A generic encoding and operation scheme for mixed aperture three and four hexagonal discrete global grid systems

ABSTRACT

Discrete Global Grid Systems (DGGSs) are an emerging data model for integration and analysis of big Earth data. Current research on hexagonal DGGSs focuses mainly on the pure aperture, which limits application of resolution and may cause data redundancy. The mixed aperture hexagonal DGGS provides a new and flexible scheme that can optimize data precision by designing the most suitable grid resolution. This paper proposes a generic encoding and operation scheme for the mixed aperture 3 and 4 hexagonal DGGSs. A planar mathematical model with unique location representation was constructed. Based on this model, this paper designed an encoding scheme and gave relevant operational properties and rules. A generic method of extending the planar scheme to the surface of an icosahedron was then designed and spherical grids were obtained by projection. The conversion between geographical coordinates and codes was also provided. The proposed scheme has a more complete theoretical basis than existing schemes and can be applicable to different aperture sequences. Experiments show that the code addition efficiency of the proposed algorithm is superior to existing hexagonal grid systems. A case study with ocean salinity hexagonal data demonstrated the flexibility of the proposed scheme.

KEYWORDS:

• Mixed aperture
• discrete global grid system
• hexagon
• encoding
• icosahedron

Acknowledgments

The author would like to thank the associate editor and anonymous reviewers for their careful reading and constructive suggestions, which provide an important guidance for our paper writing and research work. The authors would also like to thank Sahr for their previous studies and the software DGGRID, which helped us very much. This work was supported by the National Natural Science of Foundation of China (Grant No. 41671410).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [41671410].

Notes on contributors

R. Wang

R. Wang, is currently working toward the Ph.D degree in Surveying and Mapping at PLA Strategic Support Force Information Engineering University, Zhengzhou, where she received the B.S. degree and the M.S. degree. Her current research interest includes spatial data modelling.

J. Ben

J. Ben, is a professor in remote sensing at PLA Strategic Support Force Information Engineering University, Zhengzhou, where he received the Ph.D degree in 2005. He conducts research in Photogrammetry and Remote Sensing, spatial data modelling.

J.B. Zhou

J.B. Zhou, is currently working toward the M.S degree in surveying and mapping at PLA Strategic Support Force Information Engineering University, Zhengzhou, where he received the B.S. degree. HIS current research interest includes spatial data modelling.

M. Y. Zheng

M. Y. Zheng is currently working toward the M.S degree in surveying and mapping at PLA Strategic Support Force Information Engineering University, Zhengzhou. She received the B.S. degree in the Survey and Mapping field from North China University of Water Resources and Electric Power, Zhengzhou. Her current research interest includes spatial data modelling.