Spatial indexing technology is widely used in Geographic Information Systems (GIS) and spatial databases. As a data retrieval technology, spatial indexing is becoming increasingly important in the big-data age. The purpose of this study is to propose a unified indexing strategy for the mixed data of a future marine GIS. First, data organisation of the system is described. Second, the display condition of each type of data is introduced. These conditions are the basis for the construction of a unified indexing structure. Third, a unified indexing structure for mixed data is presented. The construction process and the search method of the indexing structure are described. Finally, we implement the indexing strategy in our system “Automotive Intelligent Chart Three-dimensional Electronic Chart Display and Information Systems” (AIC 3D ECDIS). Our strategy can provide fast and integrated data retrieval. The spatial indexing strategy we propose breaks through the limitation of data types in our system. It can also be applied in other GIS systems. With the advent of the big-data age, mixed data indexing will become more and more important.

The rapid development of positioning technology, wireless communication and mobile devices has given rise to the exciting Location Based Services (LBS) thus significantly influencing existing navigational procedures. Motivated by the increasing need to search efficiently through a huge number of service locations (e.g. restaurants, hotels, shops, and more), this paper presents an efficient spatial index QR-tree, a hybrid index structure of Quadtree and R-tree, instead of the exhaustive search to improve the performance in response to user queries. QR-tree consists of two levels: the upper level is a Quadtree residing in the main memory which partitions the data space and the lower level is disk-resident R-trees assigned to the subspaces resulting from the partitioning process. Computational experiments show that the hybrid index structure is able to reduce query response time by up to 30% and achieve significant improvement on data update over the conventional indexing methods, thereby providing an effective option for efficient navigation services.