TY - GEN
T1 - A Distribution Strategy for Measuring Points of Street Green Space Reducing Traffic Noise
AU - Li, Mengmeng
AU - Wu, Yuanxiang
AU - Sun, Shi
AU - Zhang, Mingfeng
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Street green spaces play a critical role in reducing traffic noise. When assessing the overall noise reduction effect generated by street green spaces, the discrepancies caused by measuring point density have not been taken into consideration in current researches. The aim of this research is to determine the optimal density of measuring points for street green space, which is effective in properly calculating the overall noise reduction effect. Consequently, a segment of a street green space with 16 m long and 30 m wide is selected for this study, which was split into slices perpendicular to the road with intervals of 1m and measuring points with 0 m, 10 m, 20 m and 30 m from the road respectively are set in each slice. In this study, data was interpolated using ARCGIS, and a noise map of the street green space was developed. This study indicates that the noise mapping varies with the density of measuring points, while variations in beginning positions of measuring points in the same density condition have little effect. This implies that the estimate of the overall noise reduction effect of street green spaces is influenced by measuring point density rather than position. In order to identify the ideal distance between measuring points, the study used analysis of variance. This study proposes a distribution strategy for street green space noise reduction measuring point positions that can be used to compare the results of other research.
AB - Street green spaces play a critical role in reducing traffic noise. When assessing the overall noise reduction effect generated by street green spaces, the discrepancies caused by measuring point density have not been taken into consideration in current researches. The aim of this research is to determine the optimal density of measuring points for street green space, which is effective in properly calculating the overall noise reduction effect. Consequently, a segment of a street green space with 16 m long and 30 m wide is selected for this study, which was split into slices perpendicular to the road with intervals of 1m and measuring points with 0 m, 10 m, 20 m and 30 m from the road respectively are set in each slice. In this study, data was interpolated using ARCGIS, and a noise map of the street green space was developed. This study indicates that the noise mapping varies with the density of measuring points, while variations in beginning positions of measuring points in the same density condition have little effect. This implies that the estimate of the overall noise reduction effect of street green spaces is influenced by measuring point density rather than position. In order to identify the ideal distance between measuring points, the study used analysis of variance. This study proposes a distribution strategy for street green space noise reduction measuring point positions that can be used to compare the results of other research.
KW - Measuring Points Arrangement
KW - Noise Mapping
KW - Street Green Space
KW - Traffic Noise Reduction
UR - https://www.scopus.com/pages/publications/85214104766
U2 - 10.1007/978-981-97-8317-5_63
DO - 10.1007/978-981-97-8317-5_63
M3 - 会议稿件
AN - SCOPUS:85214104766
SN - 9789819783168
T3 - Lecture Notes in Civil Engineering
SP - 430
EP - 435
BT - Multiphysics and Multiscale Building Physics - Proceedings of the 9th International Building Physics Conference IBPC 2024
A2 - Berardi, Umberto
PB - Springer Science and Business Media Deutschland GmbH
T2 - 9th International Building Physics Conference, IBPC 2024
Y2 - 25 July 2024 through 27 July 2024
ER -