{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T06:52:38Z","timestamp":1773211958158,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T00:00:00Z","timestamp":1726099200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"China National Railway Group Co., Ltd.","award":["P2023S001"],"award-info":[{"award-number":["P2023S001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The density of fog is directly related to visibility and is one of the decision-making criteria for airport flight management and highway traffic management. Estimating fog density based on images and videos has been a popular research topic in recent years. However, the fog density estimated results based on images should be further evaluated and analyzed by combining weather information from other sensors. The data obtained by different sensors often need to be aligned in terms of time because of the difference in acquisition methods. In this paper, we propose a video and a visibility data alignment method based on temporal consistency for data alignment. After data alignment, the fog density estimation results based on images and videos can be analyzed, and the incorrect estimation results can be efficiently detected and corrected. The experimental results show that the new method effectively combines videos and visibility for fog density estimation.<\/jats:p>","DOI":"10.3390\/s24185930","type":"journal-article","created":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T11:04:33Z","timestamp":1726139073000},"page":"5930","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Fog Density Analysis Based on the Alignment of an Airport Video and Visibility Data"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0463-9384","authenticated-orcid":false,"given":"Mingrui","family":"Dai","sequence":"first","affiliation":[{"name":"Institute of Computing Technology, China Academy of Railway Sciences Co., Ltd., Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guohua","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, China Academy of Railway Sciences Co., Ltd., Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weifeng","family":"Shi","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, China Academy of Railway Sciences Co., Ltd., Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1177\/1473871613510429","article-title":"The nested blocks and guidelines model","volume":"14","author":"Meyer","year":"2015","journal-title":"Inf. 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