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ANNEXURE 1

QUALITY CONTROL METHODS

Complete, accurate and current spatial and attribute data are essential for conducting accessibility
studies as they impact on the reliability of the results. You should quality control all your spatial
data sets before undertaking such a study.

The quality control exercise should follow standardised approaches that are internationally
accepted and it needs to include aspects such as completeness, validity, logical consistency,
physical consistency, referential integrity and positional accuracy. A detailed description of the
methods that can be used is provided in this Annexure.

A COMPLETENESS OF DATA

The completeness of a dataset means that all the spatial features and their associated attributes
that are required for the study area are included. A spatial feature is an area, line or point on a
map that has its own set of geographic coordinates. Attributes are records in a database that are
linked to the spatial feature (e.g. number of classrooms at a primary school).

Target population

To do a completeness check, the boundary of the study area can be overlaid on the spatial
information of the target population. Thematic maps of variables in the target population data
can be produced to see if there are gaps in the spatial information or attributes associated with
the spatial features. Figure 1 shows a thematic map of the total population and where there are
missing spatial features and attributes associated with the spatial features.

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