4.7 Article

Web-based 3D visualization framework for time-varying and large-volume oceanic forecasting data using open-source technologies

期刊

ENVIRONMENTAL MODELLING & SOFTWARE
卷 135, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2020.104908

关键词

3D visualization; WebGL; Volume rendering; Cesium virtual globe; Plotly

资金

  1. National Natural Science Foundation of China (NSFC) [61701487]
  2. Strategic Priority Research Program of Chinese Academy of Sciences [XDA13030102]
  3. Youth Innovation Promotion Association CAS

向作者/读者索取更多资源

The study utilized open-source visualization technologies to create a browser-based 3D visualization framework, providing users with 3D GIS experiences and efficient volume rendering and analysis. Experimental results demonstrate that this approach allows for quick establishment of 3D visualization applications without the need for complex programming and computations. Case studies suggest that this method is a feasible alternative for web-based 3D visualization with faster rendering speeds, high visual effects, and real-time visualization of oceanographic data.
There are limitations to traditional visualization solutions regarding real-time 3D visualization of time-varying and large-volume 3D gridded oceanographic data in a web environment. We adopted the open-source visualization technologies to implement a browser-based 3D visualization framework. The developed 3D visualization interfaces provide users 3DGIS experiences on a virtual globe and simultaneously provide efficient 3D volume rendering and enriched interactive volume analysis. Our experiments suggest that the well-designed Cesium and Plotly.js API allow researchers to easily establish 3D visualization applications while avoiding the requirements of intensive programming and computations. The case study conducted shows that the proposed methods is a feasible alternative web-based 3D visualization solution, which provides a faster rendering speed, high visual effects and on-the-fly 3D visualization of oceanographic data. Due to its open-source architecture and the simplicity of the adopted technologies, the visualization framework can be easily customized to visualize other scientific data with few modifications.

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