Recent significant subseasonal fluctuations of supraglacial lakes on Greenland monitored by passive optical satellites

[en] Temporarily impounded liquid water on the surface of the Greenland Ice Sheet (GrIS), prominently represented as supraglacial lakes (SGLs), may enhance ice flow and modulate surface meltwater runoff, serving as a dynamic indicator of the cryohydrologic cycle. Despite their importance in understanding glacier mass balance and regional climate change, a detailed description of SGLs and their intra-annual fluctuations across the entire GrIS remains understudied. Here, we present a deep learning-based approach to automatically map SGLs from passive optical satellite imagery across the entire GrIS during the melt seasons of 2017–2022. Approximately 150,000 Sentinel-2 and Landsat 8/9 images were utilized, each representing a 5-day average composite at a 10 km × 10 km grid resolution, with the Landsat images used as possible supplements. SGL predictions by the proposed method demonstrate high performance, achieving an F1-score of up to 0.959 compared to the independent test dataset. This high accuracy enables a detailed analysis of the key role SGLs play in enhancing surface ablation by absorbing solar radiation and delivering meltwater. The SGL-driven ablation effect was most pronounced in the South-West basin of the GrIS, where the peak lake area in July accounted for 44.9 % of the total GrIS-wide lake area. In contrast, the lowest magnitude (4.2 %) was observed in the South-East basin, despite similarly strong ablation in this region. Among all the generated SGL occurrence grids, peak SGL areas in certain grids (∼14 % of the total) were observed in May or September, rather than exclusively during the typical high-ablation months of June to August, reflecting regional and elevation-dependent variations. Grids further from the ice sheet margin generally showed peak SGL areas later in the melt season, which is evident in the western part of the GrIS. Monthly SGL peak areas shift dramatically from 253.18 ± 123.94 km2 to 5084.90 ± 1043.26 km2, with the lowest in May 2018 and the highest in August 2021. An extraordinary area spike occurred in September 2022 and was particularly monitored in the South-West basin, where abnormally intense rainfall and runoff simulated by the Modèle Atmosphérique Régional (MAR) model were recorded. Our study highlights the significance of examining SGL area changes at short temporal intervals to understand the dynamics of cryospheric hydrology under future climate scenarios.

Research Center/Unit :

SPHERES - ULiège

Disciplines :

Earth sciences & physical geography

Author, co-author :

Qiu, Jiahui

Ran, Jiangjun

Tangdamrongsub, Natthachet

Fettweis, Xavier ; Université de Liège - ULiège > Département de géographie > Climatologie et Topoclimatologie

Ali, Shoaib

Feng, Wei

Wan, Xiaoyun

Language :

English

Title :

Recent significant subseasonal fluctuations of supraglacial lakes on Greenland monitored by passive optical satellites

Publication date :

October 2025

Journal title :

Remote Sensing of Environment

ISSN :

0034-4257

eISSN :

1879-0704

Publisher :

Elsevier

Volume :

328

Pages :

114896

Peer reviewed :

Peer Reviewed verified by ORBi

Tags :

CÉCI : Consortium des Équipements de Calcul Intensif

Additional URL :

https://api.elsevier.com/content/article/PII:S0034425725003001?httpAccept=text/xml

Funders :

AIT - Asian Institute of Technology
NSCF - National Natural Science Foundation of China

Available on ORBi :

