{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T02:05:45Z","timestamp":1780365945823,"version":"3.54.1"},"reference-count":43,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T00:00:00Z","timestamp":1659052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12001504"],"award-info":[{"award-number":["12001504"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022127"],"award-info":[{"award-number":["2022127"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Youth Innovation Promotion Association, CAS","award":["12001504"],"award-info":[{"award-number":["12001504"]}]},{"name":"Youth Innovation Promotion Association, CAS","award":["2022127"],"award-info":[{"award-number":["2022127"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The extensive amount of Satellite Image Time Series (SITS) data brings new opportunities and challenges for land cover analysis. Many supervised machine learning methods have been applied in SITS, but the labeled SITS samples are time- and effort-consuming to acquire. It is necessary to analyze SITS data with an unsupervised learning method. In this paper, we propose a new unsupervised learning method named Deep Temporal Iterative Clustering (DTIC) to deal with SITS data. The proposed method jointly learns a neural network\u2019s parameters and the resulting features\u2019 cluster assignments, which uses a standard clustering algorithm, K-means, to iteratively cluster the features produced by the feature extraction network and then uses the subsequent assignments as supervision to update the network\u2019s weights. We apply DTIC to the unsupervised training of neural networks on both SITS datasets. Experimental results demonstrate that DTIC outperforms the state-of-the-art K-means clustering algorithm, which proves that the proposed approach successfully provides a novel idea for unsupervised training of SITS data.<\/jats:p>","DOI":"10.3390\/rs14153635","type":"journal-article","created":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T04:04:00Z","timestamp":1659326640000},"page":"3635","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Deep Temporal Iterative Clustering for Satellite Image Time Series Land Cover Analysis"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8480-1603","authenticated-orcid":false,"given":"Wenqi","family":"Guo","sequence":"first","affiliation":[{"name":"School of Science, China University of Geosciences (Beijing), Beijing 100083, China"},{"name":"Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3730-9223","authenticated-orcid":false,"given":"Weixiong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4549-3502","authenticated-orcid":false,"given":"Zheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Tang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shichen","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Science, China University of Geosciences (Beijing), Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.isprsjprs.2019.04.015","article-title":"Deep learning in remote sensing applications: A meta-analysis and review","volume":"152","author":"Ma","year":"2019","journal-title":"ISPRS J. 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