The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-4/W3-2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W3-2022-195-2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W3-2022-195-2022
02 Dec 2022
 | 02 Dec 2022

INFLUENCE OF URBAN GREEN SPACES ON ROAD TRAFFIC NOISE LEVELS: - A REVIEW

N. Wickramathilaka, U. Ujang, S. Azri, and T. L. Choon

Keywords: Green spaces, Noise absorption, urban forms, Characteristics of leaves, LiDAR, GIS

Abstract. Ninety per cent of urban areas' total noise pollution is caused by traffic. Green areas are a very important factor for noise reduction. They will absorb noise from 5dB (A) to 10 dB (A). Nonetheless, some major concerns can be addressed, such as: how can green areas be established in the urban city?, how trees absorb noise?, what are the equations to calculate noise absorption by trees?, and what are the best survey methods to measure the trees' properties?, and is it possible to visualize trees in three-dimensional (3D) space?. Thirty-five (35) research papers were selected under the subtopics, green spaces and urban forms, noise absorption by green spaces, and green spaces visualization in 3D to find solutions for the above problems. The review has identified how to increase green spaces in urban forms like core, star, satellite, and linear. Next, the leaves are the main possible part to absorb noise, and depend on the leaves' surface area, tree depth, and noise absorption coefficient. These parameters must be considered to formulate an equation to identify sound absorption by leaves. Furthermore, the Light Detection and Ranging (LiDAR) technique can be used for determining the surface area of leaves and tree depth, due to its high resolution of point clouds. The Digital Surface Model (DSM) is not applicable for visualizing green areas, because it represents the only top view of trees, and tree depth cannot be identified properly. Proper visualization of green spaces in 3D will convey a significant point of view to visualize noise absorption accurately in a 3D urban city.