Special Issue “Global Grid Systems”

Samavati, Faramarz; Alderson, Troy

doi:10.3390/ijgi9060376

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…DGGs have been widely used in large-scale spatial data management, decision making, and simulation analysis. For example, they have been used in the spatial data organization, indexing, analysis, and visualization [6][7][8][9]; global environmental and soil monitoring models [10,11]; atmospheric numerical simulations and visualizations [12]; ocean numerical simulations and visualizations [13]; place names management or gazetteers [14]; big Earth data observations [12,15]; modeling of offset regions around the locations of Internet of Things (IoT) devices [16]; cartographic generalization and pattern recognition for choropleth map-making [17]; the Unmanned Aerial Vehicle (UAV) data integration and sharing [18]; the Modifiable Areal Unit Problem (MAUP) [19]; especially in digital Earth [5,16,[20][21][22], and so on.…”

Section: Introductionmentioning

confidence: 99%

Correlation Analysis and Reconstruction of the Geometric Evaluation Indicator System of the Discrete Global Grid

Wang

Zhao

Sun

et al. 2021

IJGI

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Although a Discrete Global Grid (DGG) is uniform in its initial subdivision, its geometric deformation increases with the level of subdivisions. The Goodchild Criteria are often used to evaluate the quality of DGGs. However, some indicators in these criteria are mutually incompatible and overlap. If the criteria are used directly, the evaluation of the DGGs is inaccurate or unreliable. In this paper, we calculated and analyzed the correlation between the evaluation indicators of the DGG and reconstructed a quality evaluation system of DGGs with independent indicators. Firstly, we classified the Goodchild Criteria into quantitative and qualitative indicators. Then, we calculated the correlation among the quantitative indicators and extracted the independent evaluation factors and related weights of the observed values by factor analysis. After eliminating or merging the incompatible and overlapping quantitative indicators and performing a logical reasoning of the qualitative indicators, we reconstructed a comprehensive evaluation system with independent indicators. Finally, taking the Quaternary Triangular Mesh (QTM) model as an example, we verified the independence of the indicators and the feasibility of the evaluation system. The new indicator system ensures the reliability of the evaluation of DGGs in many fields.

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