Measuring view preferences in cities: a window onto urban landscapes

Mirza, Leila and Byrd, Hugh (2020) Measuring view preferences in cities: a window onto urban landscapes. Cities and Health . ISSN 2374-8834

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Measuring view preferences in cities: a window onto urban landscapes
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Landscape plays a crucial role in modern life for urban dwellers although the majority of their time is spent indoors. In this context, window view is the dominant way of connecting urban dwellers to landscapes. The visual quality of urban environments can have a great influence on the quality of life. But how can visual quality be assessed? This paper presents a novel method Active Perception Technique to measure visual preference for urban scenes. Windowscape is used as a convenient tool using graphic responses to draw from memory what landscape people recall seeing. Active Perception Technique is designed to both identify the most and least visually preferred features of urban windowscapes and to predict preference for windowscapes. Results show that natural features of urban windowscapes were preferred over built ones. However, some natural features contributed more strongly to overall preference than others. Preferences for some features were found to differ across home and workplace windowscapes. Personal association with features was also found to impact on visual preferences. Results obtained can be useful for policy makers, and planners to enhance the visual quality of built environments. Active Perception Technique may also have other uses; including examining the perceived significance of cultural features in everyday urban landscapes.

Keywords:Urban Landscape, preference, windowscape, Active Perception Technique, green infrastructure
Subjects:K Architecture, Building and Planning > K421 Urban Planning
K Architecture, Building and Planning > K100 Architecture
C Biological Sciences > C841 Health Psychology
Divisions:College of Arts > Lincoln School of Architecture and the Built Environment
ID Code:41501
Deposited On:17 Jul 2020 10:57

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