Web-based spatiotemporal visualization of marine environment data

Yawen He; Fenzhen Su; Yunyan Du; Rulin Xiao

doi:10.1007/s00343-010-0029-8

Your Location：

Home >

Browse articles >

Web-based spatiotemporal visualization of marine environment data

Updated：2023-05-16

- Web-based spatiotemporal visualization of marine environment data
- Journal of Oceanology and Limnology Vol. 28, Issue 5, Pages: 1086-1094(2010)
- Affiliations：
  
  1. Institute of Geographic Sciences and Natural Resources Research CAS
  2. Yantai Institute of Coastal Zone Research CAS
  3. Graduate School of Chinese Academy of Sciences
- Author bio：
- Funds：
- DOI：10.1007/s00343-010-0029-8
  CLC：
- Online First：11 September 2010，
  
  Published：2010
- Accepted：
Scan QR Code
He, Y., Su, F., Du, Y. et al. Web-based spatiotemporal visualization of marine environment data., Chin. J. Ocean. Limnol. 28, 1086–1094 (2010). https://doi.org/10.1007/s00343-010-0029-8
DOI：

He, Y., Su, F., Du, Y. et al. Web-based spatiotemporal visualization of marine environment data., Chin. J. Ocean. Limnol. 28, 1086–1094 (2010). https://doi.org/10.1007/s00343-010-0029-8 DOI：

摘要

Abstract

With long-term marine surveys and research

and especially with the development of new marine environment monitoring technologies

prodigious amounts of complex marine environmental data are generated

and continuously increase rapidly. Features of these data include massive volume

widespread distribution

multiple-sources

heterogeneous

multi-dimensional and dynamic in structure and time. The present study recommends an integrative visualization solution for these data

to enhance the visual display of data and data archives

and to develop a joint use of these data distributed among different organizations or communities. This study also analyses the web services technologies and defines the concept of the marine information gird

then focuses on the spatiotemporal visualization method and proposes a process-oriented spatiotemporal visualization method. We discuss how marine environmental data can be organized based on the spatiotemporal visualization method

and how organized data are represented for use with web services and stored in a reusable fashion. In addition

we provide an original visualization architecture that is integrative and based on the explored technologies. In the end

we propose a prototype system of marine environmental data of the South China Sea for visualizations of Argo floats

sea surface temperature fields

sea current fields

salinity

in-situ investigation data

and ocean stations. An integration visualization architecture is illustrated on the prototype system

which highlights the process-oriented temporal visualization method and demonstrates the benefit of the architecture and the methods described in this study.

关键词

Keywords

references

Beard K, Deese H, Pettigrew N R. 2008. A framework for visualization and exploration of events. Information Visualization, 7(2): 133–151.

Bethel W. 2000. Visapult: A Prototype Remote and Distributed Visualization Application and Framework. In: Proceedings of the Conference Abstracts and Applications, Sketches and Applications, ACM SIGGRAPH 2000, LBNL(45215): 1–3.

Brodlie K W, Duce D A, Gallop J R. et al. 2004. Distributed and collaborative visualization. Computer Graphics Forum, 23(2): 223–251.

Chen S P. 2006. Typhoon disaster prevention and reduction information system. Geo-Information Science, 8(4): 1–3. (in Chinese with English abstract)

Dimmestol T, Lucas A. 1992. Integrating GIS with ocean models to simulate and visualize spills. In: Proceedings of the 4th Scandinavian Research Conference on GIS, Helsinki, Finland. p. 225–240.

El-Geresy B A, Abdelmoty A I, Jones C B. 2002. Spatio-temporal geographic information systems: a causal perspective. Advances in Databases and Information Systems (ADBIS), LNCS(2435): 191–203.

Foster I, Kesselman C. 1997. Globus: a meta-computing infrastructure toolkit. Supercomputer Application, 11(2): 115–128.

Foster I, Kesselman C. 1998. Computational Grids. The Grid: Blueprint for a New Computing Infrastructures, Mogan Kaufmann Publishers, San Francisco, USA. p. 12–25.

Foster I. 2002. What is the Grid? A Three Point Checklist. GRID Today, 7(20): 252–261.

