A grid is a pattern of geometrical shapes used to segment a surface or region and which can be defined using a simple mathematical function or formula. Dividing a space in grids helps in better understanding of the space and location of objects. The grids are of great use in translating the spatial information stored in the maps. The shape, size and the type of grid varies depending on the need of the study and the data to be plotted. Most common shapes used are square and triangle. Hexagons are rapidly emerging as the most efficient shape. The selection of the most suitable grid depends on two major criteria; the reality check and the ease of use. Hexagon is the highest order polygon which is capable of covering an area completely by itself. Hexagonal grids are not frequently used due to the referencing problem. Hexagon maintains linearity and directionality. This paper focuses on the selection criteria of the most suitable grid and the efficiency comparison of the squares and hexagons. The results prove that the hexagonal grids are more efficient and accurate.

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Grids Hexagon Linear Distance Angularity Spatial Coverage