{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T15:33:45Z","timestamp":1776353625922,"version":"3.51.2"},"reference-count":64,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Convention Industrielle de Formation par la REcherche","award":["2019\/1810"],"award-info":[{"award-number":["2019\/1810"]}]},{"name":"French National Association of Research and Technology"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/jstars.2023.3263755","type":"journal-article","created":{"date-parts":[[2023,3,31]],"date-time":"2023-03-31T17:43:16Z","timestamp":1680284596000},"page":"3645-3675","source":"Crossref","is-referenced-by-count":24,"title":["Temporal-Domain Adaptation for Satellite Image Time-Series Land-Cover Mapping With Adversarial Learning and Spatially Aware Self-Training"],"prefix":"10.1109","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-8651-2183","authenticated-orcid":false,"given":"Emmanuel","family":"Capliez","sequence":"first","affiliation":[{"name":"INRAE, UMR TETIS, University of Montpellier, Montpellier, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8736-3132","authenticated-orcid":false,"given":"Dino","family":"Ienco","sequence":"additional","affiliation":[{"name":"INRAE, UMR TETIS, University of Montpellier, Montpellier, France"}]},{"given":"Raffaele","family":"Gaetano","sequence":"additional","affiliation":[{"name":"CIRAD, UMR TETIS, University of Montpellier, Montpellier, France"}]},{"given":"Nicolas","family":"Baghdadi","sequence":"additional","affiliation":[{"name":"INRAE, UMR TETIS, University of Montpellier, Montpellier, France"}]},{"given":"Adrien Hadj","family":"Salah","sequence":"additional","affiliation":[{"name":"Airbus Defence and Space, Toulouse, France"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2015.10.004"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/rs10081221"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3390\/rs11050523"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2012.01.010"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2017.05.013"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2016.03.008"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3390\/rs9010095"},{"issue":"19","key":"ref8","article-title":"DeepForest: Novel deep learning models for land use and land cover classification using multi-temporal and -modal sentinel data of the amazon basin","volume-title":"Remote Sens.","volume":"14","author":"Cherif","year":"2022"},{"issue":"11","key":"ref9","article-title":"Fusion approaches for land cover map production using high resolution image time series without reference data of the corresponding period","volume-title":"Remote Sens.","volume":"9","author":"Tardy","year":"2017"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.3390\/rs11091047"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2022.04.018"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3400066"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2945942"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3018879"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.3004263"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2616585"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2021.3119191"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/rs11171986"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00483"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/rs11192305"},{"key":"ref21","first-page":"11","article-title":"Combining sentinel-1 and sentinel-2 satellite image time series for land cover mapping via a multi-source deep learning architecture","volume-title":"ISPRS J. Photogramm. Remote Sens.","volume":"158","author":"Ienco","year":"2019"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2017.2728698"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.193"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2018.2794581"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2018.11.032"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01234"},{"key":"ref27","article-title":"Self-training: A survey","author":"Amini","year":"2022"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-019-05855-6"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/279943.279962"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.186"},{"key":"ref31","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. 31st Int. Conf. Neural Inf. Process. Syst.","author":"Tarvainen","year":"2017"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2014.2360833"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3390\/rs12010159"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2021.3114611"},{"key":"ref35","first-page":"596","article-title":"FixMatch: Simplifying semi-supervised learning with consistency and confidence","volume-title":"Proc. 34th Int. Conf. Neural Inf. Process. Syst.","author":"Sohn","year":"2020"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86383-8_10"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2020.3004555"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6247911"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.5555\/2946645.2946704"},{"key":"ref41","first-page":"1647","article-title":"Conditional adversarial domain adaptation","volume-title":"Proc. 32nd Int. Conf. Neural Inf. Process. Syst.","author":"Long","year":"2018"},{"key":"ref42","first-page":"7404","article-title":"Bridging theory and algorithm for domain adaptation","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"97","author":"Zhang","year":"2019"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5757"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2016.2548504"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3140108"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2022.113058"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00329"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.3390\/rs13132564"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01239"},{"key":"ref50","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. Workshop Challenges Representation Learn.","volume":"3","author":"Lee","year":"2013"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58526-6_35"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.3390\/rs70302668"},{"key":"ref53","article-title":"iota2-a25386","author":"Inglada","year":"2016"},{"key":"ref54","doi-asserted-by":"crossref","DOI":"10.5194\/essd-2021-125","article-title":"Harmonized in situ JECAM datasets for agricultural land use mapping and monitoring in tropical countries","author":"Jolivot","year":"2021"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2016.01.011"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2021.3136100"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-05972-1"},{"key":"ref58","article-title":"Revisiting batch normalization for practical domain adaptation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Li","year":"2017"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045167"},{"key":"ref60","article-title":"ADAPT: Awesome domain adaptation python toolbox","author":"de Mathelin","year":"2021"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01228-1_19"},{"key":"ref62","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6692"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.09.011"}],"container-title":["IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4609443\/9973430\/10089508.pdf?arnumber=10089508","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,3]],"date-time":"2024-03-03T10:59:32Z","timestamp":1709463572000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10089508\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":64,"URL":"https:\/\/doi.org\/10.1109\/jstars.2023.3263755","relation":{},"ISSN":["1939-1404","2151-1535"],"issn-type":[{"value":"1939-1404","type":"print"},{"value":"2151-1535","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}