UAV photogrammetry combined with post-processed kinematic positioning (PPK) is a widely used solution for obtaining high-resolution topographic models. However, the absolute vertical accuracy of photogrammetric models based solely on PPK, in the absence of ground control points (GCPs), remains poorly understood, particularly in complex mountainous terrain. This study investigates the magnitude and consistency of the systematic vertical bias in UAV-PPK photogrammetry by comparing two processing scenarios applied to the same dataset: (i) with GCPs and (ii) without GCPs. The analysis was conducted on three representative surface types — paved road, grassland and forest — using independent GNSS ground control points. The results show that the GCP-based solution achieves high vertical accuracy, with RMSE values ranging from 0.022 m to 0.069 m. In contrast, processing without GCPs reveals a negative systematic vertical bias of approximately −2.0 m, which is consistent across all surface types, with low internal dispersion (±0.02–0.03 m). This behavior indicates that the error is predominantly systematic and manifests as a uniform vertical shift affecting the entire model. The observed bias exhibits similar values regardless of surface type and elevation variation, suggesting that the error is not driven by local terrain characteristics but is related to the absolute positioning of the photogrammetric model. The results highlight the crucial role of external constraints in the bundle adjustment process (the process of adjusting the photogrammetric image block) and underscore the importance of vertical reference consistency in PPK-based georeferencing. From an application perspective, the study shows that the exclusive use of PPK georeferencing, in the absence of GCPs or vertical reference verification, can lead to significant errors in absolute altitudes. The introduction of even a minimal number of GCPs enables the effective elimination of this systematic offset and ensures reliable vertical accuracy.

UAV photogrammetry, PPK, ground control points, systematic vertical bias, altimetric accuracy, georeferencing, bundle adjustment, vertical reference.

geodesy engineering

Presentation: poster