测绘通报 ›› 2024, Vol. 0 ›› Issue (9): 156-160.doi: 10.13474/j.cnki.11-2246.2024.0928

• 技术交流 • 上一篇    下一篇

基于LOD1城市模型的噪声数据可视化

任萍1,2, 陈学业1,2, 江鹢1,2, 肖海波1,2, 梁常德3, 贺彪4, 李胜1,2   

  1. 1. 深圳市规划和自然资源数据管理中心(深圳市空间地理信息中心), 广东 深圳 518000;
    2. 自然资源部城市土地资源监测与仿真重点实验室, 广东 深圳 518000;
    3. 深圳市生态环境智能管控中心, 广东 深圳 518000;
    4. 深圳大学, 广东 深圳 518000
  • 收稿日期:2024-02-04 发布日期:2024-10-09
  • 通讯作者: 李胜。E-mail:shenglee@whu.edu.cn
  • 作者简介:任萍(1983—),女,硕士,高级工程师,主要研究方向为规划和自然资源业务信息化、二三维GIS、人工智能等新一代信息技术的应用。E-mail:81572932@qq.com

Noise data visualization based on LOD1 city model

REN Ping1,2, CHEN Xueye1,2, JIANG Yi1,2, XIAO Haibo1,2, LIANG Changde3, HE Biao4, LI Sheng1,2   

  1. 1. Shenzhen Data Management Center of Planning and Natural Resource (Shenzhen Geospatial Information Center), Shenzhen 518000, China;
    2. Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518000, China;
    3. Shenzhen Ecological Environment Intelligent Control Center, Shenzhen 518000, China;
    4. Shenzhen University, Shenzhen 518000, China
  • Received:2024-02-04 Published:2024-10-09

摘要: 近年来,噪声污染日益严重,已成为生态环境类投诉的主要内容。为更直观地查看和分析噪声污染,提升噪声治理和管控能力,本文基于城市信息模型(CIM)和噪声监测数据,结合数据叠加和三维渲染技术,研究大尺度三维噪声地图技术,实现了融合倾斜摄影和白膜噪声数据的三维可视化,在噪声污染监督和治理中,通过该技术的噪声可视化分析进行优化决策,可为智慧城市建设增添动力。

关键词: CIM, 噪声监测数据, 噪声可视化, 三维噪声地图, 交通噪声

Abstract: In recent years, noise pollution has become increasingly serious and has become the main content of ecological and environmental complaints. In order to more intuitively view and analyze noise pollution, improve noise control and management capabilities, this article is based on urban information modeling (CIM) and noise monitoring data, combined with data superposition and 3D rendering technology, to study large-scale 3D noise map technology, and achieve 3D visualization by integrating oblique photography and white film noise data. The aim is to optimize decision-making in noise pollution supervision and control through the noise visualization analysis of this technology, add momentum to the construction of smart cities.

Key words: CIM, noise monitoring data, noise visualization, 3D noise map, traffic noise

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