{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T12:10:25Z","timestamp":1770898225455,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,6]],"date-time":"2021-05-06T00:00:00Z","timestamp":1620259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Jining Yan","award":["41801363"],"award-info":[{"award-number":["41801363"]}]},{"name":"Lizhe Wang","award":["U1711266"],"award-info":[{"award-number":["U1711266"]}]},{"name":"Lizhe Wang","award":["41701468"],"award-info":[{"award-number":["41701468"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Nowadays, in the field of data mining, time series data analysis is a very important and challenging subject. This is especially true for time series remote sensing classification. The classification of remote sensing images is an important source of information for land resource planning and management, rational development, and protection. Many experts and scholars have proposed various methods to classify time series data, but when these methods are applied to real remote sensing time series data, there are some deficiencies in classification accuracy. Based on previous experience and the processing methods of time series in other fields, we propose a neural network model based on a self-attention mechanism and time sequence enhancement to classify real remote sensing time series data. The model is mainly divided into five parts: (1) memory feature extraction in subsequence blocks; (2) self-attention layer among blocks; (3) time sequence enhancement; (4) spectral sequence relationship extraction; and (5) a simplified ResNet neural network. The model can simultaneously consider the three characteristics of time series local information, global information, and spectral series relationship information to realize the classification of remote sensing time series. Good experimental results have been obtained by using our model.<\/jats:p>","DOI":"10.3390\/rs13091804","type":"journal-article","created":{"date-parts":[[2021,5,6]],"date-time":"2021-05-06T11:10:27Z","timestamp":1620299427000},"page":"1804","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Remote Sensing Time Series Classification Based on Self-Attention Mechanism and Time Sequence Enhancement"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4685-0196","authenticated-orcid":false,"given":"Jingwei","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jining","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences, Wuhan 430074, China"},{"name":"Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences Wuhan, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2766-0845","authenticated-orcid":false,"given":"Lizhe","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences, Wuhan 430074, China"},{"name":"Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences Wuhan, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liang","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haixu","family":"He","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1007\/s10618-014-0361-2","article-title":"Time series classification with ensembles of elastic distance measures","volume":"29","author":"Lines","year":"2015","journal-title":"Data Min. 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