A comparison of intercell metrics on discrete global grid systems

Abstract A discrete global grid system (DGGS) is a spatial data model that aids in global research by serving as a framework for environmental modeling, monitoring and sampling across the earth at multiple spatial scales. Topological and geometric criteria have been proposed to evaluate and compare DGGSs; two of which, intercell distance and the “cell wall midpoint” criterion, form the basis of this study. We propose evaluation metrics for these two criteria and present numerical results from these measures for several DGGSs. We also consider the impact of different design choices on these metrics, such as predominant tessellating shape, base modeling solid and partition density between recursive subdivisions. For the intercell distance metric, the Fuller–Gray DGGS performs best, while the Equal Angle DGGS performs substantially worse. For the cell wall midpoint metric, however, the Equal Angle DGGS has the lowest overall distortion with the Snyder and Fuller–Gray DGGSs also performing relatively well. Aggregation of triangles into hexagons has little impact on intercell distance measurements, although dual hexagon aggregation results in markedly different statistics and spatial patterns for the cell wall midpoint property. In all cases, partitions on the icosahedron outperform similar partitions on the octahedron. Partition density accounts for little variation.

[1]  K. Sahr,et al.  Comparing Geometrical Properties of Global Grids , 1999 .

[2]  E. Saff,et al.  Distributing many points on a sphere , 1997 .

[3]  J. Snyder An Equal-Area Map Projection For Polyhedral Globes , 1992 .

[4]  Lloyd A. Treinish,et al.  Sphere quadtrees: a new data structure to support the visualization of spherically distributed data , 1990, Other Conferences.

[5]  Michael F. Goodchild,et al.  A hierarchical spatial data structure for global geographic information systems , 1992, CVGIP Graph. Model. Image Process..

[6]  K. Sahr,et al.  Geodesic Discrete Global Grid Systems , 2003 .

[7]  R. Heikes,et al.  Numerical Integration of the Shallow-Water Equations on a Twisted Icosahedral Grid , 1995 .

[8]  Ulf Dieckmann,et al.  The Geometry of Ecological Interactions: Simplifying Spatial Complexity , 2000 .

[9]  Lian Song,et al.  Comparing Area and Shape Distortion on Polyhedral-Based Recursive Partitions of the Sphere , 1998, Int. J. Geogr. Inf. Sci..

[10]  Robert W. Gray,et al.  Exact Transformation Equations for Fuller's World Map , 1995 .

[11]  Peter van Oosterom,et al.  Advances in Spatial Data Handling , 2002, Springer Berlin Heidelberg.

[12]  Minus van Baalen,et al.  The Geometry of Ecological Interactions: Pair Approximations for Different Spatial Geometries , 2000 .

[13]  B. G. Murray,et al.  Dispersal in Vertebrates , 1967 .

[14]  Denis White,et al.  Cartographic and Geometric Components of a Global Sampling Design for Environmental Monitoring , 1992 .

[15]  David A. Randall,et al.  Numerical Integration of the Shallow-Water Equations on a Twisted Icosahedral Grid. Part II. A Detailed Description of the Grid and an Analysis of Numerical Accuracy , 1995 .

[16]  Geoffrey Dutton Part 4: Mathematical, Algorithmic and Data Structure Issues: Geodesic Modelling Of Planetary Relief , 1984 .

[17]  Will Steffen,et al.  Global change and terrestrial ecosystems , 1996 .