skip to main content

Traffic Noise Absorption and Propagation in a Three-Dimensional Spatial Environment: A Review

Nevil Vidyamanee Wickramathilaka  -  3D GIS Research Lab, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia, Sri Lanka
*Uznir Ujang  -  3D GIS Research Lab, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia, Malaysia
Suhaibah Azri  -  3D GIS Research Lab, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia, Malaysia
Tan Liat Choon  -  3D GIS Research Lab, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia, Malaysia
Attygalage Ranjith Rupasinghe  -  General Sir John Kotelawala Defence University, Southern Campus, Edison Hill, Nugegalayaya, Sewanagala, Sri Lanka, Sri Lanka

Citation Format:
Abstract

The impact of noise barriers on noise propagation is vital for traffic noise calculations and visualizations. Noise barriers create a major noise reduction. Green belts are the most common type of noise barrier to mitigate road traffic noise. The width, height, and surface area of leaves a green belt, as well as the noise absorption coefficient of leaves, are vital for noise absorption. This review aims to compare the characteristics and performance of green belts barriers built for traffic noise reduction. Individual tree canopies play the main role in absorbing noise in green belts. Therefore, identifying the canopy's properties is important. The side scan and nadir scan from the LiDAR survey were used to detect the tree canopy points cloud. The voxel-based, convex hull, and concave hull methods are used to visualise tree canopies in three-dimensional (3D). Concave hull provides an extract fitting surface than convex hull visualization. However, these hull surfaces do not provide accurate estimation of surface area of leaves. Further, voxel-based horizontal layers through the voxel-based profiling describes a significant method to calculate surface area of leaves in tree canopies. Establishing green belts as barriers is more cost-effective, making the former better for developing countries.

Fulltext
Keywords: Green belts; Noise barriers; Noise propagation; Tree canopy detection; Tree canopy three-dimensional visualisation

Article Metrics:

