{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T16:54:50Z","timestamp":1774457690562,"version":"3.50.1"},"reference-count":198,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2023,8,3]],"date-time":"2023-08-03T00:00:00Z","timestamp":1691020800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Beijing Outstanding Young Scientists Program","award":["BJJWZYJH01201910028032"],"award-info":[{"award-number":["BJJWZYJH01201910028032"]}]},{"name":"Beijing Outstanding Young Scientists Program","award":["2018YFC1508902"],"award-info":[{"award-number":["2018YFC1508902"]}]},{"name":"Beijing Outstanding Young Scientists Program","award":["2017YFC0406006"],"award-info":[{"award-number":["2017YFC0406006"]}]},{"name":"Beijing Outstanding Young Scientists Program","award":["2017YFC0406004"],"award-info":[{"award-number":["2017YFC0406004"]}]},{"name":"National Key Research and Development Project","award":["BJJWZYJH01201910028032"],"award-info":[{"award-number":["BJJWZYJH01201910028032"]}]},{"name":"National Key Research and Development Project","award":["2018YFC1508902"],"award-info":[{"award-number":["2018YFC1508902"]}]},{"name":"National Key Research and Development Project","award":["2017YFC0406006"],"award-info":[{"award-number":["2017YFC0406006"]}]},{"name":"National Key Research and Development Project","award":["2017YFC0406004"],"award-info":[{"award-number":["2017YFC0406004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The rapid advancement of remote sensing technology has significantly enhanced the temporal resolution of remote sensing data. Multitemporal remote sensing image classification can extract richer spatiotemporal features. However, this also presents the challenge of mining massive data features. In response to this challenge, deep learning methods have become prevalent in machine learning and have been widely applied in remote sensing due to their ability to handle large datasets. The combination of remote sensing classification and deep learning has become a trend and has developed rapidly in recent years. However, there is a lack of summary and discussion on the research status and trends in multitemporal images. This review retrieved and screened 170 papers and proposed a research framework for this field. It includes retrieval statistics from existing research, preparation of multitemporal datasets, sample acquisition, an overview of typical models, and a discussion of application status. Finally, this paper discusses current problems and puts forward prospects for the future from three directions: adaptability between deep learning models and multitemporal classification, prospects for high-resolution image applications, and large-scale monitoring and model generalization. The aim is to help readers quickly understand the research process and application status of this field.<\/jats:p>","DOI":"10.3390\/rs15153859","type":"journal-article","created":{"date-parts":[[2023,8,3]],"date-time":"2023-08-03T11:13:06Z","timestamp":1691061186000},"page":"3859","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Application of Deep Learning in Multitemporal Remote Sensing Image Classification"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6815-7149","authenticated-orcid":false,"given":"Xinglu","family":"Cheng","sequence":"first","affiliation":[{"name":"Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China"},{"name":"College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China"}]},{"given":"Yonghua","family":"Sun","sequence":"additional","affiliation":[{"name":"Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China"},{"name":"College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China"}]},{"given":"Wangkuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China"},{"name":"College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China"}]},{"given":"Yihan","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China"},{"name":"College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China"}]},{"given":"Xuyue","family":"Cao","sequence":"additional","affiliation":[{"name":"Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China"},{"name":"College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China"}]},{"given":"Yanzhao","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China"},{"name":"College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"29900","DOI":"10.1007\/s11356-020-09091-7","article-title":"Survey on Land Use\/Land Cover (LU\/LC) change analysis in remote sensing and GIS environment: Techniques and Challenges","volume":"27","author":"MohanRajan","year":"2020","journal-title":"Environ. 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