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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