Barbat, M. M., Rackow, T., Wesche, C., Hellmer, H. H., and Mata, M. M.:
Automated iceberg tracking with a machine learning approach applied to SAR
imagery: A Weddell sea case study, ISPRS J. Photogramm., 172, 189–206, https://doi.org/10.1016/j.isprsjprs.2020.12.006, 2021.
Baumhoer, C. A., Dietz, A. J., Kneisel, C., and Kuenzer, C.: Automated
extraction of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery
using deep learning, Remote Sens.-Basel, 11, 2529, https://doi.org/10.3390/rs11212529,
2019.
Berberoglu, S., Lloyd, C. D., Atkinson, P. M., and Curran, P. J.: The
integration of spectral and textural information using neural networks for
land cover mapping in the Mediterranean, Comput. Geosci., 26,
385–396, https://doi.org/10.1016/S0098-3004(99)00119-3, 2000.
Bevan, S. L., Luckman, A. J., and Murray, T.: Glacier dynamics over the last quarter of a century at Helheim, Kangerdlugssuaq and 14 other major Greenland outlet glaciers, The Cryosphere, 6, 923–937, https://doi.org/10.5194/tc-6-923-2012, 2012.
Bevan, S. L., Luckman, A. J., Benn, D. I., Cowton, T., and Todd, J.: Impact of warming shelf waters on ice mélange and terminus retreat at a large SE Greenland glacier, The Cryosphere, 13, 2303–2315, https://doi.org/10.5194/tc-13-2303-2019, 2019.
Bolch, T., Menounos, B., and Wheate, R.: Landsat-based inventory of glaciers
in western Canada, 1985–2005, Remote Sens. Environ., 114,
127–137, https://doi.org/10.1016/j.rse.2009.08.015, 2010.
Brough, S., Carr, J. R., Ross, N., and Lea, J. M.: Exceptional retreat of
Kangerlussuaq Glacier, East Greenland, between 2016 and 2018, Front.
Earth Sci., 7, 123, https://doi.org/10.3389/feart.2019.00123, 2019.
Bunce, C., Carr, J. R., Nienow, P. W., Ross, N., and Killick, R.: Ice front
change of marine-terminating outlet glaciers in northwest and southeast
Greenland during the 21st century, J. Glaciol., 64, 523–535,
https://doi.org/10.1017/jog.2018.44, 2018.
Carbonneau, P. E., Dugdale, S. J., Breckon, T. P., Dietrich, J. T., Fonstad,
M. A., Miyamoto, H., and Woodget, A. S.: Adopting deep learning methods for
airborne RGB fluvial scene classification, Remote Sens. Environ.,
251, 112107, https://doi.org/10.1016/j.rse.2020.112107, 2020a.
Carbonneau, P. E., Belletti, B., Micotti, M., Lastoria, B., Casaioli, M.,
Mariani, S., Marchetti, G., and Bizzi, S.: UAV-based training for fully fuzzy
classification of Sentinel-2 fluvial scenes, Earth Surf. Proc.
Land., 45, 3120–3140, https://doi.org/10.1002/esp.4955, 2020b.
Carr, J. R., Stokes, C. R., and Vieli, A.: Threefold increase in
marine-terminating outlet glacier retreat rates across the Atlantic Arctic:
1992–2010, Ann. Glaciol., 58, 72–91, https://doi.org/10.1017/aog.2017.3,
2017.
Carroll, D., Sutherland, D. A., Hudson, B., Moon, T., Catania, G. A.,
Shroyer, E. L., Nash, J. D., Bartholomaus, T. C., Felikson, D., Stearns, L.
A., Noël, B. P. Y., and van den Broeke, M. R.: The impact of glacier
geometry on meltwater plume structure and submarine melt in Greenland
fjords, Geophys. Res. Lett., 43, 9739–9748,
https://doi.org/10.1002/2016GL070170, 2016.
Cassotto, R., Fahnestock, M., Amundson, J. M., Truffer, M., and Joughin, I.:
Seasonal and interannual variations in ice melange and its impact on
terminus stability, Jakobshavn Isbræ, Greenland, J. Glaciol.,
61, 76–88, https://doi.org/10.3189/2015JoG13J235, 2015.
