Shifting the Metric from Overlap to Information Density – Improved UAV Photogrammetry Strategies for High-Alpine Snow Depth Mapping

Abstract:
Knowledge of spatio-temporal snow storage is crucial to understand snow-hydrological dynamics in complex, high alpine environments. Due to the low cost and fast deployability, photogrammetry in combination with commercial aerial photography UAVs has become a viable method for capturing high-resolution snowpack information. We utilize this technique in a high alpine catchment at Mt. Zugspitze in Germany to capture digital snow surface models and consequently snow depth information in heterogeneous environments. The fundamental step is the acquisition of overlapping aerial images, which are used for the reconstruction of the surface in the photogrammetric processing. It is well known that the properties of the image dataset determine the quality of the resulting reconstruction. Therefore, a number of studies from different areas of research focus on this topic. For snow depth mapping, Bühler et al. 2016 recommend, for instance a single overlap value, while Lee et al. 2021 collected different overlap values. Wu et al. 2025 found that the 3D model quality in an urban environment is linked to the overlap of an oblique image dataset in a nonlinear way. Depending on the studied terrain and structures, Maes 2025 summarizes various recommendations for appropriate overlap settings. To provide an insight into how often, in what resolution, and from which angle an area is captured, the current concept of overlap is unsuited. We suggest a paradigm change towards metrics representing the image information of a surface. Our approach is to increase the image capture frequency while angling the camera in a forward direction, wherefore a high image capture frequency of current digital camera systems is fundamental. Through this combination, the near-nadir information is retained, and the changed viewing geometry provides additional information in the along path and side view directions. The potential can be used for an increase in the dataset quality or a decrease in capture time. Both are highly relevant when working in the structurally complex and remote regions of high mountain areas. Battery capacity and regulations for flight speed and height do limit other options for an increase in data capture. Our goal is to share preliminary results for increasing the information in the image dataset while staying within the capability of current hardware.

Literature:

Bühler, Y., Adams, M.S., Bösch, R., Stoffel, A., 2016. Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations. The Cryosphere 10, 1075–1088. https://doi.org/10.5194/tc-10-1075-2016

Lee, S., Park, J., Choi, E., Kim, D., 2021. Factors Influencing the Accuracy of Shallow Snow Depth Measured Using UAV-Based Photogrammetry. Remote Sensing 13, 828. https://doi.org/10.3390/rs13040828

Maes, W.H., 2025. Practical Guidelines for Performing UAV Mapping Flights with Snapshot Sensors. Remote Sensing 17, 606. https://doi.org/10.3390/rs17040606

Wu, S., Feng, L., Zhang, X., Yin, C., Quan, L., Tian, B., 2025. Optimizing overlap percentage for enhanced accuracy and efficiency in oblique photogrammetry building 3D modeling. Construction and Building Materials 489, 142382. https://doi.org/10.1016/j.conbuildmat.2025.142382