{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:31:05Z","timestamp":1771702265529,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2021,7,13]],"date-time":"2021-07-13T00:00:00Z","timestamp":1626134400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The timing of lake ice-off regulates biotic and abiotic processes in Arctic ecosystems. Due to the coarse spatial and temporal resolution of available satellite data, previous studies mainly focused on lake-scale investigations of melting\/freezing, hindering the detection of subtle patterns within heterogeneous landscapes. To fill this knowledge gap, we developed a new approach for fine-resolution mapping of Pan-Arctic lake ice-off phenology. Using the Scene Classification Layer data derived from dense Sentinel-2 time series images, we estimated the pixel-by-pixel ice break-up end date information by seeking the transition time point when the pixel is completely free of ice. Applying this approach on the Google Earth Engine platform, we mapped the spatial distribution of the break-up end date for 45,532 lakes across the entire Arctic (except for Greenland) for the year 2019. The evaluation results suggested that our estimations matched well with both in situ measurements and an existing lake ice phenology product. Based on the generated map, we estimated that the average break-up end time of Pan-Arctic lakes is 172 \u00b1 13.4 (measured in day of year) for the year 2019. The mapped lake ice-off phenology exhibits a latitudinal gradient, with a linear slope of 1.02 days per degree from 55\u00b0N onward. We also demonstrated the importance of lake and landscape characteristics in affecting spring lake ice melting. The proposed approach offers new possibilities for monitoring the seasonal Arctic lake ice freeze\u2013thaw cycle, benefiting the ongoing efforts of combating and adapting to climate change.<\/jats:p>","DOI":"10.3390\/rs13142742","type":"journal-article","created":{"date-parts":[[2021,7,13]],"date-time":"2021-07-13T04:26:06Z","timestamp":1626150366000},"page":"2742","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data"],"prefix":"10.3390","volume":"13","author":[{"given":"Chong","family":"Liu","sequence":"first","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China"}]},{"given":"Huabing","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China"}]},{"given":"Fengming","family":"Hui","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3638-6294","authenticated-orcid":false,"given":"Ziqian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6910-6565","authenticated-orcid":false,"given":"Xiao","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5970","DOI":"10.1080\/01431161.2015.1110263","article-title":"A Refined Mapping of Arctic Lakes Using Landsat Imagery","volume":"36","author":"Paltan","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"317","DOI":"10.5194\/essd-9-317-2017","article-title":"PeRL: A Circum-Arctic Permafrost Region Pond and Lake Database","volume":"9","author":"Muster","year":"2017","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5423","DOI":"10.1038\/s41467-018-07663-3","article-title":"Remote Sensing Quantifies Widespread Abundance of Permafrost Region Disturbances across the Arctic and Subarctic","volume":"9","author":"Nitze","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_4","first-page":"1","article-title":"The Boreal-Arctic Wetland and Lake Dataset (BAWLD)","volume":"2021","author":"Olefeldt","year":"2021","journal-title":"Earth Syst. Sci. Data Discuss."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2111","DOI":"10.1029\/2018GL081584","article-title":"Arctic-Boreal Lake Dynamics Revealed Using CubeSat Imagery","volume":"46","author":"Cooley","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_6","first-page":"1","article-title":"Climate Change and Northern Hemisphere Lake and River Ice Phenology","volume":"2020","author":"Newton","year":"2020","journal-title":"Cryosphere Discuss."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"941","DOI":"10.5194\/tc-10-941-2016","article-title":"Evidence of Recent Changes in the Ice Regime of Lakes in the Canadian High Arctic from Spaceborne Satellite Observations","volume":"10","author":"Surdu","year":"2016","journal-title":"Cryosphere"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.rse.2015.12.014","article-title":"Lake Ice Phenology from AVHRR Data for European Lakes: An Automated Two-Step Extraction Method","volume":"174","author":"Weber","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zhang, S., and Pavelsky, T.M. (2019). Remote Sensing of Lake Ice Phenology across a Range of Lakes Sizes, ME, USA. Remote Sens., 11.","DOI":"10.3390\/rs11141718"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1126\/science.1253119","article-title":"Sunlight Controls Water Column Processing of Carbon in Arctic Fresh Waters","volume":"345","author":"Cory","year":"2014","journal-title":"Science"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"667","DOI":"10.5589\/m12-054","article-title":"Synthetic Aperture Radar (SAR) Backscatter Response from Methane Ebullition Bubbles Trapped by Thermokarst Lake Ice","volume":"38","author":"Engram","year":"2013","journal-title":"Can. