Mapping of geo-location influence on the uncertainty level of GNSS observations

The random errors of differential Global Navigation Satellite Systems (GNSS) are statistically identifiable by an uncertainty component for each coordinate axis at each observed station. Literature reflects a noticeable correlation between stations’ geo-location and the uncertainty components. In this study, the multi-temporal correlation between uncertainty components in easting and northing was confirmed with moderate correlation coefficients of R 2 =0.68 and 0.59 respectively. However, a low R 2 of 0.38 was obtained for the elevation component. Quantified uncertainties were mapped using first-order polynomial, quadratic polynomial, and kriging. The first-order polynomial revealed a slightly higher residual level than the quadratic polynomial. However, they both performed correspondingly for the validation points, whereas Kriging showed a clear case of an over-fitting. Therefore, the first-order polynomial was considered as a suitable scheme. Geo-statistical analysis of Easting and Northing components showed that the uncertainty is not uniform over the study area. It also showed that although the uncertainty is not purely continuous, it has a significant continuity. A geo-location based uncertainty map layers were produced based on the geo-statistical analysis result. The map concluded two layers represent the resultant, and the resultant orientation. Results represent an example of the possibilities to produce meaningful maps of uncertainties.