ABSTRACT. Deriving glacier outlines from satellite data has become increasingly popular in the past decade. In particular when glacier outlines are used as a base for change assessment, it is important to know how accurate they are. Calculating the accuracy correctly is challenging, as appropriate reference data (e.g. from higher-resolution sensors) are seldom available. Moreover, after the required manual correction of the raw outlines (e.g. for debris cover), such a comparison would only reveal the accuracy of the analyst rather than of the algorithm applied. Here we compare outlines for clean and debriscovered glaciers, as derived from single and multiple digitizing by different or the same analysts on very high-(1 m) and medium-resolution (30 m) remote-sensing data, against each other and to glacier outlines derived from automated classification of Landsat Thematic Mapper data. Results show a high variability in the interpretation of debris-covered glacier parts, largely independent of the spatial resolution (area differences were up to 30%), and an overall good agreement for clean ice with sufficient contrast to the surrounding terrain (differences $5%). The differences of the automatically derived outlines from a reference value are as small as the standard deviation of the manual digitizations from several analysts. Based on these results, we conclude that automated mapping of clean ice is preferable to manual digitization and recommend using the latter method only for required corrections of incorrectly mapped glacier parts (e.g. debris cover, shadow).

Glacier inventories provide essential baseline information for the determination of water resources, glacier-specific changes in area and volume, climate change impacts as well as past, potential and future contribution of glaciers to sea-level rise. Although Greenland is heavily glacierised and thus highly relevant for all of the above points, a complete inventory of its glaciers was not available so far. Here we present the results and details of a new and complete inventory that has been compiled from more than 70 Landsat scenes (mostly acquired between 1999 and 2002) using semi-automated glacier mapping techniques. A digital elevation model (DEM) was used to derive drainage divides from watershed analysis and topographic attributes for each glacier entity. To serve the needs of different user communities, we assigned to each glacier one of three connectivity levels with the ice sheet (CL0, CL1, CL2; i.e. no, weak, and strong connection) to clearly, but still flexibly, distinguish the local glaciers and ice caps (GIC) from the ice sheet and its outlet glaciers. In total, we mapped ~ 20 300 glaciers larger than 0.05 km² (of which ~ 900 are marine terminating), covering an area of 130 076 ± 4032 km², or 89 720 ± 2781 km² without the CL2 GIC. The latter value is about 50% higher than the mean value of more recent previous estimates. Glaciers smaller than 0.5 km² contribute only 1.5% to the total area but more than 50% (11 000) to the total number. In contrast, the 25 largest GIC (> 500 km²) contribute 28% to the total area, but only 0.1% to the total number. The mean elevation of the GIC is 1700 m in the eastern sector and around 1000 m otherwise. The median elevation increases with distance from the coast, but has only a weak dependence on mean glacier aspect

Meltwater from glaciers in the European Alps plays an important role in hydropower production, and future glacier development is thus of economic interest. However, an up-to-date and alpine-wide inventory for accurate assessment of glacier changes or modelling of future glacier development has not hitherto been available. Here we present a new alpine-wide inventory (covering Austria, France, Italy and Switzerland) derived from ten Landsat Thematic Mapper (TM) scenes acquired within 7 weeks in 2003. Combined with the globally available digital elevation model from the Shuttle Radar Topography Mission, topographic inventory parameters were derived for each of the 3770 mapped glaciers, covering 2050km2. The area-class frequency distribution is very similar in all countries, and a mean northerly aspect (NW, N, NE) is clearly favoured (arithmetic counting). Mean glacier elevation is 2900 m, with a small dependence on aspect. The total area loss since the previous glacier inventory (acquired around 1970 ±15 years) is roughly one-third, yielding a current area loss rate of 2%a-1. Digital overlay of the outlines from the latest Austrian glacier inventory revealed differences in the interpretation of glacier extents that prohibit change assessment. A comparison of TM-derived outlines with manually digitized extents on a high-resolution IKONOS image returned 1.5% smaller glaciers with TM.

Abstract. Glacier fluctuations contribute to variations in sea level and historical glacier length fluctuations are natural indicators of past climate change. To study these subjects, long-term information of glacier change is needed. In this paper we present a data set of global long-term glacier length fluctuations. The data set is a compilation of available information on changes in glacier length worldwide, including both measured and reconstructed glacier length fluctuations. All 471 length series start before 1950 and cover at least four decades. The longest record starts in 1535, but the majority of time series start after 1850. The number of available records decreases again after 1962. The data set has global coverage including records from all continents. However, the Canadian Arctic is not represented in the data set. The available glacier length series show relatively small fluctuations until the mid-19th century, followed by a global retreat. The retreat was strongest in the first half of the 20th century, although large variability in the length change of the different glaciers is observed. During the 20th century, calving glaciers retreated more than land-terminating glaciers, but their relative length change was approximately equal. Besides calving, the glacier slope is the most important glacier property determining length change: steep glaciers have retreated less than glaciers with a gentle slope.

Abstract. 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 km2 when considering 4395 glaciers >0.01 km2. This is 14 % (−1.2 % a−1) less than the 2100 km2 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 https://doi.org/10.1594/PANGAEA.909133 (Paul et al., 2019).