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Lesson Navigation IconSuitability analyis

Unit Navigation IconDecision support with GIS

Unit Navigation IconBoolean Overlay

Unit Navigation IconWeighted overlay

LO Navigation IconWhat is a weighted overlay?

LO Navigation IconWeighted linear summation

LO Navigation IconWeaknesses, problems, and evaluation

LO Navigation IconSelf Assessment

Unit Navigation IconDetermining weights

Unit Navigation IconSummary

Unit Navigation IconRecommended Reading

Unit Navigation IconGlossary

Unit Navigation IconBibliography

Unit Navigation IconMetadata


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Weighted overlay

Boolean overlay of binary thematic layers offers a simple and quick approach to a suitability analysis with GIS. However, for many applications the division of reality into two categories ("true" and "false") is an inadequate representation of reality.
First, with Boolean analysis all influencing factors are of equal importance, by definition. However, most often criteria are not equally influencing the decision. When someone buys a new car, its color and brand might have a heavier weight than its fuel consumption or susceptibility to breakdowns. This principle of assigning weights to influencing factors is used for suitability analysis in GIS as well. This approach is called termweighted overlay and is discussed in this unit.
Natural phenomena are not defined by sharp boundaries and can seldom be squeezed into binary categories. To be able to create a realistic model of potential wolf habitats, the binary classification into "forest" and "not forest" is not enough. A more precise breakdown of vegetation cover needs to be considered. Binary categories are not fit to measure the influence of spatial variables such as annual precipitation or decreasing values regarding distance to the road. Interval or ratio data (percent forest cover) should be used instead of categorical data (forest / no forest).

Learning Objectives

  • You are able to describe the key advantages of weighted overlay compared to Boolean overlay;
  • You know the principle of standardization and can apply it to simple examples;
  • You can create your own examples of which to use weighted overlay in GIS;
  • You can assess when to use weighted overlay for a suitability analysis.
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