Description: Spectral reflectance of glacier ice was measured on September 4, 2019, in the ablation zone of Jamtalferner, Austria, using an ASD Field Spec 2 handheld spectrometer. The instrument has an operating range of 325 to 1075nm. A new SRT-- 99-020 Spectralon (serial number 99AA08-0918-1593) manufactured by Lab Sphere was used to calibrate the instrument. Initial processing of the raw ASD data files was carried out using the “specdal” Python package. In total, 246 reflectance spectra were collected.12 spectra were measured at point locations and 234 were measured along 16 profile lines throughout the ablation zone of the glacier. The field of view for each measurement is a circle of approximately 30cm diameter. The surface characteristics of the ice varies between measurement sites and the data set contains spectra e.g. of dry ice, wet ice, and ice containing impurities such as mineral dust or debris, showing the spatial variability of spectral reflectance in the ablation zone. The data set also includes photographs of the ice surface at each measurement point to illustrate the different surface types.

Description: Monitoring of plant succession in glacier forelands so far has been restricted to field sampling. In this study, in situ vegetation sampling along a chronosequence between Little Ice Age (LIA) maximum extent and the recent glacier terminus at Jamtalferner/Silvretta (ferner is a Tyrolian toponym for glacier) is compared to time series of the Normalized Difference Vegetation Index (NDVI) calculated from 13 Landsat scenes (1985-2016). The glacier terminus positions at 16 dates between the LIA maximum and 2015 were analysed from historical maps, orthophotos and LiDAR images and used for site age determination. We sampled plots of different time since deglaciation, from very recent to approx. 150 years: after 100 years, roughly 80% of the ground is covered by plants and ground cover did not increase essentially thereafter. Species number increases from 10-20 species on young sites to 40-50 species after 100 years. The NDVI increases for all plots between 1985 and 2016, from a mean of 0.11 for 1985-1991 to 0.2 in 2009 and 0.27 in 2016. For the plots deglaciated between 1 and about 150 years, the NDVI increases with the time of exposure. As the increase in ground cover is clearly reproduced by the NDVI (R² ground cover/NDVI 0.84) - even for sparsely vegetated areas -, we see a high potential of satellite-borne NDVI to perform regional characterizations of glacier forelands for hydrological, ecological and hazard management related applications. This data collection comprises the galcier outlines, NDVIs and chronosequencing locations with diversity and ground cover data.

Description: The on-going glacier shrinkage in the Alps requires frequent updates of glacier outlines to provide an accurate database for monitoring or modeling purposes (e.g. determination of run-off, mass balance, or future glacier extent) and other applications. With the launch of the first Sentinel-2 (S2) satellite in 2015, it became possible to create a consistent, Alpine-wide glacier inventory with an unprecedented spatial resolution of 10 m. Fortunately, already the first S2 images acquired in August 2015 provided excellent mapping conditions for most of the glacierised regions in the Alps. We have used this opportunity to compile a new Alpine-wide glacier inventory in a collaborative team effort. In all countries, glacier outlines from the latest national inventories have been used as a guide to compile a consistent update. However, cloud cover over many glaciers in Italy required including also S2 scenes from 2016. Whereas the automated mapping of clean glacier ice was straightforward using the band ratio method, the numerous debris-covered glaciers required intense manual editing. The uncertainty in the outlines was determined with multiple digitising of 14 glaciers by all participants. Topographic information for all glaciers was derived from the ALOS AW3D30 DEM. Overall, we derived a total glacier area of 1806 ±60 km² when considering 4394 glaciers 〉0.01 km². This is 14% (-1.2%/a) less than the 2100 km² derived from Landsat scenes acquired in 2003 and indicating an unabated continuation of glacier shrinkage in the Alps since the mid-1980s. Due to the higher spatial resolution of S2 many small glaciers were additionally mapped in the new inventory or increased in size compared to 2003. An artificial reduction to the former extents would thus result in an even higher overall area loss. Still, the uncertainty assessment revealed locally considerable differences in interpretation of debris-covered glaciers, resulting in limitations for change assessment when using glacier extents digitised by different analysts.

Description: The glacier inventory data set includes shape files of glacier margins for the Austrian Silvretta for the year 2017 (Vorarlberg) and 2018 (Tyrol). The glacier outlines were delineated manually based on older Austrian glacier inventories and high resolution LiDAR data acquired by the Federal Administrations of Tyrol and Vorarlberg. The 46 glaciers of the Austrian Silvretta cover 13.1±0.4 km² in 2017/18, which is only 32±2% of their LIA extent of 40.9±4.1 km². Since the last inventory in 2006, three glaciers were gone.