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The design of spatial data types and structures should be based on an understanding of the properties of spatial
data in order to accommodate the design process as close as possible to the nature of spatial phenomena in the
physical world. Most data manipulated by GIS are spatial data. Spatial data[8] consist of spatial objects made up of
points, lines, surfaces, solids, and even data of higher dimension which include time. Examples of spatial data
include cities, rivers, roads, counties, states, crop coverage, mountain ranges, etc. Often it is also desirable to attach
non-spatial attribute information[9]. Examples of spatial properties include the extent of a given river, or the
boundary of a given county, elevation heights, city names, etc. Spatial databases facilitate the storage and efficient
processing of spatial and non-spatial information ideally without favoring one over the other. Such databases are
found increasingly usage in environ