since 07 July 2025

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Bibliography

Andrews, L.C., Catania, G.A., Hoffman, M.J., Gulley, J.D., Lüthi, M.P., Ryser, C., Hawley, R.L., Neumann, T.A., Direct observations of evolving subglacial drainage beneath the Greenland ice sheet. Nature 514 (2014), 80–83.
Badrinarayanan, V., Kendall, A., Cipolla, R., SegNet: a deep convolutional encoder-decoder architecture for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39 (2017), 2481–2495.
Banwell, A.F., Willis, I.C., Macdonald, G.J., Goodsell, B., MacAyeal, D.R., Direct measurements of ice-shelf flexure caused by surface meltwater ponding and drainage. Nat. Commun. 10 (2019), 1–10.
Bell, R.E., Chu, W., Kingslake, J., Das, I., Tedesco, M., Tinto, K.J., Zappa, C.J., Frezzotti, M., Boghosian, A., Lee, W.S., Antarctic ice shelf potentially stabilized by export of meltwater in surface river. Nature 544 (2017), 344–348.
Benedek, C.L., Willis, I.C., Winter drainage of surface lakes on the Greenland ice sheet from Sentinel-1 SAR imagery. Cryosphere 15 (2021), 1587–1606.
Benn, D.I., Cowton, T., Todd, J., Luckman, A., Glacier calving in Greenland. Curr. Clim. Chang. Rep. 3 (2017), 282–290.
van den Berk, J., Drijfhout, S.S., Hazeleger, W., Circulation adjustment in the Arctic and Atlantic in response to Greenland and Antarctic mass loss. Clim. Dyn. 57 (2021), 1689–1707.
Beyer, S., Kleiner, T., Aizinger, V., Rückamp, M., Humbert, A., A confined–unconfined aquifer model for subglacial hydrology and its application to the Northeast Greenland ice stream. Cryosphere 12:12 (2018), 3931–3947.
van den Broeke, M.R., Enderlin, E.M., Howat, I.M., Kuipers Munneke, P., Noël, B.P.Y., van de Berg, W.J., van Meijgaard, E., Wouters, B., On the recent contribution of the Greenland ice sheet to sea level change. Cryosphere 10 (2016), 1933–1946.
Chen, C., Howat, I.M., De la Pena, S., Formation and development of supraglacial lakes in the percolation zone of the Greenland ice sheet. J. Glaciol. 63 (2017), 847–853.
Chen, Z., Chi, Z., Zinglersen, K.B., Tian, Y., Wang, K., Hui, F., Cheng, X., A new image mosaic of Greenland using Landsat-8 OLI images. Sci. Bull. 65 (2020), 522–524.
Christoffersen, P., Bougamont, M., Hubbard, A., Doyle, S.H., Grigsby, S., Pettersson, R., Cascading lake drainage on the Greenland ice sheet triggered by tensile shock and fracture. Nat. Commun., 9, 2018, 1064.
Chu, V., Greenland ice sheet hydrology: a review. Prog. Phys. Geogr. 38 (2014), 19–54.
Chudley, T.R., Christoffersen, P., Doyle, S.H., Bougamont, M., Schoonman, C.M., Hubbard, B., James, M.R., Supraglacial lake drainage at a fast-flowing Greenlandic outlet glacier. Proc. Natl. Acad. Sci. USA 116 (2019), 25468–25477.
Colgan, W., Steffen, K., McLamb, W.S., Abdalati, W., Rajaram, H., Motyka, R., Phillips, T., Anderson, R., An increase in crevasse extent, West Greenland: hydrologic implications. Geophys. Res. Lett. 38 (2011), 113–120.
Datta, R.T., Wouters, B., Supraglacial lake bathymetry automatically derived from ICESat-2 constraining lake depth estimates from multi-source satellite imagery. Cryosphere 15 (2021), 5115–5132.
Dell, R.L., Banwell, A.F., Willis, I.C., Arnold, N.S., Halberstadt, A.R.W., Chudley, T.R., Pritchard, H.D., Supervised classification of slush and ponded water on Antarctic ice shelves using Landsat 8 imagery. J. Glaciol. 68:268 (2021), 401–414.
Diakogiannis, F.I., Waldner, F., Caccetta, Peter, Wu, C., ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data. Isprs J. Photogramm. 162 (2020), 94–114.
