基于虚拟地球的台风多维动态可视化系统的设计与实现

胡自和; 刘坡; 龚建华; 王群

doi:10.13203/j.whugis20130669

基于虚拟地球的台风多维动态可视化系统的设计与实现

胡自和^1,2,
刘坡^1,3,,
龚建华³,
王群²

1.
城市空间信息工程北京市重点实验室, 北京, 100038;
2.
武汉智慧政通科技有限公司, 湖北武汉, 430079;
3.
中国科学院遥感与数字地球研究所, 北京, 100039

基金项目: 国家自然科学基金资助项目(41171351);国家科技支撑计划资助项目(KZCX2-EW-318);国家“十二五”攻关计划资助项目(2014ZX10003002);城市空间信息工程北京市重点实验室开放研究基金资助项目(2014210)。

详细信息

作者简介:
胡自和,工程师,主要从事空间数据可视化与仿真研究。E-mail:huzihe06@163.com

通讯作者:
刘坡,博士。E-mail:liuposwust@163.com

中图分类号: P208
计量
- 文章访问数: 1469
- HTML全文浏览量: 95
- PDF下载量: 770
出版历程
- 收稿日期: 2014-04-16
- 发布日期: 2015-10-04

Design and Implementation of Multidimensional and Animated Visualization System for Typhoon on Virtual Globes

HU Zihe^1,2,
LIU Po^1,3,,
GONG Jianhua³,
WANG Qun²

1.
Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing 100038, China;
2.
Wuhan eGOVA Co., Ltd., Wuhan 430079, China;
3.
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100039, China

Funds: The National Natural Science Foundation of China, No. 41171351;the Key Knowledge Innovative Project of the Chinese Academy of Sciences, No. KZCX2-EW-318; the National Key Technology R&D Program of China, No. 2014ZX10003002; Foundation of Beijing Key Laboratory of Urban Spatial Information Engineering, No.2014210.

摘要

摘要: 台风作为一种热带气旋,是影响我国东南沿海区域的主要灾害性天气。台风可视化是台风研究及预报应用的重要组成部分,在防灾减灾中发挥着重要作用。但是由于数据量巨大,台风动态交互可视化很难在网络环境下实现。虚拟地球技术的出现提供了一个新的网络可视化平台,提高了公众参与的能力,但是其很难支持专业的气象应用。基于开源的虚拟地球平台构建台风动态可视化环境,首先介绍了坐标转换、数据组织和基于GPU的体可视化这些关键技术,然后详细介绍了系统的主要功能,并在World Wind开源平台上实现相关功能的开发,最后通过一个具体的案例证明了系统的有效性和实用性。
- 台风 /
- 体可视化 /
- GPU /
- 虚拟地球
Abstract: Typhoons, a type of tropical cyclone,are the main severe weather event effecting areas on the Southeastern coast of China. Typhoon visualization is a signifiant component in weather research and forecasting applications, and plays an important role in disaster prevention and harm reduction. However, challenges arise when the volume of data is huge, virtual globes can be regarded as a logical platform to visualize such geospatial data over the Internet, but they provide few advanced visualization tools for rendering volumetric data.This paper proposes a virtual globe-based multidimensional and animated visualization system for typhoons. We describe the key technologies, including coordinate transformation, data organization and GPU-based volume rendering. Then, we present the proposed design and implementation in World Wind, introducing the main functions. To demonstrate the capabilities of this system, the data for a simulated typhoon event are rendered on the globe.
- typhoon /
- volume rendering /
- GPU /
- virtual globes

HTML全文

参考文献(29)

