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Ocean data exhibits great heterogeneity from variances in measuring methods, formats, and quality, making it extremely complicated and diverse due to a variety of data kinds, sources, and study elements. A few examples of data sources are satellites, buoys, ships, self-driving cars, and distant systems. The processing of data is made more challenging by the significant regional and temporal variations in oceanic characteristics including temperature, salinity, and currents. This work presents an interactive tool for multivariate ocean parameter visualisation, specifically overlays, based on Python. In ocean data visualisation, overlays are extra visual layers or data points that are layered to improve comprehension over a basic map. Based on the available data and the visualisation goals, these overlays are chosen and blended. Users can customise overlays with this tool, which also supports formatting, 2D and 3D visualisation, and data preparation. In order to reduce artefacts, it uses kriging interpolation for 3D visualisation and a modified version of the ray casting algorithm for representing octree data. By integrating overlays like as bathymetry, currents, temperature, and marine life, users can produce visually appealing and comprehensive depictions of ocean data. This method provides a thorough grasp of intricate marine processes by making it easier to see patterns, trends, and abnormalities in the data.
Preetha et al. (Fri,) studied this question.