Since the e-Navigation strategy was put forward, various countries and regions in the world have researched e-Navigation test platforms. However, the sources of navigation data are multi-source, and there are still difficulties in the unified acquisition, processing, analysis and application of multi-source data. Users often find it difficult to obtain the required comprehensive navigation information. The purpose of this paper is to use e-Navigation architecture to design and develop maritime data security management platform, strengthen navigation safety guarantee, strengthen Marine environment monitoring, share navigation and safety information, improve the ability of shipping transportation organizations in ports, and protect the marine environment. Therefore, this paper proposes a four-layer system architecture based on Java 2 Platform Enterprise Edition (J2EE) technology, and designs a unified maritime data storage, analysis and management platform, which realizes the intelligent, visualized and modular management of maritime data at shipside and the shore. This platform can provide comprehensive data resource services for ship navigation and support the analysis and mining of maritime big data. This paper expounds on the design, development scheme and demonstration operation scheme of the maritime data security management platform from the system structure and data exchange mode.

The three-dimensional (3D) visualization of the electronic navigation chart (ENC) can reflect the marine environment and various marine features truly, accurately, and directly, to reduce misoperation during chart use and improve the convenience of using the chart. Due to a large amount of ENC data, complex data structure, and uneven distribution in 3D space, the construction and real-time rendering of 3D ENCs depend on the retrieval speed of 3D spatial data. Improving the spatial retrieval efficiency of 3D ENC data is helpful for the rapid rendering of a 3D scene. In this paper, based on the S-100 universal hydrological data model (S-100) and the 3D characteristics to classify the ENC features and create the 3D ENC data set, a hybrid spatial index structure is proposed based on quadtree and R-tree and ENC features data structure, using the smallest minimum bounding box (SMBB) and classification retrieval methods to optimize the spatial index structure. All the ENC features are rendered in a 3D marine scene. By analyzing the overlap of ENC features and testing the efficiency of spatial index structure, the results show that this method can effectively reduce the overlap rate of index nodes and improve the efficiency of data retrieval, realize the effective management of 3D ENC data, and improve the drawing speed of 3D ENCs.

Spatial relation models are the basis for realising three-dimensional spatial analysis. More researchers are now focusing on models that combine topological relations with distance or directional relations; however, a model that unifies all three relations has not yet been developed. In particular, it is more effective to use different spatial relations between features with different spatial characteristics in three-dimensional electronic navigation charts (3D ENC). Therefore, this paper proposes a 3D ENC feature spatial relation model (3DSRM) based on point-set topology theory, which combines 3D topological relations, distance relations and directional relations, and uses a unified model framework to describe 64 topological relations of 3D ENC features from both horizontal and vertical directions. Through the comparison and derivation of feature topological relations, it is demonstrated that the model can distinguish 3D spatial topological relations more comprehensively, realise the mutual derivation between spatial relations and spatial features, and improve the robustness of spatial relations judgement. The model can be used to judge the topological relations between features, realise 3D topological relation checking and topological creation of complex features, and improve the accuracy and interactivity of 3D ENC.