Performance assessment of spatial interpolations for traffic noise mapping on undulating and level terrain
Abstract
Traffic noise mapping frequently employs Kriging, Inverse Distance Weighted (IDW), and Triangular Irregular Networks (TIN) spatial interpolations. This study uses the Henk de Kluijver noise model to evaluate the performance of spatial interpolations. Effective traffic noise mapping requires that noise observation points (Nops) be designed as 2 m grids. The upper and lower slopes function as noise barriers to reduce sound levels. Therefore, assessment of accuracy is essential for visualising noise levels in undulating and level terrain. In addition, this work gives an accurate comparison of traffic noise interpolation in undulating areas. The elements of spatial interpolations, such as the weighting factor, variogram, radius, and number of points influence the interpolation accuracy. The Kriging with a Gaussian variogram, where the radius is 5 m and the number of points is 12 demonstrates the highest level of precision. However, there is no direct relationship between accuracy validation and cross-validation. In cross-validation, however, the accuracy of the Gaussian variogram with a 7 m radius and 18 points is more accurate. In addition, this study demonstrates that Kriging is superior for extrapolating noise levels in undulating regions. Accurate visualising traffic noise levels requires a prior understanding of spatial interpolations.
Keyword : noise observation points, accuracy validation, IDW, Kriging, TIN
How to Cite
Wickramathilaka, N., Ujang, U., Azri, S., & Choon, T. L. (2024). Performance assessment of spatial interpolations for traffic noise mapping on undulating and level terrain. Geodesy and Cartography, 50(1), 35–42. https://doi.org/10.3846/gac.2024.18751
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Lesieur, A., Mallet, V., Aumond, P., & Can, A. (2021). Data assimilation for urban noise mapping with a meta-model. Applied Acoustics, 178, Article 107938. https://doi.org/10.1016/j.apacoust.2021.107938
Maleika, W. (2020). Inverse distance weighting method optimization in the process of digital terrain model creation based on data collected from a multibeam echosounder. Applied Geomatics, 12(4), 397–407. https://doi.org/10.1007/s12518-020-00307-6
Mishra, R. K., Mishra, A. R., & Singh, A. (2018). Traffic noise analysis using RLS-90 model in urban city. Inter-Noise and Noise- Congress and Conference Proceedings, 13, 6490–6502.
Nejad, P. G., Ahmad, A., & Zen, I. S. (2019). Assessment of the Interpolation techniques on traffic noise pollution mapping for the campus environment sustainability. International Journal of Built Environment & Sustainability, 6(1–2), 147–159. https://doi.org/10.11113/ijbes.v6.n1-2.393
Ramadhan, M. D., Marwanza, I., Nas, C., Azizi, M. A., Dahani, W., & Kurniawati, R. (2021). Drill holes spacing analysis for estimation and classification of coal resources based on variogram and Kriging. IOP Conference Series: Earth and Environmental Science, 819(1), Article 012026. https://doi.org/10.1088/1755-1315/819/1/012026
Ranjbar, H. R., Gharagozlou, A. R., & Vafaei Nejad, A. R. (2012). 3D analysis and investigation of traffic noise impact from Hemmat Highway located in Tehran on buildings and surrounding areas. Journal of Geographic Information System, 4(4), 322–334. https://doi.org/10.4236/jgis.2012.44037
Risk, C., & James, P. M. A. (2022). Optimal cross-validation strategies for selection of spatial interpolation models for the Canadian forest fire weather index system. Earth and Space Science, 9(2), 1–17. https://doi.org/10.1029/2021EA002019
Ridzuan, N., Wickramathilaka, N., Ujang, U., & Azri, S. (2024). 3D voxelisation for enhanced environmental modelling applications. Pollution, 10(1), 151–167. https://doi.org/10.22059/poll.2023.360562.1942
Samal, K., Babu, K., & Das, S. (2018). Spatio-temporal prediction of air quality using distance-based interpolation and deep learning techniques. EAI Endorsed Transactions on Smart Cities, 5(14), Article 168139. https://doi.org/10.4108/eai.15-1-2021.168139
Schneck, T., Telbisz, T., & Zsuffa, I. (2021). Precipitation interpolation using digital terrain model and multivariate regression in hilly and low mountainous areas of Hungary. Hungarian Geographical Bulletin, 70(1), 35–48. https://doi.org/10.15201/hungeobull.70.1.3
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Suthanaya, P. A. (2015). Modelling road traffic noise for collector road (case study of Denpasar City). Procedia Engineering, 125, 467–473. https://doi.org/10.1016/j.proeng.2015.11.125