[1]	Nocke T, Sterzel T, Böttinger M, et al. Visualization of Climate and Climate Change Data: An Overview [C]. Digital Earth Summit on Geoinformatics 2008: Tools for Global Change Research (ISDE'08),Wichmann, Heidelberg,2008
[2]	Van Thu T, Krishnamurti T. Vortex Initialization for Typhoon Track Prediction [J]. Meteorology and Atmospheric Physics, 1992, 47(2/4): 117-126
[3]	Zhu Zhenyi. 3D Modeling and Secene Simulaiton of Typhoon [D]. Shanghai: Tongji University, 2008 (朱震毅. 台风三维建模与视景仿真研究[D]. 上海:同济大学, 2008)
[4]	Nocke T, Flechsig M, Bohm U. Visual Exploration and Evaluation of Climate-related Simulation Data [C].2007 Winter Simulation Conference, Washington D C,USA, 2007
[5]	Doleisch H. SimVis: Interactive Visual Analysis of Large and Time-dependent 3D Simulation Data [C].The 39th Conference on Winter Simulation: 40 Years! The Best is Yet to Come, Washington D C,USA, 2007
[6]	Wang H, Lau K H, Chan W M, et al. A PC-Based Visualization System for Coastal Ocean and Atmospheric Modeling [C].Estuarine and Coastal Modeling (1999), New Orleans, Louisiana, USA, 2002
[7]	Qin Xujia, Zhang Qinfeng, Chen Jian, et al. GPU Accelerated Typhoon Visualization Method [J]. Journal of Image and Graphic, 2012, 17(2): 293-300(秦绪佳, 张勤锋, 陈坚, 等. GPU加速的台风可视化方法[J]. 中国图像图形学报, 2012,17(2): 293-300)
[8]	Kim C S, Parks K, Park J, et al. Scientific Visualization of Time-varying Oceanographic and Meteorological Data Using VR [C].The 16th IEEE Visualization 2005 (VIS 2005), Minneapolis, MN, USA, 2005
[9]	Xu Min, Fang Chaoyang, Zhu Qing, et al. Design and Implementation of Multidimension and Animated Visualization System for Ocean and Atmosphere [J]. Geomatics and Information Science of Wuhan University, 2009, 34(1): 57-59(徐敏, 方朝阳, 朱庆, 等. 海洋大气环境的多维动态可视化系统的设计与实现[J]. 武汉大学学报·信息科学版, 2009,34(1): 57-59)
[10]	Gore A. The Digital Earth: Understanding Our Planet in the 21st Century [J]. Australian Surveyor, 1998, 43(2): 89-91
[11]	Blenkinsop T. Visualizing Structural Geology: From Excel to Google Earth [J]. Computers & Geosciences, 2012, 45:52-56
[12]	Smith T M, Lakshmanan V. Real-time, Rapidly Updating Severe Weather Products for Virtual Globes [J]. Computers & Geosciences, 2011, 37(1): 3-12
[13]	Nguyen Q C,Soon K T. Google Earth as a Tool in 2D Hydrodynamic Modeling [J]. Computers & Geosciences, 2011, 37(1): 38-46
[14]	Ballagh L M, Raup B H, Duerr R E, et al. Representing Scientific Data Sets in KML: Methods and Challenges [J]. Computers & Geosciences, 2011, 37(1): 57-64
[15]	Bailey J E, Chen A. The Role of Virtual Globes in Geoscience [J]. Computers & Geosciences, 2011, 37(1): 1-2
[16]	Joseph T, Jeff H,Kim R, et al. A Tropical Cyclone Application for Virtual Globes [J]. Computers & Geosciences, 2011, 37(1): 13-24
[17]	Li J, Wu H, Yang C, et al. Visualizing Dynamic Geosciences Phenomena Using an Octree-based View-dependent LOD Strategy Within Virtual Globes [J]. Computers & Geosciences, 2011, 37(9): 1 295-1 302
[18]	Hogan P, Coughlan J. NASA World Wind, Open Source 4D Geospatial Visualization Platform:. NET & Java [C]. AGU Fall Meeting Abstracts, San Francisco, USA, 2006
[19]	Snyder J P. Map Projections—A Working Manual [R]. United States Government Printing Office, Washington D C,1987
[20]	Evenden G I. Cartographic Projection Procedures for the UNIX Environment: A User's Manual [R]. Open-File Report 90284,United States Geological Survey, Washington D C, USA,1990
[21]	Guthe S, Wand M, Gonser J, et al. Interactive Rendering of Large Volume Data Sets [C].IEEE Visualization, 2002 VIS 2002, Boston, MA, USA, 2002
[22]	Kniss J, Mccormick P, Mcpherson A, et al. Interactive Texture-based Volume Rendering for Large Data Sets [J]. IEEE Computer Graphics and Applications, 2001, 21(4): 52-61
[23]	Boada I, Navazo I, Scopigno R. Multiresolution Volume Visualization with a Texture-based Octree [J]. The Visual Computer, 2001, 17(3): 185-197
[24]	Lamar E, Hamann B, Joy K I. Multiresolution Techniques for Interactive Texture-based Volume Visualization [C].The Conference on Visualization'99: Celebrating Ten Years, San Francisco, California, United States, 1999
[25]	Yang C, Wu L. GPU-Based Volume Rendering for 3D Electromagnetic Environment on Virtual Globe [J]. International Journal of Image, Graphics and Signal Processing, 2010, 2(1): 53-60
[26]	Li W, Mueller K, Kaufman A. Empty Space Skipping and Occlusion Clipping for Texture-based Volume Rendering [C]. The 14th IEEE Visualization 2003 (VIS 2003), Seattle, Washington D C, USA, 2003
[27]	Kruger J, Westermann R. Acceleration Techniques for GPU-based Volume Rendering [C]. The 14th IEEE Visualization 2003 (VIS 2003), Seattle,Washington D C,USA, 2003
[28]	Konikow L F, Bredehoeft J D. Computer Model of Two-dimensional Solute Transport and Dispersion in Ground Water [R]. US Government Printing Office, Washington D C, USA,1978
[29]	Butcher U J C. The Numerical Analysis of Ordinary Differential Equations: Runge-Kutta and General Linear Methods [M]. New York:Wiley-Interscience, 1987

