Key concepts 1 GIS - Spatial Data Analysis: An Introduction for GIS Users - page 21

Value Value

1-3 4-5 6-7 1-2 3-4 5-7

Figure 2.8 Alternative categorizations for vector polygon data.

in the topic edited by Wilson and Fotheringham (2008). A good summary account of
methods for visualizing spatial data (geovisualization) is given by Longley et al. (2005a).
h e data values may be visualized in other indirect ways, an example being the use of
plots or graphs to summarize data values. h is topic is amongst those explored in the
following chapter.

Querying data

2.11

At its simplest level, the analysis of spatial data could involve selecting and mapping
areas or features that have particular properties. For the example of measurement of
some pollutant at point locations, all points with a pollution level above some critical
threshold could be highlighted. In a standard database system a querying language
(such as structured query language) is likely to be used to select entries in the tables
that make up the database. Likewise, in a GIS such a query language can be used
to select a subset of the data set. Such queries take logical forms such as Nitrogen-
DioxidePPB > 21, selecting all locations where the nitrogen dioxide amount measured
is greater than 21 parts per billion. h e concept of Boolean logic and its application for
querying spatial data is outlined next.

2.11.1 Boolean logic

Selection or combination of spatial features is ot en conducted using logical (or Boolean)
operators (like the nitrogen dioxide example above). For example, population zones in