Stoter, J. E., Kluijver, H. De., & Kurakula, V. (2007). 3D noise contours. https://www.dbvision.nl/bestanden/overons/publicaties/2007/20071106%20Stoter%20dr.%20J.E.,%20Kluijver%20ir.%20H.%20de,%20Kurakula%20V.,%203.pdf
Taghizadeh, R., Zare, M., & Zare, S. (2013). Mapping of noise pollution by different interpolation methods in recovery section of Ghandi telecommunication Cables Company. Journal of Occupational Health and Epidemiology, 2(1), 1–11. https://doi.org/10.18869/acadpub.johe.2.1.2.1
Taharin, M. R., & Roslee, R. (2021). The application of semi variogram and ordinary Kriging in determining the cohesion and clay percentage distribution in hilly area of Sabah, Malaysia. International Journal of Design and Nature and Ecodynamics, 16(5), 525–530. https://doi.org/10.18280/ijdne.160506
Tang, J. H., Lin, B. C., Hwang, J. S., Chen, L. J., Wu, B. S., Jian, H. L., Lee, Y. T., & Chan, T. C. (2022). Dynamic modeling for noise mapping in urban areas. Environmental Impact Assessment Review, 97, Article 106864. https://doi.org/10.1016/j.eiar.2022.106864
Tomczak, M. (1998). Spatial interpolation and its uncertainty using automated anisotropic Inverse Distance Weighting (IDW)-Cross-validation/Jackknife Approach. Journal of Geographic Information and Decision, 2(2), 18–30.
Van Groenigen, J. W. (2000). The influence of variogram parameters on optimal sampling schemes for mapping by kriging. Geoderma, 97(3–4), 223–236. https://doi.org/10.1016/S0016-7061(00)00040-9
Van Huynh, C., Pham, T. G., Nguyen, L. H. K., Nguyen, H. T., Nguyen, P. T., Le, Q. N. P., Tran, P. T., Nguyen, M. T. H., & Tran, T. T. A. (2022). Application GIS and remote sensing for soil organic carbon mapping in a farm-scale in the hilly area of central Vietnam. Air, Soil and Water Research, 2022, Article 15. https://doi.org/10.1177/11786221221114777
Varentsov, M., Esau, I., & Wolf, T. (2020). High-resolution temperature mapping by geostatistical kriging with external drift from large-eddy simulations. Monthly Weather Review, 148(3), 1029–1048. https://doi.org/10.1175/MWR-D-19-0196.1
Wenzhong, S. (2000). Development of a hybrid model for three dimensional GIS. Geospatial Information Science, 3(2), 6–12. https://doi.org/10.1007/BF02826617
Wu, S., Fu, F., Wang, L., Yang, M., Dong, S., He, Y., & Zhang, Q. (2022). Short-term regional temperature prediction based on deep spatial and temporal networks. Atmosphere, 13(12), Article 1948. https://doi.org/10.3390/atmos13121948
Aumond, P., Can, A., Mallet, V., De Coensel, B., Ribeiro, C., Botteldooren, D., & Lavandier, C. (2018). Kriging-based spatial interpolation from measurements for sound level mapping in urban areas. The Journal of the Acoustical Society of America, 143(5), 2847–2857. https://doi.org/10.1121/1.5034799
Chen, F. W., & Liu, C. W. (2012). Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan. Paddy and Water Environment, 10(3), 209–222. https://doi.org/10.1007/s10333-012-0319-1
Debnath, A., & Singh, P. K. (2018). Environmental traffic noise modelling of Dhanbad township area – A mathematical based approach. Applied Acoustics, 129, 161–172. https://doi.org/10.1016/j.apacoust.2017.07.023
Esri. (2021). ArcGIS Desktop.
Fazio, V. S., & Roisenberg, M. (2013). Spatial interpolation: An analytical comparison between Kriging and RBF networks. Proceedings of the ACM Symposium on Applied Computing, 2(1), 2–7. https://doi.org/10.1145/2480362.2480364
Fung, K. F., Chew, K. S., Huang, Y. F., Ahmed, A. N., Teo, F. Y., Ng, J. L., & Elshafie, A. (2022). Evaluation of spatial interpolation methods and spatiotemporal modelling of rainfall distribution in Peninsular Malaysia. Ain Shams Engineering Journal, 13(2), Article 101571. https://doi.org/10.1016/j.asej.2021.09.001
Gilani, T. A., & Mir, M. S. (2021). Modelling road traffic noise under heterogeneous traffic conditions using the graph-theoretic approach. Environmental Science and Pollution Research, 28(27), 36651–36668. https://doi.org/10.1007/s11356-021-13328-4
Harman, B. I., Koseoglu, H., & Yigit, C. O. (2016). Performance evaluation of IDW, Kriging and multiquadric interpolation methods in producing noise mapping: A case study at the city of Isparta, Turkey. Applied Acoustics, 112, 147–157. https://doi.org/10.1016/j.apacoust.2016.05.024
Huang, Y., Wang, L., Hou, Y., Zhang, W., & Zhang, Y. (2018). A prototype IOT based wireless sensor network for traffic information monitoring. International Journal of Pavement Research and Technology, 11(2), 146–152. https://doi.org/10.1016/j.ijprt.2017.07.005
Iaaly-sankari, A., Jadayel, O., & El-murr, N. (2010). Urban Noise Mapping: The Case of the City of El-Mina, North Lebanon. In Proceedings Middle East & North Africa Users Conference ESRI (p. 10).
