{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:43:22Z","timestamp":1760147002351,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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>Research of seismic infrared remote sensing has been undertaken for several decades, but there is no stable and effective earthquake prediction method. A new algorithm combining the long short-term memory and the density-based spatial clustering of applications with noise models is proposed to extract the anomalies from the multichannel infrared remote sensing images of the Fengyun-4 satellites. A statistical analysis is used to validate the correlation between the anomalies and earthquakes. The results show that the correlation rate is 64.29%, the hit rate is 68.75%, and the probability gain is about 1.91. In the Madoi and YangBi earthquake cases, the infrared anomaly detected in this paper is correlated with the TEC anomaly found in the previous research. This indicates that it is feasible to combine multi-source data to improve the accuracy of earthquake prediction in future studies.<\/jats:p>","DOI":"10.3390\/rs15010259","type":"journal-article","created":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T03:00:59Z","timestamp":1672628459000},"page":"259","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Pre-Seismic Anomaly Detection from Multichannel Infrared Images of FY-4A Satellite"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1801-5134","authenticated-orcid":false,"given":"Yingbo","family":"Yue","sequence":"first","affiliation":[{"name":"Key Laboratory of Infrared System Detection and Imaging Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5829-9637","authenticated-orcid":false,"given":"Fuchun","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Infrared System Detection and Imaging Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guilin","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Infrared System Detection and Imaging Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"29001","DOI":"10.1209\/0295-5075\/132\/29001","article-title":"Self-organized criticality and earthquake predictability: A long-standing question in the light of natural time analysis","volume":"132","author":"Varotsos","year":"2020","journal-title":"EPL (Europhys. 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