Comparison of four line-based positional assessment methods by means of synthetic data

Abstract

Positional accuracy of spatial data can be assessed by means of line-based methods. In this work we develop an analysis of the following four methods: Hausdorff Distance, Mean Distance, Single Buffer Overlay and Double Buffer Overlay, using a set of 12 synthetic cases. The synthetic cases incorporate specific shape features for bias, random errors and outliers which correspond to simplified versions of real world possibilities. The use of synthetic cases helps us to understand the basic behavioral differences between the methods. Numerical results for the positional accuracy estimations are different between methods and cases due to the different concepts of distance involved and the specific configurations of each case. When the method results in a function, patterns related to different types of errors can be detected in this function. The length-inclusion level of each method is revealed as the base criterion for comparison. The Single Buffer Overlay Method offers the more general solution because it includes the others' results.