{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T21:07:13Z","timestamp":1784754433196,"version":"3.55.0"},"reference-count":40,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,11]],"date-time":"2024-05-11T00:00:00Z","timestamp":1715385600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42205146"],"award-info":[{"award-number":["42205146"]}]},{"name":"National Natural Science Foundation of China","award":["2022YFF0711703"],"award-info":[{"award-number":["2022YFF0711703"]}]},{"name":"National Natural Science Foundation of China","award":["ZKBB202201"],"award-info":[{"award-number":["ZKBB202201"]}]},{"name":"National Key Research and Development Program of China","award":["42205146"],"award-info":[{"award-number":["42205146"]}]},{"name":"National Key Research and Development Program of China","award":["2022YFF0711703"],"award-info":[{"award-number":["2022YFF0711703"]}]},{"name":"National Key Research and Development Program of China","award":["ZKBB202201"],"award-info":[{"award-number":["ZKBB202201"]}]},{"name":"Zhongke Bengbu Technology Transfer Center Project","award":["42205146"],"award-info":[{"award-number":["42205146"]}]},{"name":"Zhongke Bengbu Technology Transfer Center Project","award":["2022YFF0711703"],"award-info":[{"award-number":["2022YFF0711703"]}]},{"name":"Zhongke Bengbu Technology Transfer Center Project","award":["ZKBB202201"],"award-info":[{"award-number":["ZKBB202201"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Landslide disasters have garnered significant attention due to their extensive devastating impact, leading to a growing emphasis on the prompt and precise identification and detection of landslides as a prominent area of research. Previous research has primarily relied on human\u2013computer interactions and visual interpretation from remote sensing to identify landslides. However, these methods are time-consuming, labor-intensive, subjective, and have a low level of accuracy in extracting data. An essential task in deep learning, semantic segmentation, has been crucial to automated remote sensing image recognition tasks because of its end-to-end pixel-level classification capability. In this study, to mitigate the disadvantages of existing landslide detection methods, we propose a multiscale attention segment network (MsASNet) that acquires different scales of remote sensing image features, designs an encoder\u2013decoder structure to strengthen the landslide boundary, and combines the channel attention mechanism to strengthen the feature extraction capability. The MsASNet model exhibited an average accuracy of 95.13% on the test set from Bijie\u2019s landslide dataset, a mean accuracy of 91.45% on the test set from Chongqing\u2019s landslide dataset, and a mean accuracy of 90.17% on the test set from Tianshui\u2018s landslide dataset, signifying its ability to extract landslide information efficiently and accurately in real time. Our proposed model may be used in efforts toward the prevention and control of geological disasters.<\/jats:p>","DOI":"10.3390\/rs16101712","type":"journal-article","created":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T08:33:03Z","timestamp":1715589183000},"page":"1712","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["A Multiscale Attention Segment Network-Based Semantic Segmentation Model for Landslide Remote Sensing Images"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-3950-9015","authenticated-orcid":false,"given":"Nan","family":"Zhou","sequence":"first","affiliation":[{"name":"Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"},{"name":"University of Science and Technology of China, Hefei 230026, China"},{"name":"Key Laboratory of General Optical Calibration and Characterization Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin","family":"Hong","sequence":"additional","affiliation":[{"name":"Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"},{"name":"University of Science and Technology of China, Hefei 230026, China"},{"name":"Key Laboratory of General Optical Calibration and Characterization Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenyu","family":"Cui","sequence":"additional","affiliation":[{"name":"Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"},{"name":"Key Laboratory of General Optical Calibration and Characterization Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shichao","family":"Wu","sequence":"additional","affiliation":[{"name":"Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"},{"name":"Key Laboratory of General Optical Calibration and Characterization Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5938-4729","authenticated-orcid":false,"given":"Ziheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1007\/s10346-024-02213-z","article-title":"A small landslide induced a large disaster prior to the heavy rainy season in Jinkouhe, Sichuan, China: Characteristics, mechanism, and lessons","volume":"21","author":"Hou","year":"2024","journal-title":"Landslides"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1038\/s43017-022-00373-x","article-title":"Landslide detection, monitoring and prediction with remote-sensing techniques","volume":"4","author":"Casagli","year":"2023","journal-title":"Nat. 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