Lattice QuadTree Indexing Algorithm for a Hexagonal Discrete Global Grid System Hexagonal discrete global grid systems are the preferred data models supporting multisource geospatial information fusion. Related research has aroused widespread concern in the academic community, and hierarchical indexing algorithms are one of the main research focuses. In this paper, we propose an algorithm for indexing the cell of a ringed spatial area based on a hexagonal lattice quadtree (HLQT) structure and the indexing characteristics. First, we design a singleresolution indexing algorithm in which indexing starts from the initial quad tree and expands ring by ring using coding operations, and a quadtree structure is applied to accelerate this process. Second, the hierarchical indexing algorithm is implemented based on singleresolution indexing, and a pyramid hierarchical model is established. Finally, we perform comparison experiments with existing algorithms. The results of the experiments indicate that the singlelevel indexing efficiency of the proposed algorithm is approximately twice that of the traditional method and that the hierarchical indexing efficiency is approximately 67 times that of the traditional method. These findings verify the feasibility and superiority of the algorithm proposed in this paper.

Covering a Set of Points with k Bounding Boxes Covering a set of points with  k  orthogonal bounding boxes is useful for implementing spatiotemporal index structures that are built from a given dataset. In this work we deal with the problem of covering a set of points with kparallel axis boxes, under the restriction that the total area enclosed by the boxes must be minimized. To achieve this, we present a novel algorithm that, using dynamic programming techniques, finds the optimal solution for covering a set of points with kbounding boxes where the total sum of the areas of the boxes is minimum. This is compared with the process of generating kbounding boxes every  l  units of distance, achieving an improvement of about 50% of unuseful area covered.