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Does Urban Green Space Pattern Affect Green Space Noise Reduction?

Authors :
Feng, Liyi
Wang, Jiabing
Liu, Binyan
Hu, Fangbing
Hong, Xinchen
Wang, Wenkui
Source :
Forests (19994907); Oct2024, Vol. 15 Issue 10, p1719, 21p
Publication Year :
2024

Abstract

The effect of urban green spaces on traffic noise reduction has been extensively studied at the level of single vegetation, hedges, etc., but there is a lack of corresponding studies at the scale of spatial patterns of urban green spaces. Therefore, this study aims to analyze the relationship between the spatial pattern of urban green space and the change in green space's noise reduction capacity. Through the morphology spatial pattern analysis method, this analysis divides the urban green space in the Fuzhou high-tech zone into seven types of elements with different ecological definitions and simulates the noise condition of the urban environment with the presence of green space as well as without the presence of green space by computer simulation, calculates the distribution map of the noise reduction produced by the urban green space, and analyzes the correlation between the seven types of green space elements and the noise reduction with the geographically weighted regression modeling analysis. The study finds that (1) Urban green space patterns can significantly affect the net noise reduction of green space. Areas with high green coverage can produce a stronger green space noise reduction effect. (2) More complex green space shapes and more fragmented urban green space can produce higher noise reduction. (3) The green space close to the source of noise can exert a stronger noise reduction effect. Therefore, in the process of planning and design, from the perspective of improving the urban acoustic environment, the configuration of high-quality green spaces in areas with higher levels of noise pollution should be given priority, which may have better noise reduction effects. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19994907
Volume :
15
Issue :
10
Database :
Complementary Index
Journal :
Forests (19994907)
Publication Type :
Academic Journal
Accession number :
180558086
Full Text :
https://doi.org/10.3390/f15101719