Abstract
Time-lapse photogrammetry in conjunction with high-resolution digital elevation models is used to quantify the surficial velocity field and the ablation of the Pasterze, a rapidly retreating alpine valley glacier in Austria. Three automatic time-lapse cameras were installed along the orographic left valley flank, c. 150 m above the glacier’s surface, to monitor retreat and ablation from July to September 2020. Although time-lapse photogrammetry offers spatial and temporal high-resolution data, the various processing steps to calculate the glacier’s velocity field are challenging. Digital image correlation of the time-lapse series photos is achieved using a published Python library (How et al. (2020) PyTrx: a Python-based monoscopic terrestrial photogrammetry toolset for glaciology. Frontiers in Earth Science 8:21, doi:10.3389/feart.2020.00021), which was adapted for the Pasterze data set. Typical time intervals for the digital image correlation were two to ten days. Factors that hamper computing flow velocities from time-lapse series photos alone are low contrast of the glacier’s surface and ablation rates exceeding the horizontal flow velocity. The latter problem is solved with the aid of two high-resolution digital elevation models (DEMs), which were calculated using 790 drone images from flight missions on July 13 and September 15 2020. The photogrammetric (Structure from Motion) software Agisoft Metashape (v. 1.8.4) is used to calculate the two DEMs from dense point clouds with a resolution of 5 cm/pixel. Linear interpolation of the glacier’s elevation between the July and September DEM was used to provide an approximate surface for a given date within the monitoring period. With this additional processing step, we can project tracked pixels from the digital image correlation process on an adapted DEM, which reflects the absolute height on a certain date best. Our workflow illustrates that time-lapse series photos taken obliquely to the glacier’s surface can be used to compute the surficial velocity field with the aid of digital elevation models that yield the glacier’s surface at the beginning and at the end of the monitoring period. In fact, the glacier’s velocity field computed in that fashion is consistent with direct measurements from a sparse network of stakes and mapped structures.
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