Catania, G. A., Stearns, L. A., Sutherland, D. A., Fried, M. J.,
Bartholomaus, T. C., Morlighem, M., Shroyer, E., and Nash, J.: Geometric
controls on tidewater glacier retreat in central western Greenland, J. Geophys. Res.-Earth, 123, 2024–2038,
https://doi.org/10.1029/2017JF004499, 2018.
Catania, G. A., Stearns, L. A., Moon, T. A., Enderlin, E. M., and Jackson, R.
H.: Future evolution of Greenland's marine-terminating outlet glaciers,
J. Geophys. Res.-Earth, 125, e2018JF004873, https://doi.org/10.1029/2018JF004873, 2020.
Chauché, N., Hubbard, A., Gascard, J.-C., Box, J. E., Bates, R., Koppes, M., Sole, A., Christoffersen, P., and Patton, H.: Ice–ocean interaction and calving front morphology at two west Greenland tidewater outlet glaciers, The Cryosphere, 8, 1457–1468, https://doi.org/10.5194/tc-8-1457-2014, 2014.
Cheng, D., Hayes, W., Larour, E., Mohajerani, Y., Wood, M., Velicogna, I., and Rignot, E.: Calving Front Machine (CALFIN): glacial termini dataset and automated deep learning extraction method for Greenland, 1972–2019, The Cryosphere, 15, 1663–1675, https://doi.org/10.5194/tc-15-1663-2021, 2021.
Chollet, F.: Deep learning with Python, Manning Publications Co, Shelter
Island, New York, 384 pp., ISBN 978 1 6172 9443 3, 2017.
Cook, A. J., Copland, L., Noël, B. P. Y., Stokes, C. R., Bentley, M. J.,
Sharp, M. J., Bingham, R. G., and van den Broeke, M. R.: Atmospheric forcing
of rapid marine-terminating glacier retreat in the Canadian Arctic
Archipelago, Sci. Adv., 5, eaau8507, https://doi.org/10.1126/sciadv.aau8507, 2019.
Copernicus Open Access Hub: Sentinel-2 imagery, Copernicus [data set], available at:
https://scihub.copernicus.eu/dhus/#/home, last access: 20 July 2020.
Enderlin, E. M., Howat, I. M., Jeong, S., Noh, M.-J., van Angelen, J. H., and
van den Broeke, M. R.: An improved mass budget for the Greenland ice sheet,
Geophys. Res. Lett., 41, 866–872, https://doi.org/10.1002/2013GL059010,
2014.
Everett, A., Kohler, J., Sundfjord, A., Kovacs, K. M., Torsvik, T.,
Pramanik, A., Boehme, L., and Lydersen, C.: Subglacial discharge plume
behaviour revealed by CTD-instrumented ringed seals, Sci. Rep.-UK,
8, 13467, https://doi.org/10.1038/s41598-018-31875-8, 2018.
Foga, S., Stearns, L. A., and van der Veen, C. J.: Application of satellite
remote sensing techniques to quantify terminus and ice mélange behavior
at Helheim Glacier, East Greenland, Mar. Technol. Soc. J.,
48, 81–91, https://doi.org/10.4031/MTSJ.48.5.3, 2014.
Frey, H., Paul, F., and Strozzi, T.: Compilation of a glacier inventory for
the western Himalayas from satellite data: methods, challenges, and results,
Remote Sens. Environ., 124, 832–843, https://doi.org/10.1016/j.rse.2012.06.020,
2012.
Gerrish, L.: The coastline of Kalaallit Nunaat/ Greenland available as a
shapefile and geopackage, covering the main land and islands, with glacier
fronts updated as of 2017, 2 files, 5.26 MB,
https://doi.org/10.5285/8CECDE06-8474-4B58-A9CB-B820FA4C9429, 2020.
Guo, W., Liu, S., Xu, J., Wu, L., Shangguan, D., Yao, X., Wei, J., Bao, W.,
Yu, P., Liu, Q., and Jiang, Z.: The second Chinese glacier inventory: data,
methods and results, J. Glaciol., 61, 357–372,
https://doi.org/10.3189/2015JoG14J209, 2015.
Hill, E. A., Carr, J. R., and Stokes, C. R.: A review of recent changes in
major marine-terminating outlet glaciers in northern Greenland, Front.
Earth Sci., 4, 111, https://doi.org/10.3389/feart.2016.00111, 2017.
Hochreuther, P., Neckel, N., Reimann, N., Humbert, A., and Braun, M.: Fully
automated detection of supraglacial lake area for northeast Greenland using
Sentinel-2 time-series, Remote Sens.-Basel, 13, 205, https://doi.org/10.3390/rs13020205,
2021.
