Multi-Scale Effects of Landscape Pattern on Soundscape Perception in Residential Green Spaces

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Jiang Liu
  • Yijun Huang
  • Zhu Chen
  • Xin Chen Hong

Research Organisations

External Research Organisations

  • Fuzhou University
  • Technische Universität Braunschweig
  • Southeast University (SEU)
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Details

Original languageEnglish
Article number2323
JournalForests
Volume14
Issue number12
Publication statusPublished - 27 Nov 2023

Abstract

Soundscape quality in green spaces of residential areas directly contributes to residents’ quality of life. It has close relationships with landscape characteristics, which should be considered in landscape planning and design processes in residential areas. Accordingly, this study proposed a new perspective on the interrelationships between soundscape perception and landscape pattern on multi-scale, based on a case study of 30 residential green spaces in Fuzhou, China. Percentage of Landscape (PLAND), Patch Density (PD), Landscape Shape Index (LSI), and Patch cohesion index (COHESION) were utilized to represent the landscape pattern of vegetation, buildings, and roads in the residential areas. Soundscape perception was interpreted using the sound dominant degree (SDD) of sound sources and overall soundscape quality. The examined spatial scales range from 20 m to 180 m, with concentric circles spaced 20 m apart for each sampling point. Correlation analyses indicated that most landscape indices of vegetation and buildings were correlated with these soundscape perception indicators, while limited landscape indices of roads were associated with them. Based on the multi-scale landscape indices, multiple linear regression models for the SDD of sound sources and overall soundscape quality were established, confirming that the scale effect of landscape patterns can affect soundscape perception. Expressly, results indicated that these models were chiefly influenced by the landscape indices at a scale less than 120 m, but the scale effect of landscape pattern on the SDD of birdsong, pleasantness, and quietness was not so evident. Furthermore, we found that the number of explanatory variables may somewhat affect the model performance. The overall interpretability of these landscape indices for the SDD of sound sources was better than that of overall soundscape quality, implying the complexity of the latter. This study offers a fresh insight into the relationship between landscapes and soundscapes at varying scales. The findings can provide useful information for the promotion strategies of landscapes and soundscapes, especially in residential green spaces.

Keywords

    green space, landscape pattern, residential area, scale effect, sound dominant degree, soundscape quality

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Forestry

Cite this

Multi-Scale Effects of Landscape Pattern on Soundscape Perception in Residential Green Spaces. / Liu, Jiang; Huang, Yijun ; Chen, Zhu et al.
In: Forests, Vol. 14, No. 12, 2323, 27.11.2023.

Research output: Contribution to journalArticleResearchpeer review

Liu J, Huang Y, Chen Z, Hong XC. Multi-Scale Effects of Landscape Pattern on Soundscape Perception in Residential Green Spaces. Forests. 2023 Nov 27;14(12):2323. doi: 10.3390/f14122323
Liu, Jiang ; Huang, Yijun ; Chen, Zhu et al. / Multi-Scale Effects of Landscape Pattern on Soundscape Perception in Residential Green Spaces. In: Forests. 2023 ; Vol. 14, No. 12.
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title = "Multi-Scale Effects of Landscape Pattern on Soundscape Perception in Residential Green Spaces",
abstract = "Soundscape quality in green spaces of residential areas directly contributes to residents{\textquoteright} quality of life. It has close relationships with landscape characteristics, which should be considered in landscape planning and design processes in residential areas. Accordingly, this study proposed a new perspective on the interrelationships between soundscape perception and landscape pattern on multi-scale, based on a case study of 30 residential green spaces in Fuzhou, China. Percentage of Landscape (PLAND), Patch Density (PD), Landscape Shape Index (LSI), and Patch cohesion index (COHESION) were utilized to represent the landscape pattern of vegetation, buildings, and roads in the residential areas. Soundscape perception was interpreted using the sound dominant degree (SDD) of sound sources and overall soundscape quality. The examined spatial scales range from 20 m to 180 m, with concentric circles spaced 20 m apart for each sampling point. Correlation analyses indicated that most landscape indices of vegetation and buildings were correlated with these soundscape perception indicators, while limited landscape indices of roads were associated with them. Based on the multi-scale landscape indices, multiple linear regression models for the SDD of sound sources and overall soundscape quality were established, confirming that the scale effect of landscape patterns can affect soundscape perception. Expressly, results indicated that these models were chiefly influenced by the landscape indices at a scale less than 120 m, but the scale effect of landscape pattern on the SDD of birdsong, pleasantness, and quietness was not so evident. Furthermore, we found that the number of explanatory variables may somewhat affect the model performance. The overall interpretability of these landscape indices for the SDD of sound sources was better than that of overall soundscape quality, implying the complexity of the latter. This study offers a fresh insight into the relationship between landscapes and soundscapes at varying scales. The findings can provide useful information for the promotion strategies of landscapes and soundscapes, especially in residential green spaces.",
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AU - Liu, Jiang

AU - Huang, Yijun

AU - Chen, Zhu

AU - Hong, Xin Chen

N1 - This research was funded by the National Natural Science Foundation of China (52378049, 52208052), and the Program of Humanities and Social Science Research Program of Ministry of Education of China (Grant No. 21YJCZH038).

PY - 2023/11/27

Y1 - 2023/11/27

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