Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping

Abstract. Snow depth has traditionally been estimated based on point measurements collected either manually or at automated weather stations. Point measurements, though, do not represent the high spatial variability in snow depths present alpine terrain. Photogrammetric mapping techniques have progressed recent years and are capable of accurately a spatially continuous manner, over larger areas various resolutions. However, strengths weaknesses associated with specific platforms photogrammetric as well accuracy performance surfaces yet sufficiently investigated. Therefore, industry-standard platforms, including high-resolution satellite (Pléiades), airplane (Ultracam Eagle M3), unmanned aerial system (eBee+ RTK SenseFly S.O.D.A. camera) terrestrial (single lens reflex camera, Canon EOS 750D) were tested for Dischma valley (Switzerland) spring 2018. Imagery was acquired airborne space-borne entire valley, while (UAS) imagery subset valley. For independent validation products, measured by probing using remote observations fixed poles. When comparing maps manual pole root mean square error (RMSE) values normalized median absolute deviation (NMAD) 0.52 0.47 m, respectively, map, 0.17 m 0.16 0.11 UAS map. The area covered map only intersected four did generate statistically relevant measurements. reference surface, RMSE NMAD 0.44 0.38 0.12 0.21 0.19 compared to dataset large part (40 km2), from yielded an value 0.92 0.65 m. This study provides comparative between evaluate their advantages disadvantages operational, terrain both small geographic areas.