A Python Framework for Interactive 3D Visualisation of Ocean Data
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8628-6_46
Reference10 articles.
1. Xie C, Li M, Wang H, Dong J (2019) A survey on visual analysis of ocean data. Visual Inf 3(3):113–128
2. Qin R, Feng B, Xu Z, Zhou Y, Liu L, Li Y (2021) Web-based 3D visualization framework for time-varying and large-volume oceanic forecasting data using open-source technologies. Environ Model Softw 135:104908
3. Gan C, Cao W-H, Liu K-Z, Wu M (2020) Spatial estimation for 3D formation drillability field: a new modeling framework. J Nat Gas Sci Eng 84:103628
4. Ali WH, Mirhi MH, Gupta A, Kulkarni CS, Foucart C, Doshi MM, Subramani DN, Mirabito C, Haley Jr PJ, Lermusiaux PF (2019) Seavizkit: interactive maps for ocean visualization. In: Oceans 2019 MTS/IEEE Seattle. IEEE, pp 1–10
5. Yano M, Itoh T, Tanaka Y, Matsuoka D, Araki F (2020) A comparative visualization tool for ocean data analysis based on mode water regions. J Visualization 23(2):313–329
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