Iglesias-Merchan, C., Laborda-Somolinos, R., González-Ávila, S., & Elena-Rosselló, R. (2021). Spatio-temporal changes of road traffic noise pollution at ecoregional scale. Environmental Pollution, 286, Article 11729. https://doi.org/10.1016/j.envpol.2021.117291
International Organization for Standardization. (1996). Acoustics – attenuation of sound propagation outdoors (ISO Standard No. 9613-2:1996).
Jaman, N. I., & Adhikary, S. K. (2020, February). A positive Kriging approach for missing rainfall estimation. In The 5th International Conference on Civil Engineering for Sustainable Development (pp. 1–10). https://www.researchgate.net/publication/340447627_A_Positive_Kriging_Approach_for_Missing_Rainfall_Estimation
Kurakula, V. K., & Kuffer, M. (2008). 3D noise modelling for urban environmental planning and management. In Real Corp 0088: Mobility Nodes as Innovation Hubs (pp. 517–523). https://www.researchgate.net/publication/228622472_3D_Noise_Modeling_for_Urban_Environmental_Planning_and_Management
Kurakula, V., Skidmore, A., Kluijver, H. D., Stoter, J., Dąbrowska-Zielińska, K., & Kuffer, M. (2007). A GIS-Based approach for 3D noise modelling using 3D city models. International Institute for Geo-Information Science and Earth, 319(5864), 766–769. https://www.semanticscholar.org/paper/A-GIS-Based-approach-for-3D-noise-modelling-using-Kurakula-Skidmore/0a3e4950ec0e7ec852b90c444d66e4618757a75b
Law, C. W., Lee, C. K., Lui, A. S. W., Yeung, M. K. L., & Lam, K. C. (2011). Advancement of three-dimensional noise mapping in Hong Kong. Applied Acoustics, 72(8), 534–543. https://doi.org/10.1016/j.apacoust.2011.02.003
Laxmi, V., Dey, J., Kalawapudi, K., Vijay, R., & Kumar, R. (2019). An innovative approach of urban noise monitoring using cycle in Nagpur India. Environmental Science and Pollution Research. Environmental Science and Pollution Research, 26(36), 36812–36819. https://doi.org/10.1007/s11356-019-06817-0
Lesieur, A., Mallet, V., Aumond, P., & Can, A. (2021). Data assimilation for urban noise mapping with a meta-model. Applied Acoustics, 178, Article 107938. https://doi.org/10.1016/j.apacoust.2021.107938
Maleika, W. (2020). Inverse distance weighting method optimization in the process of digital terrain model creation based on data collected from a multibeam echosounder. Applied Geomatics, 12(4), 397–407. https://doi.org/10.1007/s12518-020-00307-6
Mishra, R. K., Mishra, A. R., & Singh, A. (2018). Traffic noise analysis using RLS-90 model in urban city. Inter-Noise and Noise- Congress and Conference Proceedings, 13, 6490–6502.
