![]() Ease of resampling to different spatial scales: increasing the spatial resolution of a square grid is just a matter of dividing each grid cell into four.This makes data storage and retrieval easier since the coordinates of the vertices of each grid cell are not explicitly stored. The attribute data can be stored as an aspatial matrix, and the geographical location of any cell can be derived given that cell’s position relative to the origin. Simplicity of definition and data storage: the only explicitly geographical information required to define a raster grid are the coordinates of the origin (e.g. bottom left corner), the cell size, and grid dimensions (i.e. number of cells in each direction).The most notable benefits of this format compared to hexagonal grids are: Raster datasets are the most ubiquitous type of square grid used in GIS. The following images from Wikipedia 1, 2, 3 demonstrate these tessellations: ![]() A forth option is a diamond pattern arising from merging pairs of equilateral triangles however diamonds are not regular polygons. Tessellation is well studied mathematically and there are just three possible regular tesselations: equilateral triangles, squares, and regular hexagons. In fact, any regular tesselation of the plane (i.e. the tiling of a plane with contiguous regular polygons of the same type), can act as a spatial grid. In ecology and conservation applications, variables may include number of individuals of a threatened species per grid cell, elevation, mean annual rainfall, or land use.įrom my experience, using square cells is by far the most common method for defining grids however, other options are possible. ![]() ![]() In the latter scenario, the most common approach is to use a raster format, in which a grid of uniform square cells is overlayed on a study area and each cell is assigned a value for the spatial variables of interest. For example, we may want to overlay a study area with a grid of points as part of some regular spatial sampling scheme, divide a large region into smaller units for indexing purposes as with UTM grid zones, or slice the study area into subunits over which we summarize a spatial variable. In spatial analysis, we often define grids of points or polygons to sample, index, or partition a study area. ![]()
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