  1. Attenborough, K., Bashir, I. and Taherzadeh, S. (2016) ‘' Exploiting ground effects for surface transport noise abatement, Noise Mapping', 3(1), pp. 1–25
  2. Bienert A, Queck R, Schmidt A, Bernhofer C, Maas HG. (2010). ‘'Voxel space analysis of terrestrial laser scans in forests for wind field modelling. Downloaded from https://academic.oup.com/aob/article/121/4/589/4107549 by guest on 12 October 2022 Lecigne et al. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 38: 92–97
  3. Bohatkiewicz, J. (2016). ‘' Noise control plans in cities - selected issues and necessary changes in approach to measures and methods of protection', Transportation Research Procedia. Elsevier B.V., 14, pp. 2744–2753
  4. Cai, J. C., Wang, X., Song, J., Wang, S. L., Yang, S. and Zhao, C. J. (2017). ‘' Development of real-time laser-scanning system to detect tree canopy characteristics for variable-rate pesticide application', International Journal of Agricultural and Biological Engineering, 10(6), pp. 155–163
  5. Can, A., Leclercq, L. and Lelong, J. (2008). ‘' Dynamic estimation of urban traffic noise: Influence of traffic and noise source representations', Applied Acoustics, 69(10), pp. 858–867
  6. Chakraborty, M., Khot, L. R., Sankaran, S. and Jacoby, P. W. (2019). ‘' Evaluation of mobile 3D light detection and ranging based canopy mapping system for tree fruit crops', Computers and Electronics in Agriculture. Elsevier, 158(October 2018), pp. 284–293
  7. Dobson, M. and Ryan, J. (2000). ‘' Trees and shrubs for noise control', Arboricultural Practice Notes, pp. 1–8
  8. Dubey, R., Bharadwaj, S., Sharma, V. B., Bhatt, A. and Biswas, S. (2022). ‘' Smartphone-based traffic noise mapping system', International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 43(B4-2022), pp. 613–620
  9. Duhamel, D. and Sergent, P. (1998) ‘' Sound propagation over noise barriers with absorbing ground', Journal of Sound and Vibration, 218(5), pp. 799–823
  10. Dunbar, M. D., Moskal, L. M. and Jakubauskas, M. E. (2004). ‘' 3D visualization for the analysis of forest cover change', Geocarto International, 19(2), pp. 103–112
  11. Fernández-Sarría A, Velázquez-Martí B, Sajdak M, Martínez L, Estornell J. (2013b). ‘'Residual biomass calculation from individual tree architecture using terrestrial laser scanner and ground-level measurements', Computers and Electronics in Agriculture 93: 90–97
  12. Gilani, T. A. and Mir, M. S. (2021). ‘' Modelling road traffic noise under heterogeneous traffic conditions using the graph-theoretic approach', Environmental Science and Pollution Research. Environmental Science and Pollution Research, 28(27), pp. 36651–36668
  13. Gu, C., Zhao, C., Zou, W., Yang, S., Dou, H. and Zhai, C. (2022). ‘' Innovative Leaf Area Detection Models for Orchard Tree Thick Canopy Based on LiDAR Point Cloud Data’, Agriculture, 12(8), p. 1241
  14. Guarnaccia, C. and Quartieri, J. (2012). ‘' Analysis of road traffic noise propagation', International Journal of Mathematical Models and Methods in Applied Sciences, 6(8), pp. 926–933
  15. Halim, H. et al. (2018) ‘' Noise barrier as an option to reduce road traffic noise from highways in Klang valley, Malaysia', AIP Conference Proceedings, 2030. doi: 10.1063/1.5066917
  16. Hao, Z., Lin, L., Post, C. J., Mikhailova, E. A., Li, M., Chen, Y., Yu, K. and Liu, J. (2021). ‘' Automated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN)', ISPRS Journal of Photogrammetry and Remote Sensing. Elsevier B.V., 178(January), pp. 112–123
  17. Hosoi, F. and Omasa, K. (2006). ‘'Voxel-based 3-D modeling of individual trees for estimating leaf area density using high-resolution portable scanning lidar’, IEEE Transactions on Geoscience and Remote Sensing, 44(12), pp. 3610–3618
  18. Huddart L. (1990). The use of vegetation for traffic noise screening. In: Laboratory TaRR, editor. Crowthorne, Berkshire: Vehicles and Environment Division; 1990. p. 1–41
  19. Islam, Z., Abdullah, F. and Khanom, M. (2021). ‘' Evaluation of traffic accessibility condition and noise pollution in Dhaka City of Bangladesh', American Journal of Traffic and Transportation Engineering, 6(2), p. 43. doi: 10.11648/j.ajtte.20210602.12
  20. Itakura, K. and Hosoi, F. (2018). ‘' Automatic individual tree detection and canopy segmentation from three-dimensional point cloud images obtained from ground-based lidar', Journal of Agricultural Meteorology, 74(3), pp. 109–113