Nejad, P. G., Ahmad, A., & Zen, I. S. (2019). Assessment of the Interpolation techniques on traffic noise pollution mapping for the campus environment sustainability. International Journal of Built Environment & Sustainability, 6(1–2), 147–159. https://doi.org/10.11113/ijbes.v6.n1-2.393
Ramadhan, M. D., Marwanza, I., Nas, C., Azizi, M. A., Dahani, W., & Kurniawati, R. (2021). Drill holes spacing analysis for estimation and classification of coal resources based on variogram and Kriging. IOP Conference Series: Earth and Environmental Science, 819(1), Article 012026. https://doi.org/10.1088/1755-1315/819/1/012026
Ranjbar, H. R., Gharagozlou, A. R., & Vafaei Nejad, A. R. (2012). 3D analysis and investigation of traffic noise impact from Hemmat Highway located in Tehran on buildings and surrounding areas. Journal of Geographic Information System, 4(4), 322–334. https://doi.org/10.4236/jgis.2012.44037
Risk, C., & James, P. M. A. (2022). Optimal cross-validation strategies for selection of spatial interpolation models for the Canadian forest fire weather index system. Earth and Space Science, 9(2), 1–17. https://doi.org/10.1029/2021EA002019
Ridzuan, N., Wickramathilaka, N., Ujang, U., & Azri, S. (2024). 3D voxelisation for enhanced environmental modelling applications. Pollution, 10(1), 151–167. https://doi.org/10.22059/poll.2023.360562.1942
Samal, K., Babu, K., & Das, S. (2018). Spatio-temporal prediction of air quality using distance-based interpolation and deep learning techniques. EAI Endorsed Transactions on Smart Cities, 5(14), Article 168139. https://doi.org/10.4108/eai.15-1-2021.168139
Schneck, T., Telbisz, T., & Zsuffa, I. (2021). Precipitation interpolation using digital terrain model and multivariate regression in hilly and low mountainous areas of Hungary. Hungarian Geographical Bulletin, 70(1), 35–48. https://doi.org/10.15201/hungeobull.70.1.3
Susanto, A., Setyawan, D. O., Setiabudi, F., Savira, Y. M., Listiarini, A., Putro, E. K., Muhamad, A. F., Wilmot, J. C., Zulfakar, D., Kara, P., Shofwati, I., Sodikin, S., & Tejamaya, M. (2021). GIS-based mapping of noise from mechanized minerals ore processing industry. Noise Mapping, 8(1), 1–15. https://doi.org/10.1515/noise-2021-0001
Suthanaya, P. A. (2015). Modelling road traffic noise for collector road (case study of Denpasar City). Procedia Engineering, 125, 467–473. https://doi.org/10.1016/j.proeng.2015.11.125
Stoter, J. E., Kluijver, H. De., & Kurakula, V. (2007). 3D noise contours. https://www.dbvision.nl/bestanden/overons/publicaties/2007/20071106%20Stoter%20dr.%20J.E.,%20Kluijver%20ir.%20H.%20de,%20Kurakula%20V.,%203.pdf
Taghizadeh, R., Zare, M., & Zare, S. (2013). Mapping of noise pollution by different interpolation methods in recovery section of Ghandi telecommunication Cables Company. Journal of Occupational Health and Epidemiology, 2(1), 1–11. https://doi.org/10.18869/acadpub.johe.2.1.2.1
Taharin, M. R., & Roslee, R. (2021). The application of semi variogram and ordinary Kriging in determining the cohesion and clay percentage distribution in hilly area of Sabah, Malaysia. International Journal of Design and Nature and Ecodynamics, 16(5), 525–530. https://doi.org/10.18280/ijdne.160506
Tang, J. H., Lin, B. C., Hwang, J. S., Chen, L. J., Wu, B. S., Jian, H. L., Lee, Y. T., & Chan, T. C. (2022). Dynamic modeling for noise mapping in urban areas. Environmental Impact Assessment Review, 97, Article 106864. https://doi.org/10.1016/j.eiar.2022.106864
Tomczak, M. (1998). Spatial interpolation and its uncertainty using automated anisotropic Inverse Distance Weighting (IDW)-Cross-validation/Jackknife Approach. Journal of Geographic Information and Decision, 2(2), 18–30.
Van Groenigen, J. W. (2000). The influence of variogram parameters on optimal sampling schemes for mapping by kriging. Geoderma, 97(3–4), 223–236. https://doi.org/10.1016/S0016-7061(00)00040-9
Van Huynh, C., Pham, T. G., Nguyen, L. H. K., Nguyen, H. T., Nguyen, P. T., Le, Q. N. P., Tran, P. T., Nguyen, M. T. H., & Tran, T. T. A. (2022). Application GIS and remote sensing for soil organic carbon mapping in a farm-scale in the hilly area of central Vietnam. Air, Soil and Water Research, 2022, Article 15. https://doi.org/10.1177/11786221221114777
Varentsov, M., Esau, I., & Wolf, T. (2020). High-resolution temperature mapping by geostatistical kriging with external drift from large-eddy simulations. Monthly Weather Review, 148(3), 1029–1048. https://doi.org/10.1175/MWR-D-19-0196.1
Wenzhong, S. (2000). Development of a hybrid model for three dimensional GIS. Geospatial Information Science, 3(2), 6–12. https://doi.org/10.1007/BF02826617
Wu, S., Fu, F., Wang, L., Yang, M., Dong, S., He, Y., & Zhang, Q. (2022). Short-term regional temperature prediction based on deep spatial and temporal networks. Atmosphere, 13(12), Article 1948. https://doi.org/10.3390/atmos13121948