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1038\/s41558-020-0762-8","article-title":"Remote Sensing Northern Lake Methane Ebullition","volume":"10","author":"Engram","year":"2020","journal-title":"Nat. Clim. Chang."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"025001","DOI":"10.1088\/1748-9326\/aaf06f","article-title":"Investigating Lake-Area Dynamics across a Permafrost-Thaw Spectrum Using Airborne Electromagnetic Surveys and Remote Sensing Time-Series Data in Yukon Flats, Alaska","volume":"14","author":"Rey","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e2020JD033082","DOI":"10.1029\/2020JD033082","article-title":"Prediction and Analysis of Lake Ice Phenology Dynamics Under Future Climate Scenarios Across the Inner Tibetan Plateau","volume":"125","author":"Ruan","year":"2020","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_15","first-page":"1","article-title":"Recent Changes in Pan-Arctic Sea Ice, Lake Ice, and Snow on\/off Timing","volume":"2021","author":"Dauginis","year":"2021","journal-title":"Cryosphere Discuss."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"529064","DOI":"10.1155\/2012\/529064","article-title":"Modelling Lake Ice Phenology with an Examination of Satellite-Detected Subgrid Cell Variability","volume":"2012","author":"Brown","year":"2012","journal-title":"Adv. Meteorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1038\/s41586-019-1848-1","article-title":"The Past and Future of Global River Ice","volume":"577","author":"Yang","year":"2020","journal-title":"Nature"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Duguay, C.R., Bernier, M., Gauthier, Y., and Kouraev, A. (2015). Remote sensing of lake and river ice. Remote Sensing of the Cryosphere, John Wiley & Sons, Ltd.","DOI":"10.1002\/9781118368909.ch12"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2294","DOI":"10.1007\/s11434-009-0044-3","article-title":"Monitoring the Frozen Duration of Qinghai Lake Using Satellite Passive Microwave Remote Sensing Low Frequency Data","volume":"54","author":"Che","year":"2009","journal-title":"Chin. Sci. Bull."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"235","DOI":"10.5194\/tc-6-235-2012","article-title":"Estimating Ice Phenology on Large Northern Lakes from AMSR-E: Algorithm Development and Application to Great Bear Lake and Great Slave Lake, Canada","volume":"6","author":"Kang","year":"2012","journal-title":"Cryosphere"},{"key":"ref_21","unstructured":"Xiong, C., Lei, Y., and Qiu, Y. (2020). Contrasting Lake Ice Phenology Changes in the Qinghai-Tibet Plateau Revealed by Remote Sensing. IEEE Geosci. Remote Sens. Lett., 1\u20135."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Murfitt, J., and Duguay, C.R. (2020). Assessing the Performance of Methods for Monitoring Ice Phenology of the World\u2019s Largest High Arctic Lake Using High-Density Time Series Analysis of Sentinel-1 Data. Remote Sens., 12.","DOI":"10.3390\/rs12030382"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5388","DOI":"10.1080\/01431161.2019.1579939","article-title":"Recent Trends of Ice Phenology for Eight Large Lakes Using MODIS Products in Northeast China","volume":"40","author":"Yang","year":"2019","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"38449","DOI":"10.1038\/srep38449","article-title":"Arctic Lakes Show Strong Decadal Trend in Earlier Spring Ice-Out","volume":"6","author":"Edwards","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"e2020JG005799","DOI":"10.1029\/2020JG005799","article-title":"Integrating Perspectives to Understand Lake Ice Dynamics in a Changing World","volume":"125","author":"Sharma","year":"2020","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1521","DOI":"10.1016\/j.jglr.2020.08.018","article-title":"Retrieval of Ice\/Water Observations from Synthetic Aperture Radar Imagery for Use in Lake Ice Data Assimilation","volume":"46","author":"Scott","year":"2020","journal-title":"J. Gt. Lakes Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.gloplacha.2011.01.004","article-title":"Lake Ice Phenology of Small Lakes: Impacts of Climate Variability in the Great Lakes Region","volume":"76","author":"Mishra","year":"2011","journal-title":"Glob. Planet. Chang."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.1654-1103.2005.tb02365.x","article-title":"The Circumpolar Arctic Vegetation Map","volume":"16","author":"Walker","year":"2005","journal-title":"J. Veg. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"111297","DOI":"10.1016\/j.rse.2019.111297","article-title":"A Raster Version of the Circumpolar Arctic Vegetation Map (CAVM)","volume":"232","author":"Raynolds","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"13603","DOI":"10.1038\/ncomms13603","article-title":"Estimating the Volume and Age of Water Stored in Global Lakes Using a Geo-Statistical Approach","volume":"7","author":"Messager","year":"2016","journal-title":"Nat. Commun."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.rse.2012.03.020","article-title":"A Decadal Investigation of Supraglacial Lakes in West Greenland Using a Fully Automatic Detection and Tracking Algorithm","volume":"123","author":"Liang","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_32","first-page":"18","article-title":"Google Earth Engine: Planetary-Scale Geospatial Analysis for Everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Big Remote. Sensed Data Tools Appl. Exp."