{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T16:45:01Z","timestamp":1768841101762,"version":"3.49.0"},"reference-count":48,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T00:00:00Z","timestamp":1644278400000},"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>Accurate cloud-masking procedures to distinguish cloud-free pixels from cloudy pixels are essential for optical satellite remote sensing. Many studies on satellite-based cloud-detection have been performed using the spectral characteristics of clouds in terms of reflectance and temperature. This study proposes a cloud-detection method using reflectance in four bands: 0.56 \u03bcm, 0.86 \u03bcm, 1.38 \u03bcm, and 1.61 \u03bcm. Methodologically, we present a conversion relationship between the normalized difference water index (NDWI) and the green band in the visible spectrum for thick cloud detection using moderate-resolution imaging spectroradiometer (MODIS) observations. NDWI consists of reflectance at the 0.56 and 0.86 \u03bcm bands. For thin cloud detection, the 1.38 and 1.61 \u03bcm bands were applied with empirically determined threshold values. Case study analyses for the four seasons from 2000 to 2019 were performed for the sea surface area of the Yellow Sea and Bohai Sea. In the case studies, the comparison of the proposed cloud-detection method with the MODIS cloud mask (CM) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation data indicated a probability of detection of 0.933, a false-alarm ratio of 0.086, and a Heidke Skill Score of 0.753. Our method demonstrated an additional important benefit in distinguishing clouds from sea ice or yellow dust, compared to the MODIS CM products, which usually misidentify the latter as clouds. Consequently, our cloud-detection method could be applied to a variety of low-orbit and geostationary satellites with 0.56, 0.86, 1.38, and 1.61 \u03bcm bands.<\/jats:p>","DOI":"10.3390\/rs14030793","type":"journal-article","created":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T23:42:20Z","timestamp":1644363740000},"page":"793","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Maritime Cloud-Detection Method Using Visible and Near-Infrared Bands over the Yellow Sea and Bohai Sea"],"prefix":"10.3390","volume":"14","author":[{"given":"Yun-Jeong","family":"Choi","sequence":"first","affiliation":[{"name":"Department of Environment, Energy and Geoinfomatics, Sejong University, Seoul 05006, Korea"}]},{"given":"Hyun-Ju","family":"Ban","sequence":"additional","affiliation":[{"name":"Department of Environment, Energy and Geoinfomatics, Sejong University, Seoul 05006, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1666-2060","authenticated-orcid":false,"given":"Hee-Jeong","family":"Han","sequence":"additional","affiliation":[{"name":"Korea Ocean Satellite Center, Korea Institute of Ocean Science and Technology, Busan 49111, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5518-9478","authenticated-orcid":false,"given":"Sungwook","family":"Hong","sequence":"additional","affiliation":[{"name":"Department of Environment, Energy and Geoinfomatics, Sejong University, Seoul 05006, Korea"},{"name":"DeepThoTh, Co., Ltd., Seoul 05006, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/0273-1177(94)90358-1","article-title":"AVHRR clear-sky radiation data sets at NOAA\/NESDIS","volume":"14","author":"Stowe","year":"1994","journal-title":"Adv. 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