Discrete global grid

[1] In a usual grid-modeling strategy, to simplify position calculations, each region is represented by a point, abstracting the grid as a set of region-points.

DGGs have been proposed for use in a wide range of geospatial applications, including vector and raster location representation, data fusion, and spatial databases.

So, the characterization of the reference model of the globe of a DGG can be summarized by: NOTE: when the DGG is covering a projection surface, in a context of data provenance, the metadata about reference-Geoid is also important — typically informing its ISO 19111's CRS value, with no confusion with the projection surface.

Examples of DGGs that use such recursive process, generating hierarchical grids, include: Cells may be hexagons, triangles, or quadrilaterals.

Main advantage, comparing with others of same indexing niche as S2, "is suitable for calculations involving spherical harmonics".

[17] There is a class of hierarchical DGG's named by the Open Geospatial Consortium (OGC) as "discrete global grid systems" (DGGS), that must to satisfy 18 requirements.

For a grid-based global spatial information framework to operate effectively as an analytical system it should be constructed using cells that represent the surface of the Earth uniformly.

In general, each cell of the DGG is identified by the coordinates of its region-point (illustrated as the centralPoint of a database representation).

Before it, the discretization of continuous coordinates for practical purposes, with paper maps, occurred only with low granularity.

Perhaps the most representative and main example of DGG of this pre-digital era was the 1940s military UTM DGGs, with finer granulated cell identification for geocoding purposes.

A global surface is not required for use on daily geographical maps, and the memory was very expensive before the 2000s, to put all planetary data into the same computer.

[26] [27] The spatial hierarchical grids were subject to more intensive studies in the 1980s,[28] when main structures, as Quadtree, were adapted in image indexing and databases.

In addition, averaged ratio between complementary profiles (AveRaComp) [29] gives a good evaluation of shape distortions for quadrilateral-shaped discrete global grid.

There are many ways to represent the value of a cell identifier (cell-ID) of a grid: structured or monolithic, binary or not, human-readable or not.

Supposing a map feature, like the Singapore's Merlion fountaine (~5m scale feature), represented by its minimum bounding cell or a center-point-cell, the cell ID will be: All these geocodes represents the same position in the globe, with similar precision, but differ in string-length, separators-use and alphabet (non-separator characters).

Successive space partitioning. The grey-and-green grid in the second and third maps are hierarchical.
Regular polyhedra (top) and their corresponding equal area DGG
Regular polyhedra (top) and their corresponding equal area DGG
In all DGG databases the grid is a composition of its cells. The region and centralPoint are illustrated as typical properties or subclasses. The cell identifier ( cell ID ) is also an important property, used as internal index and/or as public label of the cell (instead the point-coordinates) in geocoding applications. Sometimes, as in the MGRS grid, the coordinates make the role of ID.
Comparing grid-cell identifier schemas of two different curves, Morton and Hilbert. The Hilbert curve was adopted in DGGs like S2-geometry, Morton curve in DGGs like Geohash. The adoption of Hilbert curve was an evolution because have less "jumps", preserving nearest cells as neighbours.