Dirscherl, M., Dietz, A.J., Kneisel, C., Kuenzer, C., Automated mapping of Antarctic supraglacial lakes using a machine learning approach. Remote Sens., 12, 2020, 1203.
Dirscherl, M.C., Dietz, A.J., Kuenzer, C., Seasonal evolution of Antarctic supraglacial lakes in 2015–2021 and links to environmental controls. Cryosphere 15 (2021), 5205–5226.
Dow, C.F., Kulessa, B., Rutt, I.C., Tsai, V.C., Pimentel, S., Doyle, S.H., van As, D., Lindbäck, K., Pettersson, R., Jones, G.A., Hubbard, A., Modeling of subglacial hydrological development following rapid supraglacial lake drainage. Case Rep. Med. 120 (2015), 1127–1147.
Fair, Z., Flanner, M., Brunt, K.M., Fricker, H.A., Gardner, A., Using ICESat-2 and operation IceBridge altimetry for supraglacial lake depth retrievals. Cryosphere 14:11 (2020), 4253–4263.
Fettweis, X., Tedesco, M., van den Broeke, M., Ettema, J., Melting trends over the Greenland ice sheet (1958–2009) from spaceborne microwave data and regional climate models. Cryosphere 5 (2011), 359–375.
Fettweis, X., Box, J.E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., Gallée, H., Reconstructions of the 1900-2015 Greenland ice sheet surface mass balance using the regional climate MAR model. Cryosphere 11 (2017), 1015–1033.
Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C.J., Born, A., Box, J.E., Delhasse, A., Fujita, K., Gierz, P., Goelzer, H., Hanna, E., Hashimoto, A., Huybrechts, P., Kapsch, M.-L., King, M.D., Kittel, C., Lang, C., Langen, P.L., Lenaerts, J.T.M., Liston, G.E., Lohmann, G., Mernild, S.H., Mikolajewicz, U., Modali, K., Mottram, R.H., Niwano, M., Noël, B., Ryan, J.C., Smith, A., Streffing, J., Tedesco, M., van de Berg, W.J., van den Broeke, M., van de Wal, R.S.W., van Kampenhout, L., Wilton, D., Wouters, B., Ziemen, F., Zolles, T., GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland ice sheet. Cryosphere 14 (2020), 3935–3958.
Fricker, H.A., Arndt, P., Brunt, K.M., Datta, R.T., Fair, Z., Jasinski, M.F., Kingslake, J., Magruder, L.A., Moussavi, M., Pope, A., Spergel, J.J., Stoll, J.D., Wouters, B., ICESat-2 meltwater depth estimates: application to surface melt on Amery ice shelf, East Antarctica. Geophys. Res. Lett., 48(8), 2021 e2020GL090550.
Gardner, A.S., Moholdt, G., Scambos, T., Fahnstock, M., Ligtenberg, S., Van den Broeke, M., Nilsson, J., Increased West Antarctic and unchanged East Antarctic ice discharge over the last 7 years. Cryosphere 12 (2018), 521–547.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R., Google earth engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202 (2017), 18–27.
Haacker, J., Wouters, B., Fettweis, X., Glissenaar, I.A., Box, J.E., Atmospheric-river-induced foehn events drain glaciers on Novaya Zemlya. Nat. Commun., 15(1), 2024, 7021.
Halberstadt, A.R.W., Gleason, C.J., Moussavi, M.S., Pope, A., Trusel, L.D., DeConto, R.M., Antarctic supraglacial Lake identification using Landsat-8 image classification. Remote Sens., 12, 2020, 1327.
Hanna, E., Huybrechts, P., Steffen, K., Cappelen, J., Huff, R., Shuman, C., Irvine-Fynn, T., Wise, S., Griffiths, M., Increased runoff from melt from the Greenland ice sheet: a response to global warming. J. Clim. 21 (2008), 331–341.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., Thépaut, J.N., The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146 (2020), 1999–2049.
Howat, I.M., Negrete, A., Smith, B.E., The Greenland ice mapping project (GIMP) land classification and surface elevation data sets. Cryosphere 8 (2014), 1509–1518.
Hu, J., Shen, L., Albanie, S., Sun, G., Wu, E., Squeeze-and-excitation networks. IEEE Trans. Pattern Anal. Mach. Intell. 42 (2020), 2011–2023.