  21. Jamrah, A., Al-Omari, A. and Sharabi, R. (2006). ‘' Evaluation of traffic noise pollution in Amman, Jordan', Environmental Monitoring and Assessment, 120(1–3), pp. 499–525
  22. Jang, H. S., Lee, S. C. and Yong, J. (2015). ‘' Scale model evaluation of road traffic noise abatement by vegetation treatment in a 1 : 10 urban scale model', 3884
  23. Jiang, L. and Kang, J. (2016). ‘' Combined acoustical and visual performance of noise barriers in mitigating the environmental impact of motorways', Science of the Total Environment, 543, pp. 52–60
  24. Jung, S. Y., Yeom, D. H., Kong, R. K., Shin, G. G., Lee, K. S. and Byeon, H. S. (2020). ‘' Sound absorption property of the leaves of two evergreen broad-leaved tree species, dendropanax morbiferus and fatsia japonica1', Journal of the Korean Wood Science and Technology, 48(5), pp. 631–640
  25. Kargar, A. R., MacKenzie, R., Asner, G. P. and van Aardt, J. (2019). ‘' A density-based approach for leaf area index assessment in a complex forest environment using a Terrestrial Laser Scanner’, Remote Sensing, 11(15)
  26. Karbalaei, S. S., Karimi, E., Naji, H. R., Ghasempoori, S. M., Hosseini, S. M. and Abdollahi, M. (2015). ‘' Investigation of the Traffic Noise Attenuation Provided by Roadside Green Belts', Fluctuation and Noise Letters, 14(4), pp. 1–9
  27. Karlinasari, L., Hermawan, D., Maddu, A., Martianto, B., Lucky, I. K., Nugroho, N. and Hadi, Y. S. (2012). ‘' Acoustical properties of particleboards made from betung bamboo (Dendrocalamus asper) as building construction material', BioResources, 7(4), pp. 5700–5709
  28. Kempf, C., Tian, J., Kurz, F., D’Angelo, P., Schneider, T. and Reinartz, P. (2021). ‘' Oblique view individual tree crown delineation', International Journal of Applied Earth Observation and Geoinformation. Elsevier B.V., 99(January), p. 102-314
  29. Kowalska-Koczwara, A., Pachla, F., Tatara, T. and Nering, K. (2021). ‘' Green areas in the city as an element of noise protection', IOP Conference Series: Materials Science and Engineering, 1203(3), p. 032-025
  30. KP Manuranga, KP Dampegama, NV Wickramathilaka, AH Lakmal, H. P. (2021). ‘' An Approach for Real World As-Built Survey with the 3D Terrestrial Laser Scanner’, ACEPS 2021, 8th international symposium, pp. 377–383
  31. Kuby, P., Goodstadt-Killoran, I., Aldridge, J. and Kirkland, L. (1999). ‘' A review of research on environmental print', Journal of Instructional Psychology, 26(3), p. 173
  32. Kurakula, V. K. and Kuffer, M. (2008). ‘' 3D noise modeling for urban environmental planning and management Vinay Kumar Kurakula and Monika Kuffer', Real Corp 008, 2, pp. 517–523
  33. Kragh J. Road traffic noise attenuation by belts of trees. J Sound Vib 1981;74:235–41
  34. Lecigne, B., Delagrange, S. and Messier, C. (2018). ‘' Exploring trees in three dimensions: VoxR, a novel voxel-based R package dedicated to analysing the complex arrangement of tree crowns', Annals of Botany, 121(4), pp. 589–601
  35. Lee, H. P., Lim, K. M. and Kumar, S. (2021). ‘' Noise assessment of elevated rapid transit railway lines and acoustic performance comparison of different noise barriers for mitigation of elevated railway tracks noise', Applied Acoustics. Elsevier Ltd, 183(2021), p. 108340
  36. Li, L.; Li, D.; Zhu, H.; Li, Y. (2016). ‘'A dual growing method for the automatic extraction of individual trees from mobile laser scanning data', ISPRS J. Photogramm. 2016, 120, 37–52
  37. Li, S., Dai, L., Wang, H., Wang, Y., He, Z. and Lin, S. (2017). ‘' Estimating leaf area density of individual trees using the point cloud segmentation of terrestrial LiDAR data and a voxel-based model', Remote Sensing, 9(11), p. 1202
  38. Li, H. and Xie, H. (2021). ‘' Noise exposure of the residential areas close to urban expressways in a high-rise mountainous city', Environment and Planning B: Urban Analytics and City Science, 48(6), pp. 1414–1429
  39. Li, M. and Nan, L. (2021). ‘' Feature-preserving 3D mesh simplification for urban buildings', ISPRS Journal of Photogrammetry and Remote Sensing. Elsevier B.V., 173(April 2020), pp. 135–150
  40. Maleki K, Hosseini S. M, N. P. (2010). ‘' The Effect of pure and mixed plantations of Robinia Pseudoacasia and Pinus Eldarica on traffic noise decrease', International Journal of Environmental Science, 1