Hoeser, T., Bachofer, F., and Kuenzer, C.: Object detection and image
segmentation with deep learning on earth observation data: a review – part
II: applications, Remote Sens.-Basel, 12, 3053, https://doi.org/10.3390/rs12183053,
2020.
How, P., Benn, D. I., Hulton, N. R. J., Hubbard, B., Luckman, A., Sevestre, H., van Pelt, W. J. J., Lindbäck, K., Kohler, J., and Boot, W.: Rapidly changing subglacial hydrological pathways at a tidewater glacier revealed through simultaneous observations of water pressure, supraglacial lakes, meltwater plumes and surface velocities, The Cryosphere, 11, 2691–2710, https://doi.org/10.5194/tc-11-2691-2017, 2017.
Howat, I. M., Joughin, I., and Scambos, T. A.: Rapid changes in ice discharge
from Greenland outlet glaciers, Science, 315, 1559–1561,
https://doi.org/10.1126/science.1138478, 2007.
Howat, I. M., Ahn, Y., Joughin, I., van den Broeke, M. R., Lenaerts, J. T.
M., and Smith, B.: Mass balance of Greenland's three largest outlet glaciers,
2000–2010, Geophys. Res. Lett., 38, L12501, https://doi.org/10.1029/2011GL047565,
2011.
Joughin, I., Howat, I. M., Fahnestock, M., Smith, B., Krabill, W., Alley, R.
B., Stern, H., and Truffer, M.: Continued evolution of Jakobshavn Isbrae
following its rapid speedup, J. Geophys. Res.-Earth,
113, F04006, https://doi.org/10.1029/2008JF001023, 2008.
Juan, J. de, Elósegui, P., Nettles, M., Larsen, T. B., Davis, J. L.,
Hamilton, G. S., Stearns, L. A., Andersen, M. L., Ekström, G.,
Ahlstrøm, A. P., Stenseng, L., Khan, S. A., and Forsberg, R.: Sudden
increase in tidal response linked to calving and acceleration at a large
Greenland outlet glacier, Geophys. Res. Lett., 37, L12501,
https://doi.org/10.1029/2010GL043289, 2010.
King, M. D., Howat, I. M., Jeong, S., Noh, M. J., Wouters, B., Noël, B., and van den Broeke, M. R.: Seasonal to decadal variability in ice discharge from the Greenland Ice Sheet, The Cryosphere, 12, 3813–3825, https://doi.org/10.5194/tc-12-3813-2018, 2018.
King, M. D., Howat, I. M., Candela, S. G., Noh, M. J., Jeong, S., Noël,
B. P. Y., van den Broeke, M. R., Wouters, B., and Negrete, A.: Dynamic ice
loss from the Greenland Ice Sheet driven by sustained glacier retreat,
Communications Earth & Environment, 1, 1–7,
https://doi.org/10.1038/s43247-020-0001-2, 2020.
Kingma, D. P. and Ba, J.: Adam: A method for Stochastic Optimization, arXiv [preprint],
http://arxiv.org/abs/1412.6980, 2017.
Krieger, L. and Floricioiu, D.: Automatic glacier calving front delineation
on TerraSAR-X and Sentinel-1 SAR imagery, in: 2017 IEEE Int.
Geosci. Remote Se. (IGARSS), 2817–2820, https://doi.org/10.1109/IGARSS.2017.8127584, 2017.
Lea, J. M.: Google Earth Engine Digitisation Tool (GEEDiT), and Margin
change Quantification Tool (MaQiT) – simple tools for the rapid mapping and
quantification of changing Earth surface margins, Earth Surf. Dynam.,
6, 551–561, 2018.
Lea, J. M., Mair, D. W. F., and Rea, B. R.: Evaluation of existing and new
methods of tracking glacier terminus change, J. Glaciol., 60,
323–332, https://doi.org/10.3189/2014JoG13J061, 2014.
LeCun, Y., Bengio, Y., and Hinton, G.: Deep learning, Nature, 521,
436–444, https://doi.org/10.1038/nature14539, 2015.
Li, X., Myint, S. W., Zhang, Y., Galletti, C., Zhang, X., and Turner, B. L.:
Object-based land-cover classification for metropolitan Phoenix, Arizona,
using aerial photography, Int. J. Appl. Earth Obs., 33, 321–330, https://doi.org/10.1016/j.jag.2014.04.018, 2014.
