{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T21:33:37Z","timestamp":1775597617932,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T00:00:00Z","timestamp":1706659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Natural Science Foundation of China","award":["42201492"],"award-info":[{"award-number":["42201492"]}]},{"name":"the National Natural Science Foundation of China","award":["61401509"],"award-info":[{"award-number":["61401509"]}]},{"name":"the National Natural Science Foundation of China","award":["42201492"],"award-info":[{"award-number":["42201492"]}]},{"name":"the National Natural Science Foundation of China","award":["61401509"],"award-info":[{"award-number":["61401509"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Lake ice thickness (LIT) is one of the key climate variables in the lake ice domain, but there are currently large uncertainties in the retrieval of LIT. We present and validate a new LIT retrieval method that utilizes ICESat-2 data to assist CryoSat-2 echo peak selection, aiming to improve the accuracy of LIT retrieval and enable data acquisition without on-site measurements. The method involves screening out similar ICESat-2 and CryoSat-2 tracks based on time and space constraints. It also involves dynamically adjusting the range constraint window of CryoSat-2 waveforms based on the high-precision lake ice surface ellipsoid height obtained from ICESat-2\/ATL06 data. Within this range constraint window, the peak selection strategy is used to determine the scattering interfaces between snow-ice and ice-water. By utilizing the distance between the scattering horizons, the thickness of the lake ice can be determined. We performed the ice thickness retrieval experiment for Baker Lake in winter and verified it against the on-site measurement data. The results showed that the accuracy was about 0.143 m. At the same time, we performed the ice thickness retrieval experiment for Great Bear Lake (GBL), which does not have on-site measurement data, and compared it with the climate change trend of GBL. The results showed that the retrieval results were consistent with the climate change trend of GBL, confirming the validity of the proposed method.<\/jats:p>","DOI":"10.3390\/rs16030546","type":"journal-article","created":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T09:56:34Z","timestamp":1706694994000},"page":"546","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Lake Ice Thickness Retrieval Method with ICESat-2-Assisted CyroSat-2 Echo Peak Selection"],"prefix":"10.3390","volume":"16","author":[{"given":"Hao","family":"Ye","sequence":"first","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Guowang","family":"Jin","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Hongmin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Data and Target Engineering, Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Xin","family":"Xiong","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"},{"name":"Key Laboratory of Smart Earth, 88 Tujing East Road, Beijing 100094, China"}]},{"given":"Jiahao","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Jiajun","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"},{"name":"92556 Troops, Ningbo 315000, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1128","DOI":"10.1002\/grl.50238","article-title":"Quantifying Northern Hemisphere Freshwater Ice: Qualifying Freshwater Ice","volume":"40","author":"Brooks","year":"2013","journal-title":"Geophys. Res. Lett."},{"key":"ref_2","unstructured":"Belward, A., Bourassa, M., Dowell, M., Briggs, S., Dolman, H.A.J., Holmlund, K., Husband, R., Quegan, S., Simmons, A., and Sloyan, B. (2016). The Global Observing System for Climate: Implementation Needs, World Meteorological Organization."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5387","DOI":"10.5194\/tc-15-5387-2021","article-title":"River Ice Phenology and Thickness from Satellite Altimetry: Potential for Ice Bridge Road Operation and Climate Studies","volume":"15","author":"Zakharova","year":"2021","journal-title":"Cryosphere"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Derouin, S. (2020). River Ice Is Disappearing. Eos, 101.","DOI":"10.1029\/2020EO140159"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"112616","DOI":"10.1016\/j.rse.2021.112616","article-title":"50 Years of Lake Ice Research from Active Microwave Remote Sensing: Progress and Prospects","volume":"264","author":"Murfitt","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_6","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."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"869","DOI":"10.5194\/tc-5-869-2011","article-title":"The Fate of Lake Ice in the North American Arctic","volume":"5","author":"Brown","year":"2011","journal-title":"Cryosphere"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4305623","DOI":"10.1109\/TGRS.2022.3197109","article-title":"Investigating the Effect of Lake Ice Properties on Multifrequency Backscatter Using the Snow Microwave Radiative Transfer Model","volume":"60","author":"Murfitt","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1016\/j.scib.2021.10.015","article-title":"The State and Fate of Lake Ice Thickness in the Northern Hemisphere","volume":"67","author":"Li","year":"2022","journal-title":"Sci. Bull."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"5956","DOI":"10.1109\/TGRS.2017.2718533","article-title":"Improvement of Lake Ice Thickness Retrieval from MODIS Satellite Data Using a Thermodynamic Model","volume":"55","author":"Duguay","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.11834\/jrs.20221683","article-title":"Progress and Prospects of Remote Sensing of Lake Ice Thickness","volume":"26","author":"Li","year":"2022","journal-title":"Natl. Remote Sens. Bull."