施引文献(35)

期刊类型引用(15)

1.	肖泽辉，季青，庞小平，闫忠男. 利用海洋2B卫星数据反演南极海冰表面积雪厚度. 测绘地理信息. 2024(06): 64-68 . 百度学术
2.	张颖，刘建强，石立坚，蒋城飞. 极地海冰观测卫星的发展现状与展望. 遥感技术与应用. 2024(06): 1339-1352 . 百度学术
3.	陈国栋，陈钰，金涛勇，张志杰，李黎. 利用Cryosat-2 SAR模式数据确定北冰洋海平面模型. 大地测量与地球动力学. 2023(06): 606-611+621 . 百度学术
4.	于亚冉，王丽华，张梦悦. 基于CryoSat-2的北极海冰类型分类. 测绘与空间地理信息. 2022(01): 147-150 . 百度学术
5.	陈国栋，梁圣豪，孟子淇，朱家亨. 利用Cryosat-2数据确定格陵兰冰盖高程和体积变化. 苏州科技大学学报(自然科学版). 2022(01): 66-70+76 . 百度学术
6.	屈猛，赵羲，庞小平，雷瑞波. 北极冰间水道区域的物理过程和遥感观测研究进展. 地球科学进展. 2022(04): 382-391 . 百度学术
7.	高翔，庞小平，季青. 利用CryoSat-2测高数据研究南极威德尔海海冰出水高度时空变化. 武汉大学学报(信息科学版). 2021(01): 125-132 . 百度学术
8.	张婷，张杰，张晰. 基于CryoSat-2数据的2014—2018年北极海冰厚度分析. 海洋科学进展. 2020(03): 425-434 . 百度学术
9.	王志勇，王丽华，张晰，孙伟富，刘健. 雷达高度计在海冰厚度探测中的研究进展. 遥感信息. 2020(05): 1-8 . 百度学术
10.	满富康，夏文韬，张杰，柯长青. 基于OSI-SAF微波遥感数据的北极一年冰和多年冰研究. 极地研究. 2019(01): 69-83 . 百度学术
11.	吴星泉，张胜军，车德福. 利用CryoSat-2卫星测高资料确定北极海冰干舷高. 测绘通报. 2019(07): 64-68 . 百度学术
12.	庞小平，刘清全，季青. 北极一年海冰表面积雪深度遥感反演与时序分析. 武汉大学学报(信息科学版). 2018(07): 971-977 . 百度学术
13.	蒋广敏，戴利，代欣. 基于改进遗传算法的镀层氧化膜厚度测量研究. 周口师范学院学报. 2018(05): 121-124 . 百度学术
14.	王蔓蔓，柯长青，邵珠德. 基于CryoSat-2卫星测高数据的北极海冰体积估算方法. 海洋学报. 2017(03): 135-144 . 百度学术
15.	袁乐先，李斐，张胜凯，朱婷婷，左耀文. 利用ICESat/GLAS数据研究北极海冰干舷高度. 武汉大学学报(信息科学版). 2016(09): 1176-1182 . 百度学术