Hu, J., Huang, H., Chi, Z., Cheng, X., Wei, Z., Chen, P., Xu, X., Qi, S., Xu, Y., Zheng, Y., Distribution and evolution of Supraglacial Lakes in Greenland during the 2016–2018 melt seasons. Remote Sens., 14, 2022, 55.
Ignéczi, Á., Sole, A.J., Livingstone, S.A., Leeson, A.A., Fettweis, X., Selmes, N., Gourmelen, N., Briggs, K., Northeast sector of the Greenland ice sheet to undergo the greatest inland expansion of supraglacial lakes during the 21st century. Geophys. Res. Lett. 43 (2016), 9729–9738.
Jiang, D., Li, X., Zhang, K., Marinsek, S., Hong, W., Wu, Y., Automatic supraglacial Lake extraction in Greenland using Sentinel-1 SAR images and attention-based U-net. Remote Sens., 14, 2022, 4998.
Kim, Y., Kimball, J.S., Glassy, J., McDonald, K.C., MEaSUREs Polar EASE-Grid 2.0 Daily 6 km Land Freeze. Thaw Status from AMSR-E and AMSR2, Version, 2. 2021.
Lampkin, D.J., Koenig, L., Joseph, C., Box, J.E., Carr, R.J., Lampkin, D.J., Investigating controls on the formation and distribution of wintertime storage of water in supraglacial lakes. Front. Earth Sci., 8, 2020, 370.
Li, R., Liu, W., Yang, L., Sun, S., Hu, W., Zhang, F., Li, W., DeepUNet: a deep fully convolutional network for pixel-Level Sea-land segmentation. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 11 (2017), 3954–3962.
Li, Y., Yang, K., Gao, S., Smith, L.C., Fettweis, X., Li, M., Surface meltwater runoff routing through a coupled supraglacial-proglacial drainage system, Inglefield land, Northwest Greenland. Int. J. Appl. Earth Obs., 106, 2022, 102647.
Liu, W., Chen, X., Ran, J., Liu, L., Wang, Q., Xin, L., Li, G., LaeNet: a novel lightweight multitask CNN for automatically extracting Lake area and shoreline from remote sensing images. Remote Sens., 13, 2021, 56.
Lüthje, M., Pedersen, L.T., Reeh, N., Greuell, W., Modeling the evolution of supraglacial lakes on the West Greenland ice-sheet margin. J. Glaciol. 52 (2006), 608–618.
Miles, K.E., Willis, I.C., Benedek, C.L., Williamson, A.G., Tedesco, M., Toward monitoring surface and subsurface lakes on the Greenland ice sheet using Sentinel-1 SAR and Landsat-8 OLI imagery. Front. Earth Sci., 5, 2017, 58.
Mohajerani, S., Saeedi, P., Cloud-net: an end-to-end cloud detection algorithm for Landsat 8 imagery. Int. Geosci. Remote Sens. Symp. (IGARSS), 2019, 1029–1032.
Moon, T.A., Mankoff, K.D., Fausto, R.S., Fettweis, X., Loomis, B.D., Mote, T.L., Poinar, K., Tedesco, M., Wehrlé, A., Jensen, C.D., Arctic Report Card 2022: Greenland Ice Sheet. 2022, 10.25923/c430-hb50.
Moussavi, M., Pope, A., Halberstadt, A.R.W., Trusel, L.D., Cioffi, L., Abdalat, W., Antarctic supraglacial lake detection using Landsat 8 and Sentinel-2 imagery: towards continental generation of lake volumes. Remote Sens., 12, 2020, 134.
Nienow, P.W., Sole, A.J., Slater, D.A., Cowton, T.R., Recent advances in our understanding of the role of meltwater in the Greenland ice sheet system. Curr. Clim. Chang. Rep. 3 (2017), 330–344.
Otsu, N., A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9 (1979), 62–66.
Ouyang, S., Li, Y., Combining deep semantic segmentation network and graph convolutional neural network for semantic segmentation of remote sensing imagery. Remote Sens., 13, 2021, 119.
Pekel, J.-F., Cottam, A., Gorelick, N., Belward, A.S., High-resolution mapping of global surface water and its long-term changes. Nature 540 (2016), 418–422.
Pi, X., Luo, Q., Feng, L., Xu, Y., Tang, J., Liang, X., Ma, E., Cheng, R., Fensholt, R., Brandt, M., Mapping global lake dynamics reveals the emerging roles of small lakes. Nat. Commun., 13, 2022, 5777.
Pitcher, L.H., Smith, L.C., Supraglacial streams and Rivers. Annu. Rev. Earth Planet. Sci. 47 (2019), 421–452.
