Photogrammetric reconstruction of homogenous snow surfaces in alpine terrain applying near-infrared UAS imagery

Abstract

Operating unmanned aerial systems (UAS) to record imagery of alpine snow cover for photogrammetric applications is challenging due to topographic and meteorological conditions. Furthermore, the homogenous snow surface encumbers the automated detection of matching points, which are required for generating accurate digital surface models (DSMs). On the other hand, there is rising demand for high spatial resolution snow depth and snow surface-type mapping as well as snow avalanche documentation. UAS have the potential to enable flexible, timely, and cost-efficient data acquisition, even in poorly accessible alpine terrain. This could be a major step forward for many applications in snow hydrology, avalanche research, mitigation measure planning, hazard zonation, and alpine ecology investigations.In this study, we investigate the applicability and performance of UAS-based structure-from-motion (SfM) photogrammetry on very homogenous snow surfaces, under suboptimal illumination conditions, at two alpine test sites in Tschuggen (2000 m a.s.l.) close to Davos, Switzerland, and Lizum (2000 m a.s.l.) near Innsbruck, Austria. We discuss the topographic and meteorological challenges for flying UAS missions in high-alpine terrain. Additionally, we compare DSMs calculated from the imagery acquired in the visual (VIS, λ = 400–700 nm) and near-infrared (NIR, λ = 700–830 nm) parts of the electromagnetic spectrum. We evaluate the resulting DSMs qualitatively and quantitatively by applying: a) differential Global Navigation Satellite System (GNSS) measurements at the Swiss test site, with an expected accuracy better than 0.1 m within x, y, and z directions; b) terrestrial laser scanning (TLS) at the Austrian test site, with an expected accuracy of ± 0.025 m (1σ), along with a distance-dependent error. The results of this study reveal the potential and limitations of UAS-based SfM photogrammetry for applications on snow-covered, alpine terrain in general and in particular the benefit of NIR imagery on the accuracy and precision of the results.