{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T04:47:16Z","timestamp":1772945236195,"version":"3.50.1"},"reference-count":42,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,8,11]],"date-time":"2025-08-11T00:00:00Z","timestamp":1754870400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42325105"],"award-info":[{"award-number":["42325105"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007046","name":"Wuhan University","doi-asserted-by":"publisher","award":["2042022dx0001"],"award-info":[{"award-number":["2042022dx0001"]}],"id":[{"id":"10.13039\/501100007046","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFB3903502"],"award-info":[{"award-number":["2022YFB3903502"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Applied Earth Observation and Geoinformation"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1016\/j.jag.2025.104795","type":"journal-article","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T08:28:02Z","timestamp":1755505682000},"page":"104795","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["CR-CLCD: A cross-regional cropland change detection framework with multi-view domain adaptation for high-resolution satellite imagery"],"prefix":"10.1016","volume":"143","author":[{"given":"Zhendong","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-0493-3954","authenticated-orcid":false,"given":"Xinyu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanfei","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.jag.2025.104795_b0005","first-page":"1","article-title":"Domain adaptation for remote sensing image semantic segmentation: an integrated approach of contrastive learning and adversarial learning","volume":"60","author":"Bai","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0010","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2020.3034752","article-title":"Remote sensing image change detection with transformers","volume":"60","author":"Chen","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0015","first-page":"1","article-title":"Changemamba: Remote sensing change detection with spatio-temporal state space model","volume":"62","author":"Chen","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0020","article-title":"Multitask learning for large-scale semantic change detection","volume":"187","author":"Daudt","year":"2019","journal-title":"Comput. Vis. Image Underst."},{"key":"10.1016\/j.jag.2025.104795_b0025","first-page":"1","article-title":"Changer: Feature interaction is what you need for change detection","volume":"61","author":"Fang","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0030","first-page":"1","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"Ganin","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.jag.2025.104795_b0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2023.113856","article-title":"Cross-city matters: a multimodal remote sensing benchmark dataset for cross-city semantic segmentation using high-resolution domain adaptation networks","volume":"299","author":"Hong","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.jag.2025.104795_b0040","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2023.3297850","article-title":"Stable prototype-guided single-temporal supervised learning for change detection and extraction of building","volume":"61","author":"Hou","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0045","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.isprsjprs.2022.11.013","article-title":"Semi-supervised bidirectional alignment for remote sensing cross-domain scene classification","volume":"195","author":"Huang","year":"2023","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0050","first-page":"2505","article-title":"Cross-domain adaptive clustering for semi-supervised domain adaptation","author":"Li","year":"2021","journal-title":"Proc. IEEE\/CVF Conf. Comput. vis. Pattern Recognit."},{"key":"10.1016\/j.jag.2025.104795_b0055","first-page":"6758","article-title":"Constructing self-motivated pyramid curriculums for cross-domain semantic segmentation: a non-adversarial approach","author":"Lian","year":"2019","journal-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit."},{"key":"10.1016\/j.jag.2025.104795_b0060","first-page":"1","article-title":"Candidate-aware and Change-guided Learning for Remote Sensing Change Detection","volume":"62","author":"Liu","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0065","first-page":"1","article-title":"A memory guided network and a novel dataset for cropland semantic change detection","volume":"62","author":"Liu","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0070","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1016\/j.isprsjprs.2023.07.001","article-title":"An attention-based multiscale transformer network for remote sensing image change detection","volume":"202","author":"Liu","year":"2023","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0075","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1109\/LGRS.2020.2988032","article-title":"Building change detection for remote sensing images using a dual-task constrained deep siamese convolutional network model","volume":"18","author":"Liu","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"10.1016\/j.jag.2025.104795_b0080","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.isprsjprs.2024.04.012","article-title":"Semantic change detection using a hierarchical semantic graph interaction network from high-resolution remote sensing images","volume":"211","author":"Long","year":"2024","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"8","key":"10.1016\/j.jag.2025.104795_b0085","first-page":"3940","article-title":"Category-level adversarial adaptation for semantic segmentation using purified features","volume":"44","author":"Luo","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.jag.2025.104795_b0090","first-page":"1","article-title":"Unsupervised domain adaptation augmented by mutually boosted attention for semantic segmentation of VHR remote sensing images","volume":"61","author":"Ma","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0095","first-page":"1","article-title":"Decomposition-based unsupervised domain adaptation for remote sensing image semantic segmentation","volume":"62","author":"Ma","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0100","doi-asserted-by":"crossref","unstructured":"Mei, K., Zhu, C., Zou, J., Zhang, S., 2020. Instance adaptive self-training for unsupervised domain adaptation. In: Proc. Eur. Conf. Comput. Vis. (ECCV), Glasgow, UK, 23\u201328 August 2020, Part XXVI, pp. 415\u2013430.","DOI":"10.1007\/978-3-030-58574-7_25"},{"key":"10.1016\/j.jag.2025.104795_b0105","first-page":"1","article-title":"SNUNet3+: a full-scale connected Siamese network and a dataset for cultivated land change detection in high-resolution remote-sensing images","volume":"62","author":"Miao","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0110","first-page":"1","article-title":"M-swin: Transformer-based multi-scale feature fusion change detection network within cropland for remote sensing images","volume":"62","author":"Pan","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0115","first-page":"1","article-title":"STENet: a spatial selection and temporal evolution network for change detection in remote sensing images","volume":"62","author":"Pan","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0120","first-page":"3723","article-title":"Maximum classifier discrepancy for unsupervised domain adaptation","author":"Saito","year":"2018","journal-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit."