TY - JOUR
T1 - Web-scale multidimensional visualization of big spatial data to support earth sciences—a case study with visualizing climate simulation data
AU - Wang, Sizhe
AU - Li, Wenwen
AU - Wang, Feng
N1 - Funding Information:
Acknowledgments: This project is supported by the National Science Foundation (PLR-1349259; BCS-1455349; and PLR-1504432).
Publisher Copyright:
© 2017 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2017/9
Y1 - 2017/9
N2 - The world is undergoing rapid changes in its climate, environment, and ecosystems due to increasing population growth, urbanization, and industrialization. Numerical simulation is becoming an important vehicle to enhance the understanding of these changes and their impacts, with regional and global simulation models producing vast amounts of data. Comprehending these multidimensional data and fostering collaborative scientific discovery requires the development of new visualization techniques. In this paper, we present a cyberinfrastructure solution—PolarGlobe—that enables comprehensive analysis and collaboration. PolarGlobe is implemented upon an emerging web graphics library, WebGL, and an open source virtual globe system Cesium, which has the ability to map spatial data onto a virtual Earth. We have also integrated volume rendering techniques, value and spatial filters, and vertical profile visualization to improve rendered images and support a comprehensive exploration of multi-dimensional spatial data. In this study, the climate simulation dataset produced by the extended polar version of the well-known Weather Research and Forecasting Model (WRF) is used to test the proposed techniques. PolarGlobe is also easily extendable to enable data visualization for other Earth Science domains, such as oceanography, weather, or geology.
AB - The world is undergoing rapid changes in its climate, environment, and ecosystems due to increasing population growth, urbanization, and industrialization. Numerical simulation is becoming an important vehicle to enhance the understanding of these changes and their impacts, with regional and global simulation models producing vast amounts of data. Comprehending these multidimensional data and fostering collaborative scientific discovery requires the development of new visualization techniques. In this paper, we present a cyberinfrastructure solution—PolarGlobe—that enables comprehensive analysis and collaboration. PolarGlobe is implemented upon an emerging web graphics library, WebGL, and an open source virtual globe system Cesium, which has the ability to map spatial data onto a virtual Earth. We have also integrated volume rendering techniques, value and spatial filters, and vertical profile visualization to improve rendered images and support a comprehensive exploration of multi-dimensional spatial data. In this study, the climate simulation dataset produced by the extended polar version of the well-known Weather Research and Forecasting Model (WRF) is used to test the proposed techniques. PolarGlobe is also easily extendable to enable data visualization for other Earth Science domains, such as oceanography, weather, or geology.
KW - Big data
KW - Octree
KW - Scientific visualization
KW - Vertical profile
KW - Virtual globe
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U2 - 10.3390/informatics4030017
DO - 10.3390/informatics4030017
M3 - Article
AN - SCOPUS:85053053821
SN - 2227-9709
VL - 4
JO - Informatics
JF - Informatics
IS - 3
M1 - 17
ER -