A geometry-based method for visualizing time-varying flow fields on web map platforms using texture polymorphism
Yucheng Shu
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorZihao Tang
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorYiming Zhang
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorYongning Wen
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorMin Chen
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorCorresponding Author
Songshan Yue
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Correspondence
Songshan Yue, School of Geography, Nanjing Normal University, Nanjing 210023, China.
Email: [email protected]
Search for more papers by this authorYucheng Shu
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorZihao Tang
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorYiming Zhang
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorYongning Wen
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorMin Chen
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Search for more papers by this authorCorresponding Author
Songshan Yue
School of Geography, Nanjing Normal University, Nanjing, China
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Correspondence
Songshan Yue, School of Geography, Nanjing Normal University, Nanjing 210023, China.
Email: [email protected]
Search for more papers by this authorAbstract
Global climate change has escalated flood risks, necessitating advanced hydrodynamic models for predicting watershed dynamics. Integrating flow-field visualization with web maps offers a time-sensitive, geographic context for sharing and understanding these dynamic changes virtually. Traditional methods use texture series on maps for flow visualization but fall short in interactive detail examination. Drawing geometric shapes directly on maps has been limited by low efficiency. Addressing the need for interactive visualization and efficiency, this study presents a texture polymorphism strategy for geometric visualization of time-varying flow fields. This approach combines geometric style simulation with texture-assisted computation, optimizing interactivity and performance on web map platforms. Our evaluation confirms that this method enhances usability and integration, ensuring high performance in visualizing flow dynamics.
CONFLICT OF INTEREST STATEMENT
The authors have no conflict of interest to declare.
Open Research
DATA AVAILABILITY STATEMENT
FowFieldVisualization are available at: https://doi.org/10.6084/m9.figshare.23669199 and https://doi.org/10.6084/m9.figshare.23685909.
Supporting Information
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Appendix S1.. |
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REFERENCES
- Brewer, C. A., Hatchard, G. W., & Harrower, M. A. (2003). ColorBrewer in print: A catalog of color schemes for maps. Cartography and Geographic Information Science, 30(1), 5–32. https://doi.org/10.1559/152304003100010929
10.1559/152304003100010929 Google Scholar
- Brunner, G. W. (1995). HEC-RAS river analysis system. Hydraulic reference manual. Version 1.0. Hydrologic Engineering Center.
- Bryanrideshark. (2023). WebGPU support? · Issue #9646 · mapbox/mapbox-gl-js. https://github.com/mapbox/mapbox-gl-js/issues/9646
- Bujack, R., & Middel, A. (2020). State of the art in flow visualization in the environmental sciences. Environmental Earth Sciences, 79(2), 65. https://doi.org/10.1007/s12665-019-8800-4
- Chen, C., Beardsley, R., Cowles, G., Qi, J., Lai, Z., Gao, G., Stuebe, D., Xu, Q., Xue, P., & Ge, J. (2012). An unstructured-grid, finite-volume community ocean model: FVCOM user manual. Sea Grant College Program, Massachusetts Institute of Technology Cambridge ….
- Dakkak, A., Pearson, C., Hwu, W. M., & IEEE. (2016). WebGPU: A scalable online development platform for GPU programming courses. IEEE 30th International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Illinois Inst Technol, Chicago, IL
- Dharma, D., Jonathan, C., Kistidjantoro, A. I., & Manaf, A. (2017). Material point method based fluid simulation on GPU using compute shader. International Conference on Advanced Informatics, Concepts, Theory, and Applications (ICAICTA), Denpasar, Indonesia.
10.1109/ICAICTA.2017.8090962 Google Scholar
- Doleisch, H., Mayer, M., Gasser, M., Wanker, R., & Hauser, H. (2004). Case study: Visual analysis of complex, time-dependent simulation results of a diesel exhaust system. 6th Joint Eurographics—IEEE TCVG Conference on Visualization, Konstanz, Germany.
