The data set comprises an inter- and intra-annual timeseries of ten high-resolution (0.5 x 0.5 m) binary snow covered area (SCA) maps derived from TLS scans at the Weisssee Snow Research Site in Austria between March 2017 and November 2019. TLS based digital elevation models and difference (snow depth) grids can be downloaded as a separate dataset (Fey et al., 2018; https://doi.org/10.1594/PANGAEA.896843).
The binary classification of snow-covered and snow-free areas is based on intensity and snow depth. An intensity threshold of 3000 was defined based on histogram analysis in patchy snowpack conditions. Snow-covered areas were delineated according to TLS based snow depth information. Snow-depth related classifications were based on a threshold value representing the precision of the TLS acquisition represented by the standard deviation of snow-free surfaces (see Fey et al., 2019). The resulting classification was validated with fully snow covered scenes. For the scene of 2017-05-07 two available TLS scans, one with a Riegl VZ-4000 and another with a Riegl VZ-6000 scanner, were combined into one snow covered area map. This was done due to the fact that the VZ-4000 data is better suited for snow cover discrimination based on intensity data, while not providing data on wet snow surfaces in larger distance where the VZ-6000 scanner still provides snow depth observations.
The overall coverage of the scan area is identical to the one of the DGM dataset. The SCA dataset comprises three classes: snow-free (0), snow-covered (1) and NoData (-99999). No data areas are caused by obstacles in the field-of-view of the laserscanner. The SCA data can be used for validating remote sensing products including fractional snow coverage from e.g. Landsat and Sentinel-2 as done in the related literature