  41. May, D. N. and Osman, N. M. (1980). ‘' Highway noise barriers: new shapes', Journal of Sound and Vibration, 71(1), pp. 73–101
  42. M. El-Fadel, S. Shazbak, M.H. Baaj and E. Saliby. (2016). ‘'Parametric sensitivity analysis of noise impact of multihighways in urban areas', Environmental Impact Assessment Review 22 (2). pp.145–162
  43. Melville, H. I. A. S., Cauldwell, A. E. and Bothma, J. D. P. (1999) ‘'A comparison of two techniques for estimating tree canopy volume’, African Journal of Wildlife Research, 29(4), pp. 112–117
  44. Murthy, V. K., Majumder, A. K. and Khanal, S. N. (2007). ‘' Assessment oF traffic noise pollution in BANEPA , Banepa Map’, Engineering and Technology, (Iv), pp. 1–9
  45. Ow, L. F. and Ghosh, S. (2017). ‘' Urban cities and road traffic noise: reduction through vegetation', Applied Acoustics. Elsevier Ltd, 120, pp. 15–20
  46. Pamanikabud, P. and Tansatcha, M. (2009). ‘' Geoinformatic prediction of motorway noise on buildings in 3D GIS', Transportation Research Part D. Elsevier Ltd, 14(5), pp. 367–372
  47. Parmehr, E. G. and Amati, M. (2021). ‘' UAV-based photogrammetric and LiDAR point clouds in an urban park', Remote Sensing, 13, pp. 1–17
  48. Paris, C., Member, S., Kelbe, D., Aardt, J. Van and Bruzzone, L. (2017). ‘' A novel automatic method for the fusion of ALS and TLS LiDAR data for robust assessment of tree crown structure', 55(7), pp. 3679–3693
  49. Park, H. J., Lim, S., Trinder, J. C. and Turner, R. (2010). ‘' Voxel-based volume modelling of individual trees using terrestrial laser scanners', 15th Australasian Remote Sensing & Photogrammetry Conf, M, pp. 1125–1133
  50. Pathak, V., Tripathi, B. D. and Mishra, V. K. (2011). ‘' Evaluation of anticipated performance index of some tree species for green belt development to mitigate traffic generated noise', Urban Forestry and Urban Greening. Elsevier GmbH., 10(1), pp. 61–66
  51. Pathak, V., Tripathi, B. D. and Mishra, V. K. (2008). ‘' Dynamics of traffic noise in a tropical city Varanasi and its abatement through vegetation', Environmental Monitoring and Assessment, 146(1–3), pp. 67–75
  52. Peng, J., Bullen, R. and Kean, S. (2014). ‘' The effects of vegetation on road traffic noise’, Inter-noise014 - 43rd International Congress on Noise Control Engineering: Improving the World Through Noise Control, pp. 1–10
  53. Peng, J., Parnell, J. and Kessissoglou, N. (2021). ‘' Spatially differentiated profiles for road traffic noise pollution across a state road network', Applied Acoustics. Elsevier Ltd, 172, p. 107641
  54. Pultznerová, A., Šimo, J. and Grenčík, J. (2021). ‘' Possibilities of evaluating the effectiveness of noise barriers in slovakia', Applied Sciences (Switzerland), 11(21)
  55. Samara, T. and Tsitsoni, T. (2011). ‘' The effects of vegetation on reducing traffic noise from a city ring road', Noise Control Engineering Journal, 59(1), pp. 68–74
  56. Shimizu, K., Nishizono, T., Kitahara, F., Fukumoto, K. and Saito, H. (2022). ‘' Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan', International Journal of Applied Earth Observation and Geoinformation. Elsevier B.V., 106(October 2021), p. 102658
  57. Soma, M., Pimont, F. and Dupuy, J. L. (2021). ‘' Sensitivity of voxel-based estimations of leaf area density with terrestrial LiDAR to vegetation structure and sampling limitations: A simulation experiment', Remote Sensing of Environment. Elsevier Inc., 257(January), p. 112354
  58. Sordello, R., De Lachapelle, F. F., Livoreil, B. and Vanpeene, S. (2019). ‘' Evidence of the environmental impact of noise pollution on biodiversity: A systematic map protocol', Environmental Evidence, 8(1)
  59. Staab, J., Schady, A., Weigand, M., Lakes, T. and Taubenböck, H. (2022). ‘' Predicting traffic noise using land-use regression—a scalable approach', Journal of Exposure Science and Environmental Epidemiology, 32(2), pp. 232–243
  60. Stylianos Kephalopoulos, Marco Paviotti, F. A.-L. (2012). Common Noise Assessment Methods in Europe (CNOSSOS-EU), Journal of the American Podiatric Medical Association. Available at: http://europa.eu/
  61. Suwardhi, D., Fauzan, K. N., Harto, A. B., Soeksmantono, B., Virtriana, R. and Murtiyoso, A. (2022) ‘' 3D modeling of individual trees from LiDAR and photogrammetric point clouds by explicit parametric representations for green open space (GOS) management', ISPRS International Journal of Geo-Information, 11(3)
