A Maritime Cloud-Detection Method Using Visible and Near-Infrared Bands over the Yellow Sea and Bohai Sea
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 stu...
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ftdoajarticles:oai:doaj.org/article:5dfc8304d02a45499c1f3b69ec480d4e 2023-05-15T18:18:39+02:00 A Maritime Cloud-Detection Method Using Visible and Near-Infrared Bands over the Yellow Sea and Bohai Sea Yun-Jeong Choi Hyun-Ju Ban Hee-Jeong Han Sungwook Hong 2022-02-01T00:00:00Z https://doi.org/10.3390/rs14030793 https://doaj.org/article/5dfc8304d02a45499c1f3b69ec480d4e EN eng MDPI AG https://www.mdpi.com/2072-4292/14/3/793 https://doaj.org/toc/2072-4292 doi:10.3390/rs14030793 2072-4292 https://doaj.org/article/5dfc8304d02a45499c1f3b69ec480d4e Remote Sensing, Vol 14, Iss 793, p 793 (2022) cloud detection cloud mask NDWI visible near-infrared ocean color Science Q article 2022 ftdoajarticles https://doi.org/10.3390/rs14030793 2022-12-31T04:03:50Z 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 μm, 0.86 μm, 1.38 μm, and 1.61 μm. 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 μm bands. For thin cloud detection, the 1.38 and 1.61 μm 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 μm bands. Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Remote Sensing 14 3 793 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
cloud detection cloud mask NDWI visible near-infrared ocean color Science Q |
spellingShingle |
cloud detection cloud mask NDWI visible near-infrared ocean color Science Q Yun-Jeong Choi Hyun-Ju Ban Hee-Jeong Han Sungwook Hong A Maritime Cloud-Detection Method Using Visible and Near-Infrared Bands over the Yellow Sea and Bohai Sea |
topic_facet |
cloud detection cloud mask NDWI visible near-infrared ocean color Science Q |
description |
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 μm, 0.86 μm, 1.38 μm, and 1.61 μm. 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 μm bands. For thin cloud detection, the 1.38 and 1.61 μm 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 μm bands. |
format |
Article in Journal/Newspaper |
author |
Yun-Jeong Choi Hyun-Ju Ban Hee-Jeong Han Sungwook Hong |
author_facet |
Yun-Jeong Choi Hyun-Ju Ban Hee-Jeong Han Sungwook Hong |
author_sort |
Yun-Jeong Choi |
title |
A Maritime Cloud-Detection Method Using Visible and Near-Infrared Bands over the Yellow Sea and Bohai Sea |
title_short |
A Maritime Cloud-Detection Method Using Visible and Near-Infrared Bands over the Yellow Sea and Bohai Sea |
title_full |
A Maritime Cloud-Detection Method Using Visible and Near-Infrared Bands over the Yellow Sea and Bohai Sea |
title_fullStr |
A Maritime Cloud-Detection Method Using Visible and Near-Infrared Bands over the Yellow Sea and Bohai Sea |
title_full_unstemmed |
A Maritime Cloud-Detection Method Using Visible and Near-Infrared Bands over the Yellow Sea and Bohai Sea |
title_sort |
maritime cloud-detection method using visible and near-infrared bands over the yellow sea and bohai sea |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14030793 https://doaj.org/article/5dfc8304d02a45499c1f3b69ec480d4e |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Remote Sensing, Vol 14, Iss 793, p 793 (2022) |
op_relation |
https://www.mdpi.com/2072-4292/14/3/793 https://doaj.org/toc/2072-4292 doi:10.3390/rs14030793 2072-4292 https://doaj.org/article/5dfc8304d02a45499c1f3b69ec480d4e |
op_doi |
https://doi.org/10.3390/rs14030793 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
3 |
container_start_page |
793 |
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1766195290131398656 |