How eye-catching are natural features when walking through a park? Eye-tracking responses to videos of walks

Amati, M, Ghanbari Parmehr, E, McCarthy, C and Sita, J 2018, 'How eye-catching are natural features when walking through a park? Eye-tracking responses to videos of walks', Urban Forestry and Urban Greening, vol. 31, pp. 67-78.


Document type: Journal Article
Collection: Journal Articles

Title How eye-catching are natural features when walking through a park? Eye-tracking responses to videos of walks
Author(s) Amati, M
Ghanbari Parmehr, E
McCarthy, C
Sita, J
Year 2018
Journal name Urban Forestry and Urban Greening
Volume number 31
Start page 67
End page 78
Total pages 12
Publisher Elsevier GmbH
Abstract Since the 1960s researchers have developed a range of techniques for evaluating landscape preference. In parallel with this trend, eye-tracking technology has become cheaper, more mobile and more accurate, heralding a new era of big data capture and analysis for landscape preference. In this project our objective was to capitalise on the increasing mobility, sophistication and cheapness of eye-tracking technology to examine its utility in analysing landscape preference. In the following we describe how we eye-tracked 35 participants as they viewed walks through two different parks in the urban center of Melbourne, Australia. We show how participants dwelt on trees and bushes more than other objects. When we compared this to the time and space that objects occupy, participants overwhelmingly dwelt on artificial objects such as lamp-posts, distant buildings and benches. Overall we provide an exploration and method for analysing eye-tracking data in parks by normalising the dwell time by the content, providing a robust means of comparing different dynamic stimuli such as videos. © 2018 Elsevier GmbH
Subject Land Use and Environmental Planning
Keyword(s) Eye-tracking
Landscape appreciation
Machine learning
Park preference
DOI - identifier 10.1016/j.ufug.2017.12.013
Copyright notice © 2018 Elsevier GmbH
ISSN 1618-8667
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