GNSS campaign planning enables the selection of periods with favourable satellite geometry, which directly affects positioning accuracy. Most available GNSS planning tools allow analyses only for a single point and do not account for variability in satellite visibility conditions along linear features surveyed under kinematic conditions. The aim of this study was to quantitatively validate a GNSS campaign planning model designed for analyses conducted along a survey trajectory based on DTM and DSM.The validation was carried out using a mobile measurement campaign conducted in the Tri-City metropolitan area in northern Poland. Measurements were performed along an 18.4 km route using GPS observations acquired in a mobile survey campaign, enabling the assessment of the impact of terrain obstacle modelling on satellite constellation geometry. Predicted PDOP values and the number of visible satellites were compared with those obtained from measurements.In the model variant based on DTM and full DSM, the mean PDOP value was 2.45 and the mean number of visible satellites was 7.16, whereas the measurements yielded 1.80 and 9.76, respectively. This indicates that the model underestimated the number of available satellites by approximately 2–3, resulting in an overestimation of PDOP values. The analysis indicated that treating non-building obstacles, particularly vegetation, as fully obstructing GNSS signals was a major contributor to these discrepancies.After modifying the model to include only buildings in the DSM, the mean PDOP decreased to 2.08 and the mean number of visible satellites increased to 8.10, resulting in substantially improved agreement between model predictions and measurement results. Residual-based validation showed that the MAE decreased from 0.660 to 0.294 (55%) and the RMSE from 1.075 to 0.597 (44%), and the matching success rate increased from 93.0% to 98.9%. The results indicate that, under the investigated conditions, the proposed GNSS campaign planning model is capable of reproducing the general characteristics of satellite visibility and constellation geometry along a survey trajectory. They also indicate that vegetation representation is one of the major sources of discrepancies in satellite visibility modelling.