- Esri. (2014). Wind-JS. https://github.com/Esri/wind-js
- Galaz, J., Cienfuegos, R., Echeverría, A., Pereira, S., Bertin, C., Prato, G., & Karich, J.-C. (2022). Integrating tsunami simulations in web applications using BROWNI, an open source client-side GPU-powered tsunami simulation library. Computers & Geosciences, 159(104), 976. https://doi.org/10.1016/j.cageo.2021.104976
10.1016/j.cageo.2021.104976 Google Scholar
- Goodchild, M. F., Yuan, M., & Cova, T. J. (2007). Towards a general theory of geographic representation in GIS. International Journal of Geographical Information Science, 21(3), 239–260. https://doi.org/10.1080/13658810600965271
- Guo, M., Huang, Y., Guan, Q., Xie, Z., & Wu, L. (2017). An efficient data organization and scheduling strategy for accelerating large vector data rendering. Transactions in GIS, 21(6), 1217–1236. https://doi.org/10.1111/tgis.12275
- Heer, J., & Shneiderman, B. (2012). Interactive dynamics for visual analysis. Communications of the ACM, 55(4), 45–54. https://doi.org/10.1145/2133806.2133821
- InMeteo. (2023). Ventusky—Wind, rain and temperature maps. https://www.ventusky.com/
- Ivo. (2014). Windy: Wind map & weather forecast. https://www.windy.com/
- Kenwright, D. N., & Mallinson, G. D. (1992). A 3-D streamline tracking algorithm using dual stream functions. Proceedings Visualization '92, Boston, MA, USA. https://doi.org/10.1109/VISUAL.1992.235225
10.1109/VISUAL.1992.235225 Google Scholar
- Klassen, R. V., & Harrington, S. J. (1991). Shadowed hedgehogs: A technique for visualizing 2D slices of 3D vector fields. Proceedings Visualization '91, San Diego, California (pp. 148–1530). IEEE Computer Society Press. https://doi.org/10.1109/VISUAL.1991.175792
10.1109/VISUAL.1991.175792 Google Scholar
- Lane, D. A. (1994). UFAT-a particle tracer for time-dependent flow fields. Proceedings Visualization '94, Washington, DC, USA. https://doi.org/10.1109/VISUAL.1994.346311
10.1109/VISUAL.1994.346311 Google Scholar
- Laramee, R. S., Erlebacher, G., Garth, C., Schafhitzel, T., Theisel, H., Tricoche, X., Weinkauf, T., & Weiskopf, D. (2008). Applications of texture-based flow visualization. Engineering Applications of Computational Fluid Mechanics, 2(3), 264–274. https://doi.org/10.1080/19942060.2008.11015227
- Laramee, R. S., Hauser, H., Doleisch, H., Vrolijk, B., Post, F. H., & Weiskopf, D. (2004). The state of the art in flow visualization: Dense and texture-based techniques. In Computer graphics forum (Vol. 23, pp. 203–221). Wiley Online Library. https://doi.org/10.1111/j.1467-8659.2004.00753.x
10.1111/j.1467-8659.2004.00753.x Google Scholar
- Laramee, R. S., Jobard, B., & Hauser, H. (2003). Image space based visualization of unsteady flow on surfaces. IEEE Visualization, 2003. VIS 2003 (pp. 131–138). https://doi.org/10.1109/VISUAL.2003.1250364
10.1109/VISUAL.2003.1250364 Google Scholar
- Li, W., Chen, G., Kong, Q., Wang, Z., & Qian, C. (2011). A VR-Ocean system for interactive geospatial analysis and 4D visualization of the marine environment around Antarctica. Computers & Geosciences, 37(11), 1743–1751. https://doi.org/10.1016/j.cageo.2011.04.009
- Li, Y., Gong, J., Liu, H., Zhu, J., Song, Y., & Liang, J. (2015). Real-time flood simulations using CA model driven by dynamic observation data. International Journal of Geographical Information Science, 29(4), 523–535. https://doi.org/10.1080/13658816.2014.977292
- Mann, J. (1998). Wind field simulation. Probabilistic Engineering Mechanics, 13(4), 269–282. https://doi.org/10.1016/S0266-8920(97)00036-2
- Nardini, P., Böttinger, M., Scheuermann, G., & Schmidt, M. (2017). Visual study of the benguela upwelling system using pathline predicates. Proceedings of the Workshop on Visualisation in Environmental Sciences, Barcelona, Spain. https://doi.org/10.2312/envirvis.20171099
- Nehab, D., & Hoppe, H. (2008). Random-access rendering of general vector graphics. ACM Transactions on Graphics, 27(5), Article 135. https://doi.org/10.1145/1409060.1409088
