{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:33:01Z","timestamp":1760232781476,"version":"build-2065373602"},"reference-count":58,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T00:00:00Z","timestamp":1669334400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFF0711603","2018YFD0900804","2019YFA0607101","2018YFD1100101","XDA23100102","42277074","42101402","42171421","41971403","BK20210990"],"award-info":[{"award-number":["2022YFF0711603","2018YFD0900804","2019YFA0607101","2018YFD1100101","XDA23100102","42277074","42101402","42171421","41971403","BK20210990"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2022YFF0711603","2018YFD0900804","2019YFA0607101","2018YFD1100101","XDA23100102","42277074","42101402","42171421","41971403","BK20210990"],"award-info":[{"award-number":["2022YFF0711603","2018YFD0900804","2019YFA0607101","2018YFD1100101","XDA23100102","42277074","42101402","42171421","41971403","BK20210990"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022YFF0711603","2018YFD0900804","2019YFA0607101","2018YFD1100101","XDA23100102","42277074","42101402","42171421","41971403","BK20210990"],"award-info":[{"award-number":["2022YFF0711603","2018YFD0900804","2019YFA0607101","2018YFD1100101","XDA23100102","42277074","42101402","42171421","41971403","BK20210990"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["2022YFF0711603","2018YFD0900804","2019YFA0607101","2018YFD1100101","XDA23100102","42277074","42101402","42171421","41971403","BK20210990"],"award-info":[{"award-number":["2022YFF0711603","2018YFD0900804","2019YFA0607101","2018YFD1100101","XDA23100102","42277074","42101402","42171421","41971403","BK20210990"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High-latitude lakes are sensitive indicators of climate change. Monitoring lake dynamics in high-latitude regions (e.g., pan-Arctic regions) is essential to improving our understanding of the impacts of climate change; however, the lack of in situ water level measurements limits comprehensive quantification of the lake hydrologic dynamics in high-latitude regions. Fortunately, the newly launched ICESat-2 laser altimeter can provide finer footprint measurements and denser ground tracks, thus enabling us to measure the water level changes for more lakes than with conventional radar altimeters. This study aims to comprehensively assess the number and frequency of pan-Arctic lakes (&gt;1 km2, north of 60\u00b0N) observable by the ICESat-2 in space and time over the past three years. Further, we analyze the spatial and temporal characteristics of the ICESat-2-based water level observations of these pan-Arctic lakes based on our customized classification of seasonal coverage patterns (wet\/dry season, monthly, and ten-day). We find that the ICESat-2 observed 80,688 pan-Arctic lakes (97% of the total). Among the observed lakes, the ICESat-2 retrieved the seasonal coverage patterns for 40,192 lakes (~50% of observed lakes), accounting for nearly 84% of the area and 95% of the volumetric capacity. Most lakes (99%) have seasonal water-level fluctuation amplitudes within a range of 0\u20131 m. The latitudinal zonality analysis demonstrates that the seasonal change in pan-Arctic lake levels gently fluctuates around 0.5 m between 60\u00b0N and 74\u00b0N and becomes intense (range of level change from 1 m to 2 m) beyond 74\u00b0N. Our results are expected to offer an overall reference for the spatio-temporal coverage of the ICESat-2\u2019s observations of pan-Arctic lakes, which is crucial for comprehending the hydrologic response of high-latitude lakes to ongoing climate change.<\/jats:p>","DOI":"10.3390\/rs14235971","type":"journal-article","created":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T07:01:30Z","timestamp":1669618890000},"page":"5971","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["How Many Pan-Arctic Lakes Are Observed by ICESat-2 in Space and Time?"],"prefix":"10.3390","volume":"14","author":[{"given":"Tan","family":"Chen","sequence":"first","affiliation":[{"name":"Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1060-4636","authenticated-orcid":false,"given":"Chunqiao","family":"Song","sequence":"additional","affiliation":[{"name":"Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"}]},{"given":"Pengfei","family":"Zhan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Jinsong","family":"Ma","sequence":"additional","affiliation":[{"name":"Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"},{"name":"School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,25]]},"reference":[{"key":"ref_1","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. 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