Pope, A., Reproducibly estimating and evaluating supraglacial lake depth with Landsat 8 and other multispectral sensors. Earth Space Sci. 3 (2016), 176–188.
Porter, C., Morin, P., Howat, I., Noh, M.-J., Bates, B., Peterman, K., Keesey, S., Schlenk, M., Gardiner, J., Tomko, K., Willis, M., Kelleher, C., Cloutier, M., Husby, E., Foga, S., Nakamura, H., Platson, M., Wethington, Michael, Williamson, C., Bauer, G., Enos, J., Arnold, G., Kramer, W., Becker, P., Doshi, A., D'Souza, C., Cummens, P., Laurier, F., Bojesen, M., ArcticDEM, Version 3, Harvard Dataverse. 2018, 10.7910/DVN/OHHUKH.
Previdi, M., Smith, K.L., Polvani, L.M., Arctic amplification of climate change: a review of underlying mechanisms. Environ. Res. Lett., 16, 2021, 093003.
Ran, J., Vizcaino, M., Ditmar, P., van den Broeke, M.R., Moon, T., Steger, C.R., Enderlin, E.M., Wouters, B., Noël, B., Reijmer, C.H., Klees, R., Zhong, M., Liu, L., Fettweis, X., Seasonal mass variations show timing and magnitude of meltwater storage in the Greenland ice sheet. Cryosphere 12 (2018), 2981–2999.
Ran, J., Ditmar, P., van den Broeke, M.R., Liu, L., Klees, R., Khan, S.A., Moon, T., Li, J., Bevis, M., Zhong, M., Fettweis, X., Liu, J., Noël, B., Shum, C.K., Chen, J., Jiang, L., van Dam, T., Vertical bedrock shifts reveal summer water storage in Greenland ice sheet. Nature 635:8037 (2024), 108–113.
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., Prakash, P., Deep learning and process understanding for data-driven earth system science. Nature 566 (2019), 195–204.
Rignot, E., Mouginot, J., Ice flow in Greenland for the international polar year 2008–2009. Geophys. Res. Lett., 39, 2012, L11501, 10.1029/2012GL051634.
Ronneberger, O., Fischer, P., Brox, T., U-net: convolutional networks for biomedical image segmentation. Lect. Notes Comput. Sci 9351 (2015), 234–241.
Salerno, F., Thakuri, S., D'Agata, C., Smiraglia, C., Manfredi, E.C., Viviano, G., Tartari, G., Glacial lake distribution in the Mount Everest region: uncertainty of measurement and conditions of formation. Glob. Planet. Chang. 92–93 (2012), 30–39.
Sasgen, I., Wouters, B., Gardner, A.S., King, M.D., Tedesco, M., Landerer, F.W., Dahle, C., Save, H., Fettweis, X., Return to rapid ice loss in Greenland and record loss in 2019 detected by the GRACE-FO satellites. Commun. Earth Environ., 1(1), 2020, 8.
Schröder, L., Neckel, N., Zindler, R., Humbert, A., Perennial supraglacial lakes in Northeast Greenland observed by polarimetric SAR. Remote Sens., 12, 2020, 2798.
Selmes, N., Murray, T., James, T.D., Fast draining lakes on the Greenland ice sheet. Geophys. Res. Lett. 38 (2011), 165–176.
Smith, L.C., Yang, K., Pitcher, L.H., Overstreet, B.T., Chu, V.W., Rennermalm, Å.K., Ryan, J.C., Cooper, M.G., Gleason, C.J., Tedesco, M., Jeyaratnam, J., Van As, D., Van den Broeke, M.R., Van De Berg, W.J., Noël, B., Langen, P.L., Cullather, R.I., Zhao, B., Willis, M.J., Behar, A.E., Direct measurements of meltwater runoff on the Greenland ice sheet surface. Proc. Natl. Acad. Sci. USA 114 (2017), E10622–E10631.
Stevens, L.A., Behn, M.D., McGuire, J.J., Das, S.B., Joughin, I., Herring, T., Shean, D.E., King, M.A., Greenland supraglacial lake drainages triggered by hydrologically induced basal slip. Nature 522 (2015), 73–76.
Stokes, C.R., Sanderson, J.E., Miles, B., Jamieson, S.S.R., Leeson, A., Widespread distribution of supraglacial lakes around the margin of the East Antarctic ice sheet. Sci. Rep., 9, 2019, 13823.
Sundal, A.V., Shepherd, A., Nienow, P., Hanna, E., Palmer, S., Huybrechts, P., Evolution of supra-glacial lakes across the Greenland ice sheet. Remote Sens. Environ. 113 (2009), 2164–2171.