- Patrick, C. (2023). WebGPU renderer · issue #4989 · CesiumGS/cesium. https://github.com/CesiumGS/cesium/issues/4989
- Peterka, T., Ross, R., Nouanesengsy, B., Lee, T. Y., Shen, H. W., Kendall, W., & Huang, J. (2011). A study of parallel particle tracing for steady-state and time-varying flow fields. IEEE International Parallel & Distributed Processing Symposium, Anchorage, AK, USA. https://doi.org/10.1109/IPDPS.2011.62
10.1109/IPDPS.2011.62 Google Scholar
- Porcu, E., Bevilacqua, M., & Genton, M. G. (2016). Spatio-temporal covariance and cross-covariance functions of the great circle distance on a sphere. Journal of the American Statistical Association, 111(514), 888–898. https://doi.org/10.1080/01621459.2015.1072541
- Puech, W., Borş, A. G., Pitas, I., & Chassery, J.-M. (2001). Projection distortion analysis for flattened image mosaicing from straight uniform generalized cylinders. Pattern Recognition, 34(8), 1657–1670. https://doi.org/10.1016/S0031-3203(00)00056-X
- Richard, Y. (2021). Maximum values of texture dimension. https://github.com/gpuweb/gpuweb/issues/1327
- Roelvink, J., & Van Banning, G. (1995). Design and development of DELFT3D and application to coastal morphodynamics. Oceanographic Literature Review, 11(42), 925.
- Rougier, N. (2013). Higher quality 2D text rendering. Journal of Computer Graphics Techniques, 2(1), 50–64. https://inria.hal.science/hal-00821839
- She, J., Li, C., Li, J., & Wei, Q. (2018). An efficient method for rendering linear symbols on 3D terrain using a shader language. International Journal of Geographical Information Science, 32(3), 476–497. https://doi.org/10.1080/13658816.2017.1394463
- Van Wijk, J. J. (2002). Image based flow visualization. 29th Annual Conference on Computer Graphics and Interactive Techniques, San Antonio, Texas. https://doi.org/10.1145/566570.566646
10.1145/566570.566646 Google Scholar
- Vaněček, P. (2004). Triangle strips for fast rendering. https://www.kiv.zcu.cz/cz/vyzkum/publikace/technicke-zpravy/2004/tr-2004-05-.pdfpdf
- Weiskopf, D., & Ertl, T. (2004). A hybrid physical/device-space approach for spatio-temporally coherent interactive texture advection on curved surfaces. Graphics Interface 2004, London, Ontario, Canada.
- Woodring, J., Petersen, M., Schmeißer, A., Patchett, J., Ahrens, J., & Hagen, H. (2016). In situ eddy analysis in a high-resolution ocean climate model. IEEE Transactions on Visualization and Computer Graphics, 22(1), 857–866. https://doi.org/10.1109/TVCG.2015.2467411
- Yao, A., Wang, L., Li, J., Xia, X., Jin, X., & Jing, N. (2020). 2D/3D visualization of large-scale wind field based on WebGL. International Conference on Aviation Safety and Information Technology, Weihai City, China. https://doi.org/10.1145/3434581.3434662
10.1145/3434581.3434662 Google Scholar
- Yue, S., Yang, J., Chen, M., Lu, G., Zhu, A. X., & Wen, Y. (2016). A function-based linear map symbol building and rendering method using shader language. International Journal of Geographical Information Science, 30(2), 143–167. https://doi.org/10.1080/13658816.2015.1077964
- Zhang, F., Mao, R., Du, Z., & Liu, R. (2019). Spatial and temporal processes visualization for marine environmental data using particle system. Computers & Geosciences, 127, 53–64. https://doi.org/10.1016/j.cageo.2019.02.012
- Zhang, S., Li, W., Lei, X., Ding, X., & Zhang, T. (2017). Implementation methods and applications of flow visualization in a watershed simulation platform. Advances in Engineering Software, 112, 66–75. https://doi.org/10.1016/j.advengsoft.2017.06.016
- Zhang, S., Xia, Z., & Wang, T. (2013). A real-time interactive simulation framework for watershed decision making using numerical models and virtual environment. Journal of Hydrology, 493, 95–104. https://doi.org/10.1016/j.jhydrol.2013.04.030
- Zioma, R. (2007). Gpu gems 3. Addison-Wesley Professional. https://developer.nvidia.com/gpugems/gpugems3/part-i-geometry/chapter-6-gpu-generated-procedural-wind-animations-trees