Discrimination between sea ice and clouds over the Chukchi Sea via China’s ultraviolet–visible-infrared observations
The distribution of Arctic sea ice is an important direct indicator of climate change, and spaceborne optical remote sensing represents one primary technique for sea ice monitoring due to its high spatiotemporal resolution and wide swath coverage. However, this process is often impeded by heavy clou...
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| Format: | Article |
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Elsevier
2025-05-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225001554 |
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| author | Ziyi Suo Yingcheng Lu Lijian Shi Bin Zou Qing Wang Ling Li Jun Tang Weimin Ju Manchun Li |
| author_facet | Ziyi Suo Yingcheng Lu Lijian Shi Bin Zou Qing Wang Ling Li Jun Tang Weimin Ju Manchun Li |
| author_sort | Ziyi Suo |
| collection | DOAJ |
| description | The distribution of Arctic sea ice is an important direct indicator of climate change, and spaceborne optical remote sensing represents one primary technique for sea ice monitoring due to its high spatiotemporal resolution and wide swath coverage. However, this process is often impeded by heavy cloud cover, which shares similar visual and spectral features with sea ice. To address these limitations, this study proposes a novel methodological framework for discriminating between sea ice and different cloud types (cirrus and cumulus) via the ultraviolet–visible-infrared observations from China’s Haiyang-1C/D (HY-1C/D) satellites, and the ultraviolet (UV) data from the onboard Ultraviolet Imager (UVI) are used to study sea ice and clouds over the Chukchi Sea for the first time. The spectral properties are characterized by the top-of-atmosphere (TOA) reflectance (ρTOA) in both UV and visible and near-infrared (VNIR) wavelengths. This indicates that the 355 nm UV band has the optimal sensitivity to the presence of sea ice and clouds, with cirrus clouds composed of high-altitude ice crystals exhibiting extremely high UV reflectivity. A hybrid threshold is subsequently determined to separate sea ice and cloud pixels. In comparison to the MODIS MOD29 sea ice product, which masks cloud pixels with brightness temperature (BT) differences, this algorithm can effectively reduce the misclassification resulting from surface temperature inversions in polar regions. The ice/cloud identification results have been further applied to sea ice concentration (SIC) estimation, and extensive trials of this UV-based ice/cloud detection approach in the Arctic Passages demonstrates its potential applicability. |
| format | Article |
| id | doaj-art-e799a40175d24b14ba6fdc1b0f39171d |
| institution | Kabale University |
| issn | 1569-8432 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj-art-e799a40175d24b14ba6fdc1b0f39171d2025-08-20T03:49:42ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322025-05-0113910450810.1016/j.jag.2025.104508Discrimination between sea ice and clouds over the Chukchi Sea via China’s ultraviolet–visible-infrared observationsZiyi Suo0Yingcheng Lu1Lijian Shi2Bin Zou3Qing Wang4Ling Li5Jun Tang6Weimin Ju7Manchun Li8International Institute for Earth System Science, Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210023, ChinaInternational Institute for Earth System Science, Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210023, China; Corresponding author.Key Laboratory of Space Ocean Remote Sensing and Application, National Satellite Ocean Application Service, Ministry of Natural Resources, Beijing 10081, ChinaKey Laboratory of Space Ocean Remote Sensing and Application, National Satellite Ocean Application Service, Ministry of Natural Resources, Beijing 10081, ChinaPolar and Marine Research Institute, College of Harbour and Coastal Engineering, Jimei University, Xiamen 361021, ChinaInternational Institute for Earth System Science, Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210023, ChinaInternational Institute for Earth System Science, Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210023, ChinaInternational Institute for Earth System Science, Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210023, ChinaInternational Institute for Earth System Science, Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210023, China; School of Geography and Ocean Science, Nanjing University, Nanjing 210023, ChinaThe distribution of Arctic sea ice is an important direct indicator of climate change, and spaceborne optical remote sensing represents one primary technique for sea ice monitoring due to its high spatiotemporal resolution and wide swath coverage. However, this process is often impeded by heavy cloud cover, which shares similar visual and spectral features with sea ice. To address these limitations, this study proposes a novel methodological framework for discriminating between sea ice and different cloud types (cirrus and cumulus) via the ultraviolet–visible-infrared observations from China’s Haiyang-1C/D (HY-1C/D) satellites, and the ultraviolet (UV) data from the onboard Ultraviolet Imager (UVI) are used to study sea ice and clouds over the Chukchi Sea for the first time. The spectral properties are characterized by the top-of-atmosphere (TOA) reflectance (ρTOA) in both UV and visible and near-infrared (VNIR) wavelengths. This indicates that the 355 nm UV band has the optimal sensitivity to the presence of sea ice and clouds, with cirrus clouds composed of high-altitude ice crystals exhibiting extremely high UV reflectivity. A hybrid threshold is subsequently determined to separate sea ice and cloud pixels. In comparison to the MODIS MOD29 sea ice product, which masks cloud pixels with brightness temperature (BT) differences, this algorithm can effectively reduce the misclassification resulting from surface temperature inversions in polar regions. The ice/cloud identification results have been further applied to sea ice concentration (SIC) estimation, and extensive trials of this UV-based ice/cloud detection approach in the Arctic Passages demonstrates its potential applicability.http://www.sciencedirect.com/science/article/pii/S1569843225001554Sea iceCloudChukchi SeaUltraviolet (UV)Haiyang-1C/D (HY-1C/D) |
| spellingShingle | Ziyi Suo Yingcheng