},{"key":"10.1016\/j.jag.2025.104795_b0125","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1016\/j.isprsjprs.2024.05.011","article-title":"Identifying cropland non-agriculturalization with high representational consistency from bi-temporal high-resolution remote sensing images: from benchmark datasets to real-world application","volume":"212","author":"Sun","year":"2024","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0130","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.isprsjprs.2024.04.013","article-title":"The ClearSCD model: Comprehensively leveraging semantics and change relationships for semantic change detection in high spatial resolution remote sensing imagery","volume":"211","author":"Tang","year":"2024","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0135","first-page":"7472","article-title":"Learning to adapt structured output space for semantic segmentation","author":"Tsai","year":"2018","journal-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit."},{"key":"10.1016\/j.jag.2025.104795_b0140","unstructured":"Tzeng, E., Hoffman, J., Zhang, N., Saenko, K., Darrell, T., 2014. Deep domain confusion: Maximizing for domain invariance. arXiv preprint arXiv:1412.3474."},{"key":"10.1016\/j.jag.2025.104795_b0145","first-page":"642","article-title":"Classes matter: a fine-grained adversarial approach to cross-domain semantic segmentation","author":"Wang","year":"2020","journal-title":"Eur. Conf. Comput. vis."},{"key":"10.1016\/j.jag.2025.104795_b0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2022.113058","article-title":"Cross-sensor domain adaptation for high spatial resolution urban land-cover mapping: from airborne to spaceborne imagery","volume":"277","author":"Wang","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.jag.2025.104795_b0155","unstructured":"Wang, J., Zheng, Z., Ma, A., Lu, X., Zhong, Y., 2021. LoveDA: A remote sensing land-cover dataset for domain adaptive semantic segmentation. arXiv preprint arXiv:2110.08733."},{"key":"10.1016\/j.jag.2025.104795_b0160","first-page":"1","article-title":"Change detection based on supervised contrastive learning for high-resolution remote sensing imagery","volume":"61","author":"Wang","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0165","first-page":"1","article-title":"Contrastive scene change representation learning for high-resolution remote sensing scene change detection","volume":"62","author":"Wang","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0170","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.isprsjprs.2021.08.004","article-title":"Appearance based deep domain adaptation for the classification of aerial images","volume":"180","author":"Wittich","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0175","first-page":"1","article-title":"Curriculum-style local-to-global adaptation for cross-domain remote sensing image segmentation","volume":"60","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0180","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/TNNLS.2021.3089332","article-title":"ESCNet: an end-to-end superpixel-enhanced change detection network for very-high-resolution remote sensing images","volume":"34","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.jag.2025.104795_b0185","first-page":"1","article-title":"Relation changes matter: cross-temporal difference transformer for change detection in remote sensing images","volume":"61","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0190","first-page":"1","article-title":"Stagewise unsupervised domain adaptation with adversarial self-training for road segmentation of remote-sensing images","volume":"60","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0195","doi-asserted-by":"crossref","first-page":"7232","DOI":"10.1109\/TGRS.2020.2981051","article-title":"A feature difference convolutional neural network-based change detection method","volume":"58","author":"Zhang","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0200","first-page":"15193","article-title":"Change is everywhere: single-temporal supervised object change detection in remote sensing imagery","author":"Zheng","year":"2021","journal-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit."},{"key":"10.1016\/j.jag.2025.104795_b0205","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.isprsjprs.2021.10.015","article-title":"ChangeMask: deep multi-task encoder-transformer-decoder architecture for semantic change detection","volume":"183","author":"Zheng","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.jag.2025.104795_b0210","first-page":"1","article-title":"Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory","volume":"61","author":"Zhu","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["International Journal of Applied Earth Observation and Geoinformation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S156984322500442X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S156984322500442X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T14:01:10Z","timestamp":1772892070000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/linkinghub.elsevier.com\/retrieve\/pii\/S156984322500442X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":42,"alternative-id":["S156984322500442X"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.jag.2025.104795","relation":{},"ISSN":["1569-8432"],"issn-type":[{"value":"1569-8432","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"CR-CLCD: A cross-regional cropland change detection framework with multi-view domain adaptation for high-resolution satellite imagery","name":"articletitle","label":"Article Title"},{"value":"International Journal of Applied Earth Observation and Geoinformation","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.jag.2025.104795","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"104795"}}