- Periodicals; 690.015
• DOI: 10.1080/09613218.2022.2070452
• Languages: English
• ISSNs: 0961-3218

Abstract

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.