期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B7
页码：1735-1740
出版社：Copernicus Publications
摘要：Prediction of sound level of real world environment in 3D is important for managing noise pollution, urban planning, virtual realization of sound etc. Commercially available semi-empirical sound models use various input parameters such as location of source and receiver; diffraction related path length difference when sound encounters intermediate buildings; characteristics of ground; nature of vegetation etc. Empirical techniques used inside the existing sound models suffer from approximation in algorithm, inadequate technique to feed terrain related information and limitation in capturing accurate terrain information in many cases. Airborne Altimetric LiDAR (Light Detection and Ranging) surveys along with aerial photographs generate accurate high resolution terrain data in a short time. It creates interesting options for feeding intricate terrain information inside these models. In the paper a technique is described for taking input from LiDAR data and air photos to generate terrain related parameters required in empirical approach. Furthermore, these parameters are incorporated into semi-empirical models to generate the sound characteristic at any point in 3D due to a sound source. Different algorithms for sound models are developed in MATLAB whereas TerraScan is used for display purpose. The ability to work with different modelling algorithms under semi-empirical approach provides an opportunity to compare functionality of different semi-empirical models and arrive at an efficient composite model
关键词：Laser altimetry; 3D modelling; Aerial image; Clustering; Extraction
