PrintIt is fairly likely that the first analysis method you encountered in learning about GIS was overlay, where information from several different GIS layers is combined to enable complex queries to be performed. In this lesson, we will examine both the fundamentals of overlay, particularly the importance of registering layers to the same geographical coordinate system, and more elaborate versions of the method. As will become clear, overlay analysis can be generalized to almost any operation involving multiple map layers and is therefore very close to map algebra as discussed in the previous lesson.
The Multi-criteria decision analysis (MCDA) method (also known as surface overlay methods) are a set of methods that are used to combine different criteria. Criteria are ranked indicating their strength and importance of membership in a set. A number of different types of membership or overlay method can be used. These include:
- Boolean Overlay
Overlay data together to identify areas where values are suitable or not suitable. Data are transformed to represent areas that are suitable (1) or not suitable (0). - Weighted Overlay
Overlays several rasters using a common measurement scale and weights each according to its importance. This approach normalizes the output values. - Weighted Sum
Overlays several rasters and weights each according to its importance. This approach doesn't normalize the output values. - Fuzzy Overlay
Combine fuzzy membership data together, based on selected overlay type. The membership of the data are based on a fuzzification algorithm that transforms the input raster into a 0 to 1 scale (0 = no membership, 1 = full membership), indicating the strength of a membership in a set.