Abstract
In this paper, we propose an interactive visualization system for tropical cyclone data analysis. We collect historical tropical cyclone data, clean and preprocess them into a unified form for the following visual analysis. We design several views based on direct visualization and feature visualization to facilitate user understanding of the physical characteristics of tropical cyclones. Additionally, we use Support Vector Machines (SVM) to predict the tropical cyclone trajectories for users to make a deep analysis and assessment of the cyclone’s movement features. In this visual analysis process, we provide multiple linked views for physical characteristics exploration and cyclone trajectories prediction. Our system also supports multi-resolution analysis with temporal and spatial filtering. The experiments and user study demonstrate the effectiveness of our system.
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Xie, C., Luo, X., Ma, G., Gao, X., Dong, J. (2017). Multi-faceted Visual Analysis on Tropical Cyclone. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2017. Lecture Notes in Computer Science(), vol 10451. Springer, Cham. https://doi.org/10.1007/978-3-319-66805-5_33
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DOI: https://doi.org/10.1007/978-3-319-66805-5_33
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