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Louis, J., Pflug, B., Main-Knorn, M., Debaecker, V., Mueller-Wilm, U., Iannone, R.Q., Cadau, E.G., Boccia, V., and Gascon, F. (August, January 28). Sentinel-2 Global Surface Reflectance Level-2a Product Generated with Sen2Cor. Proceedings of the IGARSS 2019\u20142019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8898540"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1429","DOI":"10.1126\/science.1108142","article-title":"Disappearing Arctic Lakes","volume":"308","author":"Smith","year":"2005","journal-title":"Science"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"111792","DOI":"10.1016\/j.rse.2020.111792","article-title":"Mapping and Sampling to Characterize Global Inland Water Dynamics from 1999 to 2018 with Full Landsat Time-Series","volume":"243","author":"Pickens","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.rse.2016.02.016","article-title":"Mapping Paddy Rice Planting Area in Northeastern Asia with Landsat 8 Images, Phenology-Based Algorithm and Google Earth Engine","volume":"185","author":"Dong","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.isprsjprs.2017.07.011","article-title":"A Mangrove Forest Map of China in 2015: Analysis of Time Series Landsat 7\/8 and Sentinel-1A Imagery in Google Earth Engine Cloud Computing Platform","volume":"131","author":"Chen","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Raiyani, K., Gon\u00e7alves, T., Rato, L., Salgueiro, P., and Marques da Silva, J.R. (2021). Sentinel-2 Image Scene Classification: A Comparison between Sen2Cor and a Machine Learning Approach. Remote Sens., 13.","DOI":"10.3390\/rs13020300"},{"key":"ref_39","first-page":"111116","article-title":"Continuous Monitoring of Land Disturbance Based on Landsat Time Series","volume":"238","author":"Zhu","year":"2020","journal-title":"Time Ser. Anal. High Spat. Resolut. Imag."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.4319\/lo.2013.58.6.2013","article-title":"Recent Lake Ice-out Phenology within and among Lake Districts of Alaska, U.S.A","volume":"58","author":"Arp","year":"2013","journal-title":"Limnol. Oceanogr."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"112095","DOI":"10.1016\/j.rse.2020.112095","article-title":"A New Framework to Map Fine Resolution Cropping Intensity across the Globe: Algorithm, Validation, and Implication","volume":"251","author":"Liu","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1002\/hyp.6131","article-title":"Recent Trends in Canadian Lake Ice Cover","volume":"20","author":"Duguay","year":"2006","journal-title":"Hydrol. Process."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"47","DOI":"10.5194\/tc-11-47-2017","article-title":"Satellite Microwave Assessment of Northern Hemisphere Lake Ice Phenology from 2002 to 2015","volume":"11","author":"Du","year":"2017","journal-title":"Cryosphere"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.rse.2019.04.025","article-title":"An Efficient Approach to Capture Continuous Impervious Surface Dynamics Using Spatial-Temporal Rules and Dense Landsat Time Series Stacks","volume":"229","author":"Liu","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1007\/s00027-012-0279-y","article-title":"Physics of Seasonally Ice-Covered Lakes: A Review","volume":"74","author":"Kirillin","year":"2012","journal-title":"Aquat. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.coldregions.2004.06.010","article-title":"Dependence of Lake Ice Covers on Climatic, Geographic and Bathymetric Variables","volume":"40","author":"Williams","year":"2004","journal-title":"Cold Reg. Sci. Technol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1002\/hyp.10996","article-title":"Effects of Changing Climate on Ice Cover in Three Morphometrically Different Lakes","volume":"31","author":"Magee","year":"2017","journal-title":"Hydrol. Process."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1002\/hyp.7165","article-title":"River-Ice Hydrology in a Shrinking Cryosphere","volume":"23","author":"Beltaos","year":"2009","journal-title":"Hydrol. Process."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Cooley, S.W., Smith, L.C., Stepan, L., and Mascaro, J. (2017). Tracking Dynamic Northern Surface Water Changes with High-Frequency Planet CubeSat Imagery. Remote Sens., 9.","DOI":"10.3390\/rs9121306"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1038\/s41558-018-0393-5","article-title":"Widespread loss of lake ice around the Northern Hemisphere in a warming world","volume":"9","author":"Sharma","year":"2019","journal-title":"Nat. Clim. Chang."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2742\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:29:35Z","timestamp":1760164175000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2742"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,13]]},"references-count":50,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["rs13142742"],"URL":"https:\/\/doi.org\/10.3390\/rs13142742","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,13]]}}}