Tedesco, M., Lthje, M., Steffen, K., Steiner, N., Fettweis, X., Willis, I., Bayou, N., Banwell, A., Measurement and modeling of ablation of the bottom of supraglacial lakes in western Greenland. Geophys. Res. Lett., 39, 2012, L02502.
Turton, J.V., Hochreuther, P., Reimann, N., Blau, M.T., The distribution and evolution of supraglacial lakes on 79°N glacier (North-Eastern Greenland) and interannual climatic controls. Cryosphere 15 (2021), 3877–3896.
van de Wal, R.S.W., Boot, M., van den Broeke, M.R., Smeets, C.J.P.P., Reijmer, C.H., Donker, J.J.A., Oerlemans, J., Large and rapid melt-induced velocity changes in the ablation zone of the Greenland ice sheet. Science 321 (2008), 111–113.
Wang, M., Chen, Y., Qi, B., Residual UNet with spatial and channel attention for automatic magnetic resonance image segmentation of rectal cancer. Multimed. Tools Appl. 81 (2022), 43821–43835.
Weiss, M., Jacob, F., Duveiller, G., Remote sensing for agricultural applications: a meta-review. Remote Sens. Environ., 236, 2020, 111402.
Williams, J.J., Gourmelen, N., Nienow, P., Dynamic response of the Greenland ice sheet to recent cooling. Sci. Rep., 10(1), 2020, 1647.
Williamson, A.G., Arnold, N.S., Banwell, A.F., Willis, I.C., A fully automated supraglacial lake area and volume tracking (“FAST”) algorithm: development and application using MODIS imagery of West Greenland. Remote Sens. Environ. 196 (2017), 113–133.
Williamson, A.G., Banwell, A.F., Willis, I.C., Arnold, N.S., Dual-satellite (Sentinel-2 and Landsat 8) remote sensing of supraglacial lakes in Greenland. Cryosphere 12 (2018), 3045–3065.
Yang, K., Li, M., Greenland ice sheet surface melt: a review. Sci. Cold Arid Reg. 6 (2014), 99–106.
Yang, K., Smith, L.C., Supraglacial streams on the Greenland ice sheet delineated from combined spectral-shape information in high-resolution satellite imagery. IEEE Geosci. Remote Sens. Lett. 10 (2013), 801–805.
Yang, K., Smith, L.C., Karlstrom, L., Cooper, M.G., Tedesco, M., van As, D., Cheng, X., Chen, Z., Li, M., A new surface meltwater routing model for use on the Greenland ice sheet surface. Cryosphere 12 (2018), 3791–3811.
Yuan, J., Chi, Z., Cheng, X., Zhang, T., Li, T., Chen, Z., Automatic extraction of Supraglacial Lakes in Southwest Greenland during the 2014–2018 melt seasons based on convolutional neural network. Water, 12, 2020, 891.
Zhang, E., Liu, L., Huang, L., Ng, K.S., An automated, generalized, deep-learning-based method for delineating the calving fronts of Greenland glaciers from multi-sensor remote sensing imagery. Remote Sens. Environ., 254, 2021, 112265.
Zhang, G., Bolch, T., Yao, T., Rounce, D.R., Chen, W., Veh, G., King, O., Allen, S.K., Wang, M., Wang, W., Underestimated mass loss from lake-terminating glaciers in the greater Himalaya. Nat. Geosci. 16 (2023), 333–338.
Zhao, S., Hao, G., Zhang, Y., Wang, S., A real-time semantic segmentation method of sheep carcass images based on ICNet. J. Robot. 2021 (2021), 1–12.
Zheng, L., Li, L., Chen, Z., He, Y., Mo, L., Chen, D., Hu, Q., Wang, L., Liang, Q., Cheng, X., Multi-sensor imaging of winter buried lakes in the Greenland ice sheet. Remote Sens. Environ., 295, 2023, 113688.
Zhou, Z., Rahman Siddiquee, M.M., Tajbakhsh, N., Liang, J., Unet++: redesigning skip connections to exploit multiscale features in image segmentation. IEEE Trans. Med. Imaging 39:6 (2019), 1856–1867.
Zwally, H.J., Abdalati, W., Herring, T., Larson, K., Saba, J., Steffen, K., Surface melt-induced acceleration of Greenland ice-sheet flow. Science 297 (2002), 218–222.