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Glaciers are crucial sources of freshwater in particular for the arid lowlands surrounding High Mountain Asia. To better constrain glacio-hydrological models, annual, or even better, seasonal information about glacier mass changes is highly beneficial. In this study, we evaluate the suitability of very-high-resolution Pléiades digital elevation models (DEMs) to measure glacier mass balance at annual and seasonal scales in two regions of High Mountain Asia (Muztagh Ata in Eastern Pamirs and parts of western Nyainqêntanglha, south-central Tibetan Plateau), where recent estimates have shown contrasting glacier behaviour. The average annual mass balance in Muztagh Ata between 2019 and 2022 was -0.07 ± 0.20 m w.e. a -1 , suggesting the continuation of a recent phase of slight mass loss following a prolonged period of balanced mass budgets previously observed. The mean annual mass balance in western Nyainqêntanglha was highly negative for the same period (-0.60 ± 0.15 m w.e. a -1), suggesting increased mass loss rates compared to the approximately previous 5 decades. The 2022 winter (+0.13 ± 0.24 m w.e.) and summer (-0.35 ± 0.15 m w.e.) mass budgets in Muztagh Ata and western Nyainqêntanglha (-0.03 ± 0.27 m w.e. in winter; -0.63 ± 0.07 m w.e. in summer) suggest winter- and summer-accumulation-type regimes, respectively. We support our findings by implementing the Sentinel-1-based Glacier Index to identify the firn and wet-snow areas on glaciers and characterize the accumulation type. The good match between the geodetic and Glacier Index results supports the potential of very-high-resolution Pléiades data to monitor mass balance at short timescales and improves our understanding of glacier accumulation regimes across High Mountain Asia. [ABSTRACT FROM AUTHOR]

The ongoing glacier shrinkage in the Alps requires frequent updates of glacier outlines to provide an accurate database for monitoring, modelling 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. The first S2 images from August 2015 already provided excellent mapping conditions for most glacierized regions in the Alps and were used as a base for the compilation of 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 an update consistent with the respective previous interpretation. The automated mapping of clean glacier ice was straightforward using the band ratio method, but the numerous debris-covered glaciers required intense manual editing. Cloud cover over many glaciers in Italy required also including S2 scenes from 2016. The outline uncertainty was determined with digitizing of 14 glaciers several times by all participants. Topographic information for all glaciers was obtained from the ALOS AW3D30 digital elevation model (DEM). Overall, we derived a total glacier area of 1806±60 km 2 when considering 4395 glaciers >0.01 km 2. This is 14 % (-1.2 % a -1) less than the 2100 km 2 derived from Landsat in 2003 and indicates an unabated continuation of glacier shrinkage in the Alps since the mid-1980s. It is a lower-bound estimate, as due to the higher spatial resolution of S2 many small glaciers were additionally mapped or increased in size compared to 2003. Median elevations peak around 3000 m a.s.l., with a high variability that depends on location and aspect. The uncertainty assessment revealed locally strong differences in interpretation of debris-covered glaciers, resulting in limitations for change assessment when using glacier extents digitized by different analysts. The inventory is available at 10.1594/PANGAEA.909133 (Paul et al., 2019). [ABSTRACT FROM AUTHOR]

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 in-tense manual editing. The uncertainty in the outlines was determined with a multiple digitising experiment 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. [ABSTRACT FROM AUTHOR]

Knowledge about the coverage and characteristics of glaciers in High Mountain Asia (HMA) is still incomplete and heterogeneous. However, several applications, such as modelling of past or future glacier development, run-off, 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 the Advanced Land Observing Satellite 1 (ALOS-1) Phased Array type L-band Synthetic Aperture Radar 1 (PALSAR-1) as an additional source of information; we then (i) separated the glacier complexes into individual glaciers using drainage divides derived by watershed analysis from the ASTER global digital elevation model version 2 (GDEM2) and (ii) 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 km 2 covering an area of 35520±1948 km 2 and an elevation range from 2260 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 km 2 , i.e. 10 % of the total glacierized 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 (10.1594/PANGAEA.894707). [ABSTRACT FROM AUTHOR]

The 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 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 way of automated digital glacier mapping and manual correction using coherence images from ALOS-1 PALSAR-1 as an additional source of information, 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 27'400 glaciers >0.02km2 covering an area of 35'287 ± 1209km2 and an elevation range from 2260m to 8600m with regional median glacier elevations varying from 4150m (Pamir Alai) to almost 5400m (Karakoram); this being largely due to differences in temperature and precipitation. The coverage of glaciers by debris is on average ~5%, but glaciers >5km2 have often a much higher area share (>10%), making it an important factor to be considered in subsequent applications. [ABSTRACT FROM AUTHOR]