Abstract

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 quad-tree (HLQT) structure and the indexing characteristics. First, we design a single-resolution indexing algorithm in which indexing starts from the initial quad tree and expands ring by ring using coding operations, and a quad-tree structure is applied to accelerate this process. Second, the hierarchical indexing algorithm is implemented based on single-resolution indexing, and a pyramid hierarchical model is established. Finally, we perform comparison experiments with existing algorithms. The results of the experiments indicate that the single-level 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.

Highlights

  • In recent years, the application of geospatial data has become increasingly extensive

  • Mahdavi-Amiri et al designed a hierarchical indexing and visualization scheme for a variety of hexagonal grids based on a special coordinate system on a diamond surface [29]

  • It has been demonstrated [31] that the efficiency of the code addition operations of hexagonal lattice quad-tree (HLQT) is higher than those of hexagonal quaternary balanced structure (HQBS) and PYXIS

Read more

Summary

Introduction

The application of geospatial data has become increasingly extensive. The planar quadrilateral grid system has a direct connection with the quad-tree data structure, and the quadrature-based indexing algorithm is directly applicable [5].

Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call