A Distribution Strategy for Measuring Points of Street Green Space Reducing Traffic Noise

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.