Liu, H. and Jezek, K. C.: A complete high-resolution coastline of Antarctica
extracted from orthorectified Radarsat SAR imagery, Photogramm.
Eng. Rem. S., 70, 605–616, https://doi.org/10.14358/PERS.70.5.605,
2004.
Liu, X., Deng, Z., and Yang, Y.: Recent progress in semantic image
segmentation, Artif. Intell. Rev., 52, 1089–1106,
https://doi.org/10.1007/s10462-018-9641-3, 2019.
Miles, B. W. J., Stokes, C. R., and Jamieson, S. S. R.: Pan–ice-sheet
glacier terminus change in East Antarctica reveals sensitivity of Wilkes
Land to sea-ice changes, Sci. Adv., 2, e1501350,
https://doi.org/10.1126/sciadv.1501350, 2016.
Miles, B. W. J., Stokes, C. R., and Jamieson, S. S. R.: Velocity increases at Cook Glacier, East Antarctica, linked to ice shelf loss and a subglacial flood event, The Cryosphere, 12, 3123–3136, https://doi.org/10.5194/tc-12-3123-2018, 2018.
Mohajerani, Y., Wood, M., Velicogna, I., and Rignot, E.: Detection of glacier
calving margins with Convolutional Neural Networks: a case study, Remote
Sens.-Basel, 11, 74, https://doi.org/10.3390/rs11010074, 2019.
Mouginot, J., Rignot, E., Bjørk, A. A., van den Broeke, M., Millan, R.,
Morlighem, M., Noël, B., Scheuchl, B., and Wood, M.: Forty-six years of
Greenland Ice Sheet mass balance from 1972 to 2018, P. Natl. Acad. Sci., 116,
9239–9244, https://doi.org/10.1073/pnas.1904242116, 2019.
Nijhawan, R., Das, J., and Raman, B.: A hybrid of deep learning and
hand-crafted features based approach for snow cover mapping, Int.
J. Remote Sens., 40, 759–773,
https://doi.org/10.1080/01431161.2018.1519277, 2019.
Noël, B., van de Berg, W. J., Lhermitte, S., and van den Broeke, M. R.:
Rapid ablation zone expansion amplifies north Greenland mass loss, Sci.
Adv., 5, eaaw0123, https://doi.org/10.1126/sciadv.aaw0123, 2019.
Paul, F., Winsvold, S. H., Kääb, A., Nagler, T., and Schwaizer, G.:
Glacier remote sensing using Sentinel-2, Part II: mapping glacier extents
and surface facies, and comparison to Landsat 8, Remote Sens.-Basel, 8, 575,
https://doi.org/10.3390/rs8070575, 2016.
Rastner, P., Bolch, T., Mölg, N., Machguth, H., Le Bris, R., and Paul, F.: The first complete inventory of the local glaciers and ice caps on Greenland, The Cryosphere, 6, 1483–1495, https://doi.org/10.5194/tc-6-1483-2012, 2012.
Rignot, E. and Kanagaratnam, P.: Changes in the velocity structure of the
Greenland Ice Sheet, Science, 311, 986–990,
https://doi.org/10.1126/science.1121381, 2006.
Robson, B. A., Bolch, T., MacDonell, S., Hölbling, D., Rastner, P. and
Schaffer, N.: Automated detection of rock glaciers using deep learning and
object-based image analysis, Remote Sens. Environ., 250, 112033,
https://doi.org/10.1016/j.rse.2020.112033, 2020.
Rolnick, D., Veit, A., Belongie, S., and Shavit, N.: Deep learning is robust
to massive label noise, arXiv [preprint],
http://arxiv.org/abs/1705.10694, 2018.
Ronneberger, O., Fischer, P., and Brox, T.: U-Net: Convolutional Networks for
biomedical image segmentation, in: Medical Image Computing and
Computer-Assisted Intervention – MICCAI 2015, edited by: Navab, N.,
Hornegger, J., Wells, W. M., and Frangi, A. F., pp. 234–241, Springer
International Publishing, New York, Cham., https://doi.org/10.1007/978-3-319-24574-4_28, 2015.
Rumelhart, D. E., Hinton, G. E., and Williams, R. J.: Learning Internal Representations by Error Propagation, in: Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol. 1: Foundations, edited by: Rumelhart, D. E., McClelland, J. L., and the PDP Research Group, MIT Press, Cambridge, MA, 318–362, 1986.
