Geography Reference
In-Depth Information
4
Key concepts 3
Spatial data analysis
Introduction
4.1
In the previous chapter, a key focus was on introducing some methods for aspatial
data analysis. h is chapter builds on that previous discussion and discusses some ways
of extracting information from spatially referenced (mappable) data. h e chapter
details how basic measurements, including lengths, perimeters, and areas, are made
in a GIS. Following this, the generation of buf ers (distance bands around specii ed
objects) is detailed. Approaches for use with both vector and raster representations
of features are considered. Next, the idea of moving windows—whereby some opera-
tion (such as computing the mean average) is conducted using local subsets of the
data—is introduced. h e subject of geographical weights, another core component
of many methods detailed in the topic, is outlined next. With such approaches, the
tendency for nearby values to be more similar than those that are more distant is taken
into account. A section on spatial dependence and spatial autocorrelation discusses
spatial patterns and some ways of analysing such patterns. h e basis of spatial depen-
dence is that values close together in space tend to be more similar than those that
are farther apart. h is principle has been referred to as the 'i rst law of geography' (the
concept is outlined by Tobler, 1970) and this concept is central to many methods
for the analysis of spatial data. h e need to consider spatial scale and the form of
zones (where used) in any analysis is discussed in the following section. A small
section on merging polygons then follows. Finally, the key themes are revisited and
summarized.
In short, the objective of the chapter is to introduce the basic components of some
key tools for the analysis of spatial data. Once these ideas (and those presented in the
previous two chapters) are grasped, all of the background necessary to understand
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