Development of a component-based interactive visualization system for the analysis of ocean data

References

• Andrienko, N., & Andrienko, G. (2013). A visual analytics framework for spatio-temporal analysis and modelling. Data Mining and Knowledge Discovery, 27(1), 55–83.
   Web of Science ®Google Scholar
• Feng, J., Tian, X.-L., Dong, S.-L., He, R.-P., Zhang, K., Zhang, D.-X., Li, L., Zhang, Q.-Q., & Zhang, T. (2018b). Comparative analysis of the energy fluxes and trophic structure of polyculture ecosystems of Portunus trituberculatus based on Ecopath model. Aquaculture, 496, 185–196.
   Web of Science ®Google Scholar
• Feng, X., Li, M., Yin, B., Yang, D., & Yang, H. (2018a). Study of storm surge trends in typhoon-prone coastal areas based on observations and surge-wave coupled simulations. International Journal of Applied Earth Observation and Geoinformation, 68, 272–278.
   Web of Science ®Google Scholar
• Franz, K., Roscher, R., Milioto, A., Wenzel, S., & Kusche, J. (2018). Ocean Eddy Identification and Tracking Using Neural Networks. IGARSS 2018—2018 IEEE International Geoscience and Remote Sensing Symposium, (pp. 6887–6890). Germany: Bonn.
   Google Scholar
• Fu, Y., Luan, G., Cai, J., Li, Y., & Zhao, F. (2020). Construction and application research of ecological evaluation platform based on Cesium. Water Supply, 21(3), 983–991.
   Google Scholar
• Fulton, S., & Fulton, J. (2013). HTML5 Canvas: Native Interactivity and Animation for the Web. O’Reilly Media, Inc. America: Sebastopol.
   Google Scholar
• GeoServer. (2021). GeoServer. Retrieved from August 10, 2021, http://geoserver.org/
   Google Scholar
• Guidi, L., Fernàndez-Guerra, A., Canchaya, C., Curry, E., Foglini, F., Irisson, J.-O., Malde, K., Marshall C. T., Obst M., Ribeiro R. P., Tjiputra J., Bakker D. C. E., Alexander B., Heymans S. J. J., Muñiz Piniella A., Kellett P., & Coopman J. (2020). Big data in marine science. Marine Board Future Science Brief Belgium: Oostende.
   Google Scholar
• Han, J., . E., . H., Le, G., & Du, J. (2011). Survey on NoSQL database. 2011 6th International Conference on Pervasive Computing and Applications (pp. 363–366). South Africa: Port Elizabeth.
   Google Scholar
• Kappe, C. P., Böttinger, M., & Leitte, H. (2019). Exploring Variability within Ensembles of Decadal Climate Predictions. IEEE Transactions on Visualization and Computer Graphics, 25(3), 1499–1512.
   Web of Science ®Google Scholar
• Klonaris, G., Van Eeden, F., Verbeurgt, J., Troch, P., Constales, D., Poppe, H., & De Wulf, A. (2021). ROMS based hydrodynamic modelling focusing on the belgian part of the Southern North Sea. Journal of Marine Science and Engineering, 9(1), 58.
   Web of Science ®Google Scholar
• Li, S., Jaroszynski, S., Pearse, S., Orf, L., & Clyne, J. (2019). VAPOR: A Visualization Package Tailored to Analyze Simulation Data in Earth System Science. Atmosphere, 10(9), 488.
   Web of Science ®Google Scholar
• Li, X., Liu, B., Zheng, G., Ren, Y., Zhang, S., Liu, Y., Gao, L., Liu, Y., Zhang, B., & Wang, F. (2020). Deep-learning-based information mining from ocean remote-sensing imagery. National Science Review, 7(10), 1584–1605.
   PubMed Web of Science ®Google Scholar
• Liu, B., Li, X., & Zheng, G. (2019). Coastal Inundation Mapping From Bitemporal and Dual-Polarization SAR Imagery Based on Deep Convolutional Neural Networks. Journal of Geophysical Research: Oceans, 124(12), 9101–9113.
   Web of Science ®Google Scholar
• Liu, S., Chen, G., Yao, S., Tian, F., & Liu, W. (2017). A framework for interactive visual analysis of heterogeneous marine data in an integrated problem solving environment. Computers & Geosciences, 104, 20–28.
   Web of Science ®Google Scholar
• Metzger, E. J., Hogan, P. J., Shriver, J. F., Thoppil, P. G., Douglass, E., Yu, Z., Allard, R. A., Rowley, C. D., Smedstad, O. M., Franklin, D. S., Phelps, M. W., Zamudio, L., Wallcraft, A. J., & Richman, J. R. (2020). Validation Test Report for the Global Ocean Forecast System 3.5—1/25 degree HYCOM/CICE with Tides. Washington DC: Naval Research Lab.
   Google Scholar
• MinIO, I. (n.d.). MinIO | High Performance, Kubernetes Native Object Storage. MinIO. Retrieved from August 7, 2021, https://min.io
   Google Scholar
• Pautasso, C. (2014). RESTful Web Services: Principles, Patterns, Emerging Technologies. In A. Bouguettaya, Q. Z. Sheng, & F. Daniel (Eds.), Web Services Foundations (pp. 31–51). New York: Springer.
   Google Scholar
• Rautenhaus, M., Kern, M., Schäfler, A., & Westermann, R. (2015). Three-dimensional visualization of ensemble weather forecasts – Part 1: The visualization tool Met.3D (version 1.0). Geoscientific Model Development, 8(7), 2329–2353.
   Web of Science ®Google Scholar
• Sacha, D., Zhang, L., Sedlmair, M., Lee, J. A., Peltonen, J., Weiskopf, D., North, S. C., & Keim, D. A. (2017). Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis. IEEE Transactions on Visualization and Computer Graphics, 23(1), 241–250.
   Web of Science ®Google Scholar
• Thomas, J. J., & Cook, K. A. (2006). A visual analytics agenda. IEEE Computer Graphics and Applications, 26(1), 10–13.
   PubMed Web of Science ®Google Scholar
• Wang, Y., Li, X., Song, J., Li, X., Zhong, G., & Zhang, B. (2021). Carbon Sinks and Variations of pCO2 in the Southern Ocean From 1998 to 2018 Based on a Deep Learning Approach. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3495–3503.
   Web of Science ®Google Scholar
• Xie, C., Li, M., Wang, H., & Dong, J. (2019). A survey on visual analysis of ocean data. Visual Informatics, 3(3), 113–128.
   Google Scholar
• Zhang, X., Li, X., & Zheng, Q. (2021). A Machine-Learning Model for Forecasting Internal Wave Propagation in the Andaman Sea. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3095–3106.
   Web of Science ®Google Scholar
• Zheng, G., Li, X., Zhang, R.-H., & Liu, B. (2020). Purely satellite data–driven deep learning forecast of complicated tropical instability waves. Science Advances, 6(29), 1482.
   Web of Science ®Google Scholar