Points are zero-dimensional objects that contain only a single coordinate pair. Three fundamental vector types exist in geographic information systems (GIS): points, lines, and polygons. The spatial information and the attribute information for these models are linked via a simple identification number that is given to each feature on a map. The data attributes of these features are then stored in a separate database management system. Vector data models use points and their associated X, Y coordinate pairs to represent the vertices of spatial features, much as if they were being drawn on a map by hand. In this model, space is not quantized into discrete grid cells like the raster model. Find out more about these in our ebook Spatial Indexes 101.In contrast to the raster data model is the vector data model. So many organizations are now taking advantage of Spatial Indexes to enable performant analysis of truly big spatial data. Spatial Indexes are "geolocated" through a reference string, not a long geometry description (like vector data). They can be used for both vector-based analysis (like running intersections and spatial joins) and raster-based analysis (like slope or hotspot analysis).īut where they really excel is in their size, and subsequent processing and analysis speeds. However, they render a lot like vector data each "cell" in the grid is an individual feature which can be interrogated. Spatial Indexes are global grids - in that sense, they are a lot like raster data. Note: This section of the blog has been updated in January 2023. There is even a new generation of data which features some of the best characteristics of both data types. Many will make impassioned arguments extolling the virtues of one or the other but thankfully since raster can be converted to vector and vice versa there is no need to choose one exclusively.
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