Efficient cell navigation methods and applications of an aperture 4 hexagonal discrete global grid system

Zhou, Jianbin; Ben, Jianwei; Huang, Xinhai; Wang, Rui; Liang, Xiaoyu; Ding, Junjie; Liang, Qishuang

doi:10.1080/13658816.2022.2125972

Cited by 8 publications

(2 citation statements)

References 13 publications

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“…Different cell typologies are depicted in Figure 2 including triangles, quadrilaterals, and hexagons that can be used to tessellate the spherical polyhedron. Hexagonal cells are preferred in many DGGS implementations and applications due to their properties and advantages over traditional square grid cells used in raster GIS (Zhou et al, 2022). Compared with other regular cell types, hexagons are the most compact and tessellate the sphere with the least error (Robertson et al, 2020).…”

Section: Theore Ti C Al Backg Round Of G Eode S I C G Lobal G Rid Sys...mentioning

confidence: 99%

Enabling geosimulations for global scale: Spherical geographic automata

Addae

Dragićević

2023

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Several complex dynamic spatial systems are operating on the global scale. Their representation with existing geosimulation models is limited to planar level and do not consider the curvature of the Earth's surface. Thus, the objective of this study is to propose and develop a spherical geographic automata (SGA) modeling approach to represent and simulate dynamic spatial processes at the global level. The proposed SGA model is implemented for three case studies including simulations of: (1) Game of Life as population dynamics; (2) urban land‐use growth; and (3) deforestation all operating on the spherical Earth's surface. Simulation results indicate that the proposed SGA modeling approach can represent spatial processes such as expansion and shrinkage dynamics on the Earth's surface. The proposed approach has the potential to be adopted to represent different complex systems such as ecological, epidemiological, socioeconomic, and Earth systems processes to support environmental management and policymaking at the global level.

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Section: Theore Ti C Al Backg Round Of G Eode S I C G Lobal G Rid Sys...mentioning

confidence: 99%

Enabling geosimulations for global scale: Spherical geographic automata

Addae

Dragićević

2023

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“…The value of the geographic grid model has been recognized by previous research due to its advantageous features such as uniformity, discretization, multiresolution, and cell indexing (Gibb et al., 2022; Goodchild, 2018; Li & Stefanakis, 2020; Peterson, 2016; Yao et al., 2020). The geographic grid model can be defined as a system for representing a geographic entity using a series of discrete, regular cells according to some predefined rules (OGC, 2017; Ulmer et al., 2020; Zhou et al., 2010, 2023). Commonly used geographic grid geometries are triangle, quadrilateral, and hexagon (Hojati et al., 2021; OGC, 2017).…”

Section: Introductionmentioning

confidence: 99%

QuadGridSIM: A quadrilateral grid‐based method for high‐performance and robust trajectory similarity analysis

Liu,

Li,

Qiao

et al. 2024

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Measuring trajectory similarity is a fundamental algorithm in trajectory data mining, playing a key role in trajectory clustering, pattern mining, and classification, for instance. However, existing trajectory similarity measures based on vector representation have challenges in achieving both fast and accurate similarity measurements. On one hand, most existing methods have a high computational complexity of O(n × m), resulting in low efficiency. On the other hand, many of them are sensitive to trajectory sampling rates and lack of accuracy. This article proposes QuadGridSIM, a quadrilateral grid‐based method for trajectory similarity analysis, which enables high‐performance trajectory similarity measure without the cost of low effectiveness. Specifically, we first realize the multiscale coding representation of trajectory data based on quadrilateral discrete grids. Then, a novel trajectory similarity measure is defined to reduce the computational complexity of O(n). Several effectiveness properties of QuadGridSIM are further optimized, including the spatial overlap, directionality, symmetry, and robustness to sampling rate variations. Experimental results based on real‐world and simulated taxi trajectory data indicate that QuadGridSIM outperforms most of the other tested algorithms developed previously in terms of effectiveness, particularly in its robustness regarding trajectory sampling rates. Furthermore, QuadGridSIM exhibits superior performance and is approximately one order of magnitude faster than previous methods in the literature. QuadGridSIM provides a solution to the low‐efficiency problem of massive trajectory similarity analysis and can be applied in many application scenarios, such as route recommendation and suspect detection.

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