{"title":"基于Henk-de-Klujijver模型的交通噪声三维可视化","authors":"N. Wickramathilaka, U. Ujang, S. Azri, T. Choon","doi":"10.1515/noise-2022-0170","DOIUrl":null,"url":null,"abstract":"Abstract Visualisation of road traffic noise is vital for traffic noise planning policies. Several factors affect the noise from road traffic with physical and environmental conditions. Collecting noise levels around the world is not a possible task. Therefore, calculating noise levels by a valid noise model, and spatial interpolations, is prime to traffic noise visualisation. In this study, the Henk de Klujijver noise model is used. Designing noise observation points (Nops) embedding with a three-dimensional (3D) building model and identifying the best suitable spatial interpolation are important to visualise the traffic noise accurately. However, interpolating noise in 3D space (vertical direction) is a more complex process than interpolating in two-dimensional (2D) space. Flat triangles should be eliminated in the vertical direction. Therefore, the structure of Nop has a major influence on spatial interpolation. Triangular Irregular Network (TIN) interpolation is more accurate for visualising traffic noise as 3D noise contours than Inverse Distance Weighted and kriging. Although kriging is vital to visualise noise as raster formats in 2D space. The 3D kriging in Empirical Bayesian shows a 3D voxel visualisation with higher accuracy than 3D TIN noise contours.","PeriodicalId":44086,"journal":{"name":"Noise Mapping","volume":"10 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Three-dimensional visualisation of traffic noise based on the Henk de-Klujijver model\",\"authors\":\"N. Wickramathilaka, U. Ujang, S. Azri, T. Choon\",\"doi\":\"10.1515/noise-2022-0170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Visualisation of road traffic noise is vital for traffic noise planning policies. Several factors affect the noise from road traffic with physical and environmental conditions. Collecting noise levels around the world is not a possible task. Therefore, calculating noise levels by a valid noise model, and spatial interpolations, is prime to traffic noise visualisation. In this study, the Henk de Klujijver noise model is used. Designing noise observation points (Nops) embedding with a three-dimensional (3D) building model and identifying the best suitable spatial interpolation are important to visualise the traffic noise accurately. However, interpolating noise in 3D space (vertical direction) is a more complex process than interpolating in two-dimensional (2D) space. Flat triangles should be eliminated in the vertical direction. Therefore, the structure of Nop has a major influence on spatial interpolation. Triangular Irregular Network (TIN) interpolation is more accurate for visualising traffic noise as 3D noise contours than Inverse Distance Weighted and kriging. Although kriging is vital to visualise noise as raster formats in 2D space. The 3D kriging in Empirical Bayesian shows a 3D voxel visualisation with higher accuracy than 3D TIN noise contours.\",\"PeriodicalId\":44086,\"journal\":{\"name\":\"Noise Mapping\",\"volume\":\"10 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Noise Mapping\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/noise-2022-0170\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ACOUSTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Noise Mapping","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/noise-2022-0170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ACOUSTICS","Score":null,"Total":0}
Three-dimensional visualisation of traffic noise based on the Henk de-Klujijver model
Abstract Visualisation of road traffic noise is vital for traffic noise planning policies. Several factors affect the noise from road traffic with physical and environmental conditions. Collecting noise levels around the world is not a possible task. Therefore, calculating noise levels by a valid noise model, and spatial interpolations, is prime to traffic noise visualisation. In this study, the Henk de Klujijver noise model is used. Designing noise observation points (Nops) embedding with a three-dimensional (3D) building model and identifying the best suitable spatial interpolation are important to visualise the traffic noise accurately. However, interpolating noise in 3D space (vertical direction) is a more complex process than interpolating in two-dimensional (2D) space. Flat triangles should be eliminated in the vertical direction. Therefore, the structure of Nop has a major influence on spatial interpolation. Triangular Irregular Network (TIN) interpolation is more accurate for visualising traffic noise as 3D noise contours than Inverse Distance Weighted and kriging. Although kriging is vital to visualise noise as raster formats in 2D space. The 3D kriging in Empirical Bayesian shows a 3D voxel visualisation with higher accuracy than 3D TIN noise contours.
期刊介绍:
Ever since its inception, Noise Mapping has been offering fast and comprehensive peer-review, while featuring prominent researchers among its Advisory Board. As a result, the journal is set to acquire a growing reputation as the main publication in the field of noise mapping, thus leading to a significant Impact Factor. The journal aims to promote and disseminate knowledge on noise mapping through the publication of high quality peer-reviewed papers focusing on the following aspects: noise mapping and noise action plans: case studies; models and algorithms for source characterization and outdoor sound propagation: proposals, applications, comparisons, round robin tests; local, national and international policies and good practices for noise mapping, planning, management and control; evaluation of noise mitigation actions; evaluation of environmental noise exposure; actions and communications to increase public awareness of environmental noise issues; outdoor soundscape studies and mapping; classification, evaluation and preservation of quiet areas.