Seale, A., Christoffersen, P., Mugford, R. I., and O'Leary, M.: Ocean forcing
of the Greenland Ice Sheet: calving fronts and patterns of retreat
identified by automatic satellite monitoring of eastern outlet glaciers,
J. Geophys. Res.- Earth, 116, F03013, https://doi.org/10.1029/2010JF001847, 2011.
Sharma, A., Liu, X., Yang, X., and Shi, D.: A patch-based convolutional
neural network for remote sensing image classification, Neural Networks, 95,
19–28, https://doi.org/10.1016/j.neunet.2017.07.017, 2017.
Simonyan, K. and Zisserman, A.: Very Deep Convolutional Networks for
Large-Scale Image Recognition, arXiv [preprint],
http://arxiv.org/abs/1409.1556, 2015.
Sohn, H.-G. and Jezek, K. C.: Mapping ice sheet margins from ERS-1 SAR and
SPOT imagery, Int. J. Remote Sens., 20,
3201–3216, https://doi.org/10.1080/014311699211705, 1999.
Stokes, C. R., Andreassen, L. M., Champion, M. R., and Corner, G. D.:
Widespread and accelerating glacier retreat on the Lyngen Peninsula,
northern Norway, since their “Little Ice Age” maximum, J.
Glaciol., 64, 100–118, https://doi.org/10.1017/jog.2018.3, 2018.
Straneo, F., Hamilton, G. S., Stearns, L. A., and Sutherland, D. A.:
Connecting the Greenland Ice Sheet and the ocean: a case study of Helheim
Glacier and Sermilik fjord, Oceanography, 29, 34–45, 2016.
Sutherland, D. A., Jackson, R. H., Kienholz, C., Amundson, J. M., Dryer, W.
P., Duncan, D., Eidam, E. F., Motyka, R. J., and Nash, J. D.: Direct
observations of submarine melt and subsurface geometry at a tidewater
glacier, Science, 365, 369–374, https://doi.org/10.1126/science.aax3528, 2019.
Tuckett, P. A., Ely, J. C., Sole, A. J., Livingstone, S. J., Davison, B. J.,
van Wessem, J. M., and Howard, J.: Rapid accelerations of Antarctic
Peninsula outlet glaciers driven by surface melt, Nat. Commun.,
10, 4311, https://doi.org/10.1038/s41467-019-12039-2, 2019.
Vaughan, D. G., Comiso, J. C., Allison, I., Carrasco, J., Kaser, G., Kwok, R., Mote, P., Murray, T., Paul, F., Ren, J., Rignot, E., Solomina, O., Steffen, K., and Zhang, T.: Observations: Cryosphere, In: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013.
Wood, M., Rignot, E., Fenty, I., Menemenlis, D., Millan, R., Morlighem, M.,
Mouginot, J., and Seroussi, H.: Ocean-induced melt triggers glacier retreat
in northwest Greenland, Geophys. Res. Lett., 45, 8334–8342,
https://doi.org/10.1029/2018GL078024, 2018.
Xie, Z., Haritashya, U. K., Asari, V. K., Young, B. W., Bishop, M. P., and
Kargel, J. S.: GlacierNet: a deep-learning approach for debris-covered
glacier mapping, IEEE Access, 8, 83495–83510,
https://doi.org/10.1109/ACCESS.2020.2991187, 2020.
Yu, Y., Zhang, Z., Shokr, M., Hui, F., Cheng, X., Chi, Z., Heil, P., and
Chen, Z.: Automatically extracted Antarctic coastline using remotely-sensed
data: an update, Remote Sens.-Basel, 11, 1844, https://doi.org/10.3390/rs11161844, 2019.
Yuan, J., Chi, Z., Cheng, X., Zhang, T., Li, T., and Chen, Z.: Automatic
extraction of supraglacial lakes in southwest Greenland during the
2014–2018 melt seasons based on Convolutional Neural Network, Water, 12,
891, https://doi.org/10.3390/w12030891, 2020.
Zhang, E., Liu, L., and Huang, L.: Automatically delineating the calving front of Jakobshavn Isbræ from multitemporal TerraSAR-X images: a deep learning approach, The Cryosphere, 13, 1729–1741, https://doi.org/10.5194/tc-13-1729-2019, 2019.
