Introducing Geographic Information Systems with ArcGIS: A Workbook Approach to Learning GIS, 3rd Edition
by Michael D. Kennedy
Complexity of Spatial Data
With spatial data the problem is much more complex than with numbers or text. The natural and human-made environment we want to work with
- Is virtually infinite in detail
- Is a mixture of continuous and discrete phenomena
- Needs to be considered at different levels of detail
A computer, on the other hand, is finite (small, really) and discrete to a fault (made up, at its most fundamental level, of things, i.e., bits, that either are or aren’t, i.e., 1s or 0s—there is no middle ground).
So the question is this: How can we extract significance from the complex, virtually infinite, multidimensional natural and human-made environment and, using only numbers, letters, and patterns of bits, make the computer form a “map” that can be easily analyzed and compared with features that make up the environment we are interested in. Put another way, we need to find a way of structuring the geographic data in the computer’s memory so that we can derive answers to queries we might make.
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