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 weighted 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).