Research on Three-Dimensional Electronic Navigation Chart Hybrid Spatial Index Structure Based on Quadtree and R-Tree

Abstract

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.