Detecting Geo-Positional Bias in Imagery Collected Using Small UASs

Abstract

Statistical methods for detecting bias in global positioning system (<small>GPS</small>) error are presented and applied to imagery collected using three common unmanned aerial systems (<small>UASs</small>). Imagery processed without ground control points (<small>GCPs</small>) had horizontal errors of 1.0–2.5 m; however, the errors had unequal variances, significant directional bias, and did not conform to the expected statistical distribution and so should be considered unreliable. When <small>GCPs</small>were used, horizontal errors decreased to less than 5 cm, and the errors had equal variances, directional uniformity, and they conformed to the expected distribution. The analysis identified a longitudinal bias in some of the reference data, which were subsequently excluded from the analysis. Had these data been retained, the estimates of positional accuracy would have been unreliable and inaccurate. These results strongly suggest that examining <small>GPS</small> data for bias should be a much more common practice.