Combining data layers - Spatial Data Analysis: An Introduction for GIS Users - page 74

Dif erent methods for prediction of precipitation amounts will result in potentially
very dif erent outputs (see Chapter 9). Figure 5.10 includes some very small polygons
that may not have existed if a dif erent interpolation procedure was used (or the inputs
had varied in some other way) and, in such cases, removal of these small polygons
might be considered.
Summary
One of the most widely exploited benefi ts of GIS is their capacity to combine multiple
data layers in fl exible ways. Such functionality allows complex multiple criteria to be
taken into account simultaneously in a way that was practically impossible before the
advent of computer-based systems for spatial data analysis. This chapter has provided
an overview of some key ways of identifying overlaps between features in different data
layers and for combining data layers. In addition, the identifi cation of areas which fulfi l
multiple criteria was discussed.
Further reading
Overlay operators are described in standard GIS textbooks such as those by Burrough
and McDonnell (1998) , Heywood et al . (2006), Chang (2008) , and Longley et al . (2005a) .
Chou (1997) , Lee and Wong (2000) , and O'Sullivan and Unwin (2002) describe the princi-
ples in more detail. Wise (2002) details some key algorithms for overlay. A key reference
for GIS-based multicriteria decision analysis is the topic by Malczewski (1999) .
The next chapter is concerned with network analysis and introduces tools to address
questions like 'What is the shortest route between two places on a road network?'.