Extraction of Spatial Parameters from LiDAR Data and Aerial Photography for Noise Modelling

从 LiDAR 数据和航空摄影中提取空间参数以进行噪声建模

• 批准号: 521863-2017
• 负责人: ElBasyouny, Karim
• 金额: $ 1.82万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640556
• 关键词: Extraction; Spatial; Parameters; LiDAR; Data

Through the application of the Federal Highway Administration's Traffic Noise Model (FHWA TNM), GannettFleming Inc. has been providing traffic noise management solutions for several years. TNM requires accuratelysurveyed regions around transportation infrastructure installations to conduct traffic noise studies. After severaldiscussions between Gannett Fleming Inc. and the researchers at the University of Alberta (UofA), GannettFleming Inc. decided to partner with the UofA LiDAR team to improve their noise modelling procedure. Thisproject will improve the accuracy of noise modelling by applying aerial LiDAR for spatial scanning near majortransportation infrastructure. With the continued economic expansion and urban densification in Canada, trafficnoise modelling is crucial to maintaining the quality of life of residents near downtown streets, arterialcorridors, and Light Rail Train installations.

通过应用联邦公路管理局的交通噪声模型（FHWA TNM），GannettFleming Inc.多年来一直提供交通噪音管理解决方案。TNM要求对交通基础设施周围的区域进行准确的调查，以进行交通噪声研究。在甘尼特·弗莱明公司与美国加州大学洛杉矶分校的和阿尔伯塔大学的研究人员，GannettFleming Inc.决定与UofA LiDAR团队合作，以改进其噪声建模程序。该项目将通过应用航空LiDAR在主要交通基础设施附近进行空间扫描来提高噪声建模的准确性。随着加拿大经济的持续扩张和城市的密集化，交通噪声建模对于保持市中心街道、动脉走廊和轻轨列车设施附近居民的生活质量至关重要。