This dataset is supplementary to the article of Scherler et al. (submitted), in which the global distribution of supraglacial debris cover is mapped and analyzed. For mapping supraglacial debris cover, we combined glacier outlines from the Randolph Glacier Inventory (RGI) version 6.0 (RGI consortium, 2017) with remote sensing-based ice and snow identification. Areas that belong to glaciers but that are neither ice nor snow were classified as debris cover. This dataset contains the outlines of the mapped debris-covered glaciers areas, stored in shapefiles (.shp).For creating this dataset, we used optical satellite data from Landsat 8 (for the time period 2013-2017), and from Sentinel-2A/B (2015-2017). For the ice and snow identification, we used three different algorithms: a red to short-wavelength infrared (swir) band ratio (RATIO; Hall et al., 1988), the normalized difference snow index (NDSI; Dozier, 1989), and linear spectral unmixing-derived fractional debris cover (FDC; e.g., Keshava and Mustard, 2002). For a detailed description of the debris-cover mapping and an analysis of the data, please see Scherler et al. (2019) to which these data are supplementary material.This dataset includes debris cover outlines based on either Landsat 8 (LS8; 30-m resolution) or Sentinel 2 (S2; 10-m resolution), and the three algorithms RATIO, NDSI, FDC. In total, there exist six different zip-files that each contain 19 shapefiles. The structure of the shapefiles follows that of the RGI version 6.0 (RGI consortium, 2017), with one shapefile for each RGI region. The original RGI shapefiles provide each glacier as one entry (feature) and include a variety of ancillary information, such as area, slope, aspect (RGI Consortium 2017a, Technical Note p. 12ff). Because the debris-cover outlines are based on the RGI v6.0 glacier outlines, all fields of the original shapefiles, which refer to the glacier, are retained, and expanded with four new fields:- DC_Area: Debris-covered area in m². Note that this unit for area is different from the unit used for reporting the glacier area (km²).- DC_BgnDate: Start of the time period from which satellite imagery was used to map debris cover.- DC_EndDate: End of the time period from which satellite imagery was used to map debris cover.- DC_CTSmean: Mean number of observations (CTS = COUNTS) per pixel and glacier. This number is derived from the number of available satellite images for the respective time period, reduced by filtering pixels due to cloud and snow cover.The dataset has a global extent and covers all of the glaciers in the RGI v. 6.0, but it exhibits poor coverage in the RGI region Subantarctic and Antarctic, where the debris cover extents are based on very few observations.
The data set comprises Sentinel-1 scene pair-velocity fields, as well as monthly and annually averaged velocity mosaics over Svalbard for the period January 2015 - November 2020. The data are provided as GeoTIFF rasters in UTM (scene-pair velocity fields) and polar stereographic north (mosaics) coordinate reference systems at a spatial resolution of 200 m and were derived by applying a well-established intensity offset tracking algorithm (Strozzi et al., 2002; Wegmüller et al., 2016; Friedl et al., 2018; Wendleder et al., 2018; Seehaus et al., 2018). For tracking, we used consecutive pairs of single or dual polarized Sentinel-1 SLC (Single Look Complex) TOPS (Terrain Observation with Progressive Scans in azimuth) SAR (Synthetic Aperture Radar) images recorded in IW (Interferometric Wide swath) mode at a pixel spacing of ~14 m in azimuth (az) and ~3 m in range (r), and a spatial coverage of ~250 x 250 km. For the time from 2015 to 2016, Sentinel-1 imagery is available at a minimum repeat cycle of 12 days and from 2016 onward at a minimum repeat cycle of 6 days.
The Sentinel-1 data were obtained from the ASF (Alaska Satellite Facility) DAAC (Distributed Active Archive Center), https://search.asf.alaska.edu. In case of dual polarized acquisitions (HH+HV or VV+VH), we only used the HH or VV channels for the processing.
The data presented here were produced to study glacial and glacio-fluvial catchment erosion using 'tracer thermochronology' where detrital downstream samples can be used to infer the source elevation sectors of sediments when integrated with known surface bedrock ages from the catchment. For the first time, our study used the zircon (U-Th)/He (ZHe) method as tracer thermochronometer. The samples come from the Leones Valley at the northeastern flank of the Northern Patagonian Icefield, Chile (46.7° S) This data set comprises ZHe analytical results from (i) six detrital samples of different depositional age and grain size (622 single-grain analyses in total), and (ii) two previously analyzed (Andrić-Tomašević et al., 2021) bedrock samples (22 single-grain analyses in total), as well as grain size measurements and lithology identification of two of the detrital samples (two pebble samples with 262 and 211 pebbles, respectively). Data are provided in 10 tab-delimited text files. The full description of the data and methods is provided in the data description file.