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1631","DOI":"10.1002\/hyp.1026","article-title":"RADARSAT Backscatter Characteristics of Ice Growing on Shallow sub-Arctic Lakes, Churchill, Manitoba, Canada","volume":"16","author":"Duguay","year":"2002","journal-title":"Hydrol. Process."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Vaughan, R.A., and Cracknell, A.P. (1994). Remote Sensing and Global Climate Change, Springer.","DOI":"10.1007\/978-3-642-79287-8"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Murfitt, J.C., Brown, L.C., and Howell, S.E.L. (2018). Estimating Lake Ice Thickness in Central Ontario. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0208519"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"349","DOI":"10.5194\/tc-17-349-2023","article-title":"Ice Thickness and Water Level Estimation for Ice-Covered Lakes with Satellite Altimetry Waveforms and Backscattering Coefficients","volume":"17","author":"Li","year":"2023","journal-title":"Cryosphere"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3708","DOI":"10.1109\/TGRS.2017.2677583","article-title":"Retrievals of Lake Ice Thickness from Great Slave Lake and Great Bear Lake Using CryoSat-2","volume":"55","author":"Beckers","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"111643","DOI":"10.1016\/j.rse.2020.111643","article-title":"Analysis of Sentinel-3 SAR Altimetry Waveform Retracking Algorithms for Deriving Temporally Consistent Water Levels over Ice-Covered Lakes","volume":"239","author":"Shu","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"8143","DOI":"10.1109\/TGRS.2020.3040853","article-title":"Lake Level Change from Satellite Altimetry Over Seasonally Ice-Covered Lakes in the Mackenzie River Basin","volume":"59","author":"Yang","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1109\/LGRS.2010.2044742","article-title":"Sensitivity of AMSR-E Brightness Temperatures to the Seasonal Evolution of Lake Ice Thickness","volume":"7","author":"Kang","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1080\/01490419.2019.1671560","article-title":"Discrimination of Different Sea Ice Types from CryoSat-2 Satellite Data Using an Object-Based Random Forest (ORF)","volume":"43","author":"Shu","year":"2020","journal-title":"Mar. Geod."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Andersen, N.H., Simonsen, S.B., Winstrup, M., Nilsson, J., and S\u00f8rensen, L.S. (2021). Regional Assessments of Surface Ice Elevations from Swath-Processed CryoSat-2 SARIn Data. Remote Sens., 13.","DOI":"10.3390\/rs13112213"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.rse.2016.12.029","article-title":"The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2): Science Requirements, Concept, and Implementation","volume":"190","author":"Markus","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_23","unstructured":"Smith, B., Hancock, D., Harbeck, K., Roberts, L., Neumann, T., Brunt, K., Fricker, H., Gardner, A., Siegfried, M., and Adusumilli, S. (2023). Ice, Cloud, and Land Elevation Satellite (ICESat-2) Project Algorithm Theoretical Basis Document (ATBD) for Land Ice Along-Track Height Product (ATL06), Version 6, National Aeronautics and Space Administration."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"8741","DOI":"10.1029\/96JB00104","article-title":"A Global, Self-consistent, Hierarchical, High-resolution Shoreline Database","volume":"101","author":"Wessel","year":"1996","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"111352","DOI":"10.1016\/j.rse.2019.111352","article-title":"Land Ice Height-Retrieval Algorithm for NASA\u2019s ICESat-2 Photon-Counting Laser Altimeter","volume":"233","author":"Smith","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"113307","DOI":"10.1016\/j.rse.2022.113307","article-title":"Uncertainty of ICESat-2 ATL06- and ATL08-Derived Snow Depths for Glacierized and Vegetated Mountain Regions","volume":"283","author":"Enderlin","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_27","unstructured":"ESA (2021). CryoSat-2 Product Handbook Baseline E 1.0, C2-LI-ACS-ESL-5319, ESA. Technical Report."},{"key":"ref_28","unstructured":"ESA (2021). Cryosat-Baseline-E-Evolutions, C2-LI-ACS-ESL-5319, ESA. Technical Report."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Woodhouse, I.H. (2017). Introduction to Microwave Remote Sensing, CRC Press.","DOI":"10.1201\/9781315272573"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1088\/0022-3727\/20\/12\/013","article-title":"Dielectric Properties of Freshwater Ice at Microwave Frequencies","volume":"20","author":"Matzler","year":"1987","journal-title":"J. Phys. D Appl. Phys."},{"key":"ref_31","first-page":"6501905","article-title":"A Noise-Removal Algorithm Without Input Parameters Based on Quadtree Isolation for Photon-Counting LiDAR","volume":"19","author":"Zhang","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_32","first-page":"181","article-title":"A new wind-wave spectrum model for deep water","volume":"35","author":"Cheng","year":"2006","journal-title":"Indian J. Mar. Sci."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Satake, Y., and Nakamura, K. (2023). Temporal Variations in Ice Thickness of the Shirase Glacier Derived from Cryosat-2\/SIRAL Data. Remote Sens., 15.","DOI":"10.3390\/rs15051205"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/3\/546\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:52:25Z","timestamp":1760104345000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/3\/546"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,31]]},"references-count":33,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2024,2]]}},"alternative-id":["rs16030546"],"URL":"https:\/\/doi.org\/10.3390\/rs16030546","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,31]]}}}