  62. Subramani, T. and Sivaraj, M. K. K. P. (2012). ‘' Modelling of traffic noise pollution', International Journal of Engineering Research and Application, 2(3), pp. 3175–3182
  63. Tang, S., Dong, P. and Buckles, B. P. (2013). ‘' Three-dimensional surface reconstruction of tree canopy from lidar point clouds using a region-based level set method', International Journal of Remote Sensing, 34(4), pp. 1373–1385
  64. Tang, S. H. and Ong, P. P. (1988). ‘' A Monte Carlo technique to determine the effectiveness of roadside trees for containing traffic noise', Applied Acoustics, 23(4), pp. 263–271
  65. Tobollik, M., Hintzsche, M., Wothge, J., Myck, T. and Plass, D. (2019). ‘' Burden of disease due to traffic noise in Germany', International Journal of Environmental Research and Public Health, 16(13), pp. 6–12
  66. Tudor, E. M., Dettendorfer, A., Kain, G., Barbu, M. C., Réh, R. and Krišt’ák, L. (2020). ‘' Sound-absorption coefficient of bark-based insulation panels', Polymers, 12(5), pp. 1–11
  67. Trees, S., Uav, U., Cloud, I. P., Jia, R., Deng, J. and Zhang, Y. (2021). ‘' Canopy volume extraction of citrus reticulate Blanco cv . deep learning'
  68. van Leeuwen, J. J. A. and Nota, R. (1997). ‘' Some noise propagation models used for the prediction of traffic noise in the environment', Internoise, 2(August 1997), pp. 919–922
  69. Van Renterghem, T. (2014). ‘' Guidelines for optimizing road traffic noise shielding by non-deep tree belts', Ecological Engineering. Elsevier B.V., 69, pp. 276–286
  70. Wallace, L. O., Lucieer, A. and Watson, C. S. (2012). ‘' Assessing the feasibility of Uav-based Lidar for high resolution forest change detection', The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIX-B7(August), pp. 499–504
  71. Wang, C., Ji, M., Wang, J., Wen, W., Li, T. and Sun, Y. (2019). ‘‘ An improved DBSCAN method for LiDAR data segmentation with automatic Eps estimation’, Sensors (Switzerland), 19(1)
  72. Watanabe, T. and Yamada, S. (1996). ‘' Sound attenuation through absorption by vegetation', Journal of the Acoustical Society of Japan (E) (English translation of Nippon Onkyo Gakkaishi), 17(4), pp. 175–182
  73. Willman, S., Wallace, L., Reinke, K. and Jones, S. (2021). ‘' ISPRS Journal of Photogrammetry and remote sensing A comparison between TLS and UAS LiDAR to represent eucalypt crown fuel characteristics', ISPRS Journal of Photogrammetry and Remote Sensing. Elsevier B.V., 181(September), pp. 295–307
  74. Wulder, M. A., Bater, C. W., Coops, N. C., Hilker, T. and White, J. C. (2008). ‘' The role of LiDAR in sustainable forest management', Forestry Chronicle, 84(6), pp. 807–826
  75. Xu Y, X Tong and Stilla U. (2021). Voxel-based representation of 3D point clouds: methods, applications, and its potential use in the construction industry. Automation in Construction, 126, 103675. doi: 10.1016/j.autcon.2021.103675
  76. Yang, W., He, J., He, C. and Cai, M. (2020) ‘' Evaluation of urban traffic noise pollution based on noise maps', Transportation Research Part D: Transport and Environment. Elsevier, 87, p. 102516
  77. Yan, Z., Liu, R., Cheng, L., Zhou, X., Ruan, X. and Xiao, Y. (2019). ‘' A concave hull methodology for calculating the crown volume of individual trees based on vehicle-borne LiDAR data', Remote Sensing, 11(6), p. 623
  78. Yasin, I., Widaryanto, L. H. and Sutrisno, W. (2020). ‘' The technique of green belt bamboo constructions for highway noise effect reductions’, Journal of Physics: Conference Series, 1456(1), pp. 0–9
  79. Yofianti, D. and Usman, K. (2021). ‘' Relationship of plant types to noise pollution absorption level to improve the quality of the road environment’, IOP Conference Series: Earth and Environmental Science, 926(1)
  80. Zambon, G., Radaelli, S. and Sindoni, E. (2007). ‘' Errors evaluation in the estimate of the noise from the road traffic', Nuovo Cimento della Societa Italiana di Fisica C, 30(2), pp. 187–194
  81. Zhang, W., He, Z. and Li, X. (2022). ‘' Proceedings of the Fábos conference on landscape and greenway planning voxel-based urban vegetation volume analysis with LiDAR point cloud voxel-based urban vegetation volume analysis with LiDAR Point Cloud', 7(1)
  82. Zhong, L., Cheng, L., Xu, H., Wu, Y., Chen, Y. and Li, M. (2016). ‘' Segmentation of individual trees from TLS and MLS Data', pp. 1–14

Last update:

No citation recorded.

Last update: 2024-10-30 21:09:15

No citation recorded.