Greenland Ice Sheet crevasse map from ArcticDEM

Data Description Title: Greenland Ice Sheet crevasse map from ArcticDEMVersion: 1.1Format: Cloud-Optimised GeoTiffProjection: WGS84 / NSIDC Sea Ice Polar Stereographic North (EPSG: 3413)Resolution: 2 m (binary) and 200 m (fraction)Size: 3.5 GB (total binary) and 22 MB (total fraction)Citation: Chudley et al. (2021) https://doi.org/10.1029/2021JF006287Contact: Tom ChudleyEmail: [e-mail] Citation When using this data, please cite: Chudley, T. R. (2022) Greenland Ice Sheet crevasse map from ArcticDEM. Zenodo [dataset]. https://doi.org/10.5281/zenodo.6779087 Chudley, T. R., Christoffersen, P., Doyle, S. H., Dowling, T. P. F., Law, R., Schoonman, C. M., Bougamont, M., & Hubbard, B. (2021). Controls on water storage and drainage in crevasses on the Greenland Ice Sheet. Journal of Geophysical Research: Earth Surface, 126, e2021JF006287. https://doi.org/10.1029/2021JF006287. Notes This dataset is for scientific purposes only. The method is not able to detect metre-scale and snow-covered crevasses, and should not be used for field safety purposes. This dataset is produced using the ArcticDEM v3 mosaic. Since release, the new ArcticDEM v4.1 mosaic has been released, and I have developed newer and open-source methods for extracting crevasse geometries from ArcticDEM and REMA strips. I am happy to help direct you towards the solution or dataset most appropriate for your needs - please contact me at [e-mail]. Version Updates v1.1 - File type converted to cloud-optimised geotiffs (CoGs) - updated January 2026. v1.0 - Initial upload. Products This dataset contains crevasse locations identified from the ArcticDEM v3 mosaic. There are two primary products: a 2 m binary crevasse map, and a 200 m crevasse fraction map. It is divided into the six IMBIE 'Rignot' drainage basins: central west (CW), southwest (SW), southeast (SE), northeast (NE), north (NO), northwest (NW). 2 m crevasse binary Byte GeoTiff product indicating derived crevasses at 2 m resolution. File naming convention is: crevasse_binary_XX_2m.tif where XX is the IMBIE basin code. Value Meaning 0 No data 1 No crevasses identified 2 Crevasses identified 200 m crevasse fraction Float32 GeoTiff product indicating fraction of 200 m grid cell identified as crevasses in the 200 m product. File naming convention is: crevasse_fraction_XX_2m.tif where XX is the IMBIE basin code. Value Meaning 0 - 1 Fraction of grid cell identified as crevasse in 2 m dataset -9999 No data Method The full processing chain for data derivation is described in Chudley et al. (2021). A binary crevasse mask of the Greenland Ice Sheet is generated using ArcticDEM v3 mosaic data at 2 m resolution (Porter et al., 2018), with data processed in Google Earth Engine (Gorelick et al., 2017). The ArcticDEM is cropped to the GIMP ice mask (Howat et al., 2014), before a smoothed elevation model is generated by performing an image convolution with a circular kernel of 50 m radius. Residuals greater than 1 m between the smoothed and raw elevation values were identified as crevasses. To compare with public velocity datasets (and derived strain rates, stress, etc.), the 2 m dataset was aggregated (using GDAL) into grid cells to match the resolution (200 m) of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) ice sheet surface velocity grid (Joughin, 2010; 2021). Aggregated values represent the fraction of grid cell area classified as crevasses. Caveats The method, including kernel size was tuned manually based on the region of interest of the original Chudley et al. (2021) paper. As such, it may not be optimal for other regions of interest on the ice sheet, in particular in the east, where medial moraines and marginal valleys are more prevalent (see caveat #4). The ArcticDEM is derived from optical MAXAR imagery. As such, snow-filled crevasses will not be identified here, which will be problematic above the ablation zone. Following comparison with Uncrewed Aerial Vehicle (UAV) data in Chudley et al. (2021), the approximate lower bound of crevasse width identified is ~10 m. These are large crevasses, far greater than are commonly encountered in safe fieldwork environments. This method is relatively crude: at its core, it is effectively a high-pass filter applied to the ArcticDEM mosaic. As such, there are false positives that occur around other supraglacial features (rivers, moraines, etc.) as well as marginal features (proglacial geomorphology, fjord sikkusak, etc.) that are captured in regions where the GIMP ice mask does not accurately capture the terrestrial ice extent at the time of ArcticDEM data capture. Users are encouraged to critically evaluate data in their areas of interest using the 2 m binary map and external data, even when intending to use only the 200 m fraction dataset. Acknowledgements Initial processing chain created whilst Chudley was supported by a Natural Environment Research Council Doctoral Training Partnership Studentship (Grant No. NE/L002507/1). ArcticDEM v3 mosaic is provided by the Polar Geospatial Center under NSF-OPP awards 1043681, 1559691, and 1542736. References Chudley, T. R., Christoffersen, P., Doyle, S. H., Dowling, T. P. F., Law, R., Schoonman, C. M., Bougamont, M., & Hubbard, B. (2021). Controls on water storage and drainage in crevasses on the Greenland Ice Sheet. Journal of Geophysical Research: Earth Surface, 126, e2021JF006287. https://doi.org/10.1029/2021JF006287. Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031 Howat, I. M., Negrete, A., & Smith, B. E. (2014). The Greenland Ice Mapping Project (GIMP) land classification and surface elevation data sets. The Cryosphere, 8(4), 1509–1518. https://doi.org/10.5194/tc-8-1509-2014 Joughin, I. (2021). MEaSUREs Greenland Annual Ice Sheet Velocity Mosaics from SAR and Landsat, Version 3. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/C2GFA20CXUI4 Joughin, I. (2010). Greenland Flow Variability from Ice-Sheet-Wide Velocity Mapping. Journal of Glaciology. 56. 415-430. https://doi.org/10.3189/002214310792447734 Porter, C., Morin, P., Howat, I., Noh, M.-J., Bates, B., Peterman, K., et al. (2018). ArcticDEM. Harvard Dataverse. https://doi.org/10.7910/DVN/OHHUKH