ALBERT

Description: Knowledge about the coverage and characteristics of glaciers in High Mountain Asia is still incomplete and heterogeneous. However, several applications such as modelling of past or future glacier development, runoff or glacier volume, rely on the existence and accessibility of complete datasets. In particular, precise outlines of glacier extent are required to spatially constrain glacier-specific calculations such as length, area and volume changes or flow velocities. As a contribution to the Randolph Glacier Inventory (RGI) and the Global Land Ice Measurements from Space (GLIMS) glacier database, we have produced a homogeneous inventory of the Pamir and the Karakoram mountain ranges using 28 Landsat TM and ETM+ scenes acquired around the year 2000. We applied a standardized method of automated digital glacier mapping and manual correction using coherence images from ALOS-1 PALSAR-1 as an additional source of information; we then separated the glacier complexes into individual glaciers using drainage divides derived by watershed analysis from the ASTER GDEM2, and separately delineated all debris-covered areas. Assessment of uncertainties was performed for debris-covered and clean-ice glacier parts using the buffer method and independent multiple digitizing of three glaciers representing key challenges such as shadows and debris cover. Indeed, along with seasonal snow at high elevations, shadow and debris cover represent the largest uncertainties in our final dataset. In total, we mapped more than 27'800 glaciers 〉0.02 km² covering an area of 35'520 ±1948 km² and an elevation range from 2260 m to 8600 m. Regional median glacier elevations vary from 4150 m (Pamir Alai) to almost 5400 m (Karakoram), which is largely due to differences in temperature and precipitation. Supraglacial debris covers an area of 3587 ±662 km², i.e. 10% of the total glacierised area. Larger glaciers have a higher share in debris-covered area (up to 〉20%), making it an important factor to be considered in subsequent applications.

Description: A dataset with all surging glaciers detected between 1988 and 2018 based on Landsat TM, ETM+ and OLI images, AW3D30, SRTM and Corona DEMs, high resolution imagery from Corona, Hexagon, GoogleEarth and bing.com. The basis for this dataset is the glacier inventory of Pamir and Karakoram (Mölg et al., 2018). Our dataset includes three shapefiles that contain the surging glaciers in their base extension (GI-3), their minimum extension (GI-3min) and their maximum extension (GI-3max). The GI-3min inventory contains also attributes to the distinct glacier surges (start year, end year, duration and additional information - all three attributes refer to the active phases of the glaciers). Due to the highest differentiation of glacier bodies for the minimum extent these attributes are missing in the other two shapefiles.

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: Nearly complete mosaics of winter ice surface velocities for the 1990's over the Eastern Arctic (Novaya Zemlya, Franz-Josef-Land, Severnaya Zemlya and Svalbard) were compiled based on historical SAR data. Offset-tracking to JERS-1 SAR data of the time period 1992-1998 was mainly applied. Data gaps were complemented using SAR interferometry and offset-tracking of ERS-1/2 SAR data of the time period 1991-1997. Knowledge on ice surface velocity of glaciers and ice caps contributes to a better understanding of a wide range of processes related to glacier dynamics, mass change and response to climate. In order to study long-term variability of winter ice surface velocity from the 1990's to present, velocity maps computed with offset-tracking from 2008-2011 ALOS-1 PALSAR-1 and 2020-2021 Sentinel-1 data are also provided.