{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T15:13:41Z","timestamp":1761664421760,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T00:00:00Z","timestamp":1644278400000},"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>In the terrestrial cryosphere, freeze\/thaw (FT) state transitions play an important and measurable role in climatic, hydrological, ecological, and biogeochemical processes in permafrost landscapes. Active and passive microwave remote sensing has shown a principal capacity to provide effective monitoring of landscape FT dynamics. The study presents a seasonal threshold approach, which examines the timeseries progression of remote sensing measurements relative to signatures acquired during seasonal frozen and thawed reference states. This is used to estimate the FT state from the Sentinel-1 database and applied and evaluated for the region of Eastern Nunavik (Qu\u00e9bec, Canada). An optimization process of the threshold is included. In situ measurements from the meteorological station network were used for the validation process. Overall, acceptable estimation accuracy (&gt;70%) was achieved in most tests; on the best-performing sites, an accuracy higher than 90% was reached. The performance of the seasonal threshold approach over the study region was further discussed with consideration of land cover, spatial heterogeneity, and soil depth. This work is dedicated to providing more accurate data to capture the spatiotemporal heterogeneity of freeze\/thaw transitions and to improving our understanding of related processes in permafrost landscapes.<\/jats:p>","DOI":"10.3390\/rs14030802","type":"journal-article","created":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T23:42:20Z","timestamp":1644363740000},"page":"802","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Retrieving Freeze\/Thaw Cycles Using Sentinel-1 Data in Eastern Nunavik (Qu\u00e9bec, Canada)"],"prefix":"10.3390","volume":"14","author":[{"given":"Yueli","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen (LMU), 80333 Munich, Germany"}]},{"given":"Lingxiao","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen (LMU), 80333 Munich, Germany"},{"name":"School of Geographic Science, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China"}]},{"given":"Monique","family":"Bernier","sequence":"additional","affiliation":[{"name":"Centre Eau, Terre & Environnement, Institut National de la Recherche Scientifique, Quebec City, QC G1K 9A9, Canada"},{"name":"Northern Research Center\/Centre d\u2019\u00c9tudes Nordiques (CEN), Quebec City, QC G1V 0A6, Canada"}]},{"given":"Ralf","family":"Ludwig","sequence":"additional","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen (LMU), 80333 Munich, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Burgess, M.M., Smith, S.L., Brown, J., Romanovsky, V., and Hinkel, K. 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