{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T15:42:07Z","timestamp":1774366927440,"version":"3.50.1"},"reference-count":113,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,16]],"date-time":"2023-04-16T00:00:00Z","timestamp":1681603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing is a tool of interest for a large variety of applications. It is becoming increasingly more useful with the growing amount of available remote sensing data. However, the large amount of data also leads to a need for improved automated analysis. Deep learning is a natural candidate for solving this need. Change detection in remote sensing is a rapidly evolving area of interest that is relevant for a number of fields. Recent years have seen a large number of publications and progress, even though the challenge is far from solved. This review focuses on deep learning applied to the task of change detection in multispectral remote-sensing images. It provides an overview of open datasets designed for change detection as well as a discussion of selected models developed for this task\u2014including supervised, semi-supervised and unsupervised. Furthermore, the challenges and trends in the field are reviewed, and possible future developments are considered.<\/jats:p>","DOI":"10.3390\/rs15082092","type":"journal-article","created":{"date-parts":[[2023,4,17]],"date-time":"2023-04-17T02:02:59Z","timestamp":1681696979000},"page":"2092","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":82,"title":["A Review of Deep-Learning Methods for Change Detection in Multispectral Remote Sensing Images"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1055-5846","authenticated-orcid":false,"given":"Eleonora Jonasova","family":"Parelius","sequence":"first","affiliation":[{"name":"Norwegian Defence Research Establishment (FFI), NO-2007 Kjeller, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Abdollahi, A., Pradhan, B., Shukla, N., Chakraborty, S., and Alamri, A. 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