4.6 Article

Differences of Restorative Effects While Viewing Urban Landscapes and Green Landscapes

Journal

SUSTAINABILITY
Volume 11, Issue 7, Pages -

Publisher

MDPI
DOI: 10.3390/su11072129

Keywords

landscape evaluation; restorative landscape; urban green areas; attention restorative theory; eye-tracking

Funding

  1. basic research program through the National Research Foundation of Korea (NRF) under the Ministry of Education [2017R1D1A3B03032120]
  2. National Research Foundation of Korea (NRF)
  3. National Research Foundation of Korea [2017R1D1A3B03032120] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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Attention Restoration Theory argues that natural objects such as trees and flowers have psychological restoration effects. However, relevant studies have been mostly based on survey methods, and few of them suggest guidelines for restoration environments. This study, therefore, aims to verify the restorative effect of natural objects using eye-tracking methods and a survey regarding visual aesthetics, complexity, and the Perceived Restorativeness Scale, as well 25 various images divided into 4 types: natural scene and close view, natural scene and distant view, built scene and close view, and built scene and distant view. The analysis showed that natural scenes had a stronger positive restorative effect compared to built scenes regardless of differences in the distance. In terms of the overall landscape composition, visual characteristics such as visual aesthetics and complexity had a statistically significant relationship with restorative effect. Additionally, an eye-tracking method was found to be a valid and useful tool for studying the restorative environments by significant differences in the scan path length depending on the four types of landscape images. This study ultimately provides an overview regarding restorative design guidelines not only by using natural elements but also by considering landscape composition in terms of complexity, openness, and so on.

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