Positional accuracy

HOME ENV510 Landscape Ecology and GIS

Positional accuracy

Components
Types

Positional accuracy has been described as 'the expected deviance in the geographic location of an object in the data set from its true ground position' (Aranoff, 1989), or 'the likelihood that the position of a point as determined from a map will be the true position' (Aranoff, 1989).

Positional accuracy is tested by selecting specified sample points and comparing their position coordinates with a more accurate source.

Components

There are two main components of positional accuracy

Bias refers to systematic discrepancies between the represented and the true position. Ideally this should be zero. This is measured by the mean or average positional error of the sample points.
Precision relates to dispersion of the positional errors of the data elements. It is estimated by calculating standard deviation of the selected test points. A low standard deviation indicates a narrow dispersion of positional errors ie relatively small error. The higher the precision, the greater the confidence in the data set.

Types

There are two main types of error in positional accuracy

Root mean square (RMS) error is a common measure of positional accuracy used in surveying and photogrammetry. This is calculated by determining the positional error of the test points, squaring the individual deviations and taking the square root of their sum. One limitation of this measure is that it does not distinguish between bias and precision.
Entity error, or positional accuracy, can arise from incorrectly placed entities but also missing entities and disordered entities. This is mainly a problem in vector systems.
TOP

Report page problems to lrp@cdu.edu.au