An integrated framework on soundscape perception and spatial experience by adapting post-occupancy evaluation methodology. Issue 1 (March 2018)

• Record Type: Journal Article
• Authors: Aburawis, Ayad A Mohamed; Dokmeci Yorukoglu, Papatya Nur
• Is Part Of: Building acoustics. Volume 25:Issue 1(2018)
• Page Start: 3
• Page End: 16
• Publication Date: 2018-03
• Subjects: Soundscape perception -- space experience -- soundscape factors -- post-occupancy evaluation -- soundscape framework; Soundproofing -- Periodicals; Architectural acoustics -- Periodicals; Acoustical engineering -- Periodicals; Acoustical engineering; Architectural acoustics; Soundproofing; Periodicals; 693.834
• DOI: 10.1177/1351010X18758478
• Languages: English
• ISSNs: 1351-010X

Abstract

The effecting factors of soundscape perception and space experience have a very close relationship. This study aims to synthesize the diversity of soundscape classifications and schemes and unify such factorial variations in order to develop an integrated framework for soundscape perception and spatial experience within a systematic review of recent progress and by adapting post-occupancy evaluation methodology. First, factors under soundscape perception and space experience are reviewed in detail and merged to form conceptual classification models. Six soundscape perception factors are formed as (1) sonic, (2) spatial, (3) temporal, (4) psychological, (5) behavioural and (6) personal. Similarly, five space experience factors are formed as (1) user, (2) usage, (3) architectural design, (4) social context and (5) physical environment. All related items in the literature are presented and the sub-items under each factor are exemplified. Second, factors under the merged conceptual models are integrated by considering occupants' experience of space regarding their variance in perception of soundscapes through acoustical post-occupancy evaluation. An adapted study design is proposed under indicative, investigative and diagnostic stages of the post-occupancy evaluation by presenting the methods, data types and factorial correlations for each stage.