Geography Reference
In-Depth Information
a completely suitable area on the ground. A totally black area would indicate a total lack of suitability.
Other levels of suitability could be indicated by lighter or darker (grayscale) areas. For example, suppose
that you were searching for a site for an airport. On one sheet, expensive land would be created as darker,
less expensive as lighter. On another sheet, areas where structures would have to be demolished might be
made black. A third sheet would show a very flat area as clear. Assuming that all these maps were made
the same size, shape, scale, projection, and so on (quite a chore in itself), you could then line them up
and place them on a light table, making sure that equivalent geographic areas properly registered (lined
up) with one another, and look through them to perceive the resulting image. Using this “map overlay”
technique,
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the lighter a resulting area, the more suitable that area would be. You can probably think of
several reasons why this method is pretty inexact (relative importance of different factors, for one—are
weather patterns as important as topography?), but the overlay method was one way used to analyze
spatial data sets that come from several map sources.
How the Computer Aids Analyzing Spatial Data
Computers can aid in spatial data analysis and synthesis in a variety of ways. First off is speed. It helps
that computers can add and compare numbers billions of times faster than you can. (Computers, while
stupid, are fast and accurate. Humans are smart, but slow and sloppy.) Further, a computer is capable of
doing repetitive tasks (read: boring) for hours or years on end. You probably would not want to know a
person with this capability. A third virtue of computers in GIS is the ability to store very large datasets.
A vital factor in using a computer to analyze spatial data is the paradigm or schema (data model, data
structure) that is used to store the data in the memory of the machine. While the issues about the format
in which to store data are not unique to GIS, lots of other fields have much less of a problem. Usually
when one stores data in a computer, the questions that arise are ones like the following:
Should I use integers or numbers with decimal points?
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Is the number likely to be very big or very small?
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Would it cause problems if I used a text string to store a numeric value?
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Such sets of numbers usually exist in simple lists, databases, or perhaps in matrices.
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
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Is a mixture of continuous and discrete phenomena
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Needs to be considered at different levels of detail
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A method given prominence by Ian McHarg in his 1969 book
Designs with Nature
.
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