Gong J H, Lin H, Xiao L B et al. 1999. Perspective on geo-visualization. Journal of Remote Sensing, 3(3): 236–243. (in Chinese with English abstract)

Gong J H. 2008. Exploring human-oriented geo-visualization. Journal of Remote Sensing, 12(5): 772–779. (in Chinese with English abstract)

Gong J Y, Li D R. 2008. Review of the development of geospatial information service technology. Bulletin of Surveying and Mapping, 6(5): 5–10. (in Chinese with English abstract)

He Y W, Du Y Y, Xiao R L et al. 2009. Design and implementation of a web services-based application framework for sea surface temperature information. Advances in Earth Science, 24(11): 1 254–1 259. (in Chinese with English abstract)

Jaswal V. 1997, CAVEvis: distributed real-time visualization of time-varying scalar and vector fields using the CAVE virtual reality theater. In: Proceedings of the 8th conference on Visualization’ 97, Phoenix, Arizona, United States. p. 301.

Kettner L, Rossignac J, Snoeyink J. 2003. The safari interface for visualizing time-dependent volume data using iso-surfaces and contour spectra. Computational Geometry: Theory and Applications, 5(1–2): 97–116.

Lane D A. 1993. Visualization of Time-Dependent Flow Fields. In: Proceedings of Visualizaton’93, IEEE Computer Society Press, San Jose, CA, USA. p. 32–38.

Lane D A. 1994. UFAT: a particle tracer for time-dependent flow fields. In: Proceedings of the Conference on Visualization 1994, Washington DC, USA. p. 17–21.

Li D R, Wang Y D, Zhu Q, Gong J Y. 1999. Data model and visualization of 3D city landscape based on integrated database. Geo-Spatial Information Science, 2(2): 21–25. (in Chinese with English abstract)

Li D R, Zhu X Y, Gong J Y. 2003. From digital map to spatial information multi-grid-thought of spatial information multi-grid theory. Geomantics and Information Science of Wuhan University, 28(6): 642–650. (in Chinese with English abstract)

Nelson M, Crawfis R, Grant C. 1994. Visualizing 3D velocity fields near contour surfaces. In: Proceedings of IEEE Visualization 1994, Washington DC, USA. p. 248–255.

Neun M, Burghardt D, Weibel R. 2008. Web service approaches for providing enriched data structures to generalization operators. International Journal of Geographical Information Science, 22(2): 133–165.

Peuquet D J. 1994. It’s about time: a conceptual framework for the representation of temporal dynamics in geographic information systems. Annals of the Association of American Geographers, 84(3): 441–446.

Regnauld N. 2006. Improving Efficiency for Developing Automatic Generalization Solutions. In: Proceedings of ISPRS Workshop: Multiple Representation and Interoperability of Spatial Data, Hannover, Germany. p. 1–5.

Sao. 2001. Research on Temporal Representation of Marine Geographic Information. Ph. D thesis, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China, p. 12–30.

Su F Z, Zhou C H. 2006. A framework for process geographical information system. Geographical Research, 25(3): 477–484. (in Chinese with English abstract)

Su F Z, Zhou C H, Yang X M et al. 2004. Definition and structure of marine geographic information system. Acta Oceanologica Sinica, 26(6): 22–28. (in Chinese with English abstract)

Su F Z, Zhou C H, Lyne V et al. 2004. A data mining approach to determine the spatio-temporal relationship between environmental factors and fish distribution. Ecological Modeling, 174(4): 421–431.

Wood J, Wright H, Brodie K. 1997. Collaborative Visualization. In: Proceedings of the Conference on Visualization’ 97, Phoenix, Arizona, USA. p. 253-ff.

Wright D J, Barlett D J et al. 1999. Marine and Coastal Geographical Information System. Taylor & Francis Inc. London. p. 11–254.

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

Development and application of a GIS-based artificial neural network system for water quality prediction: a case study at the Lake Champlain area

Effects of Rake Measurements on Turbine Efficiency

Research on Air Turbo Ramjet Expander Performance Optimization Based on Diversity Improved NSGA II Algorithm

Parametric Model of Lubricant Particle Trajectory inAnnulus Inter-Spools

Numerical Study of High Bypass Ratio Fan/BoosterStage with Inlet Distortion

Related Author

Fang LU

Haoqing ZHANG

Wenquan LIU

Related Institution

Shandong Provincial Key Laboratory of Marine Environment and Geological Engineering, Ocean University of China

Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology

Key Laboratory of Marine Environment and Ecology, Ministry of Education

Key Laboratory of Marine Sedimentology and Environmental Geology, First Institute of Oceanography, Ministry of Natural Resources(MNR)

Address：Editorial Office of JOL, 88 Haijun Rd. Qingdao, 266000, China
Tel：+86-532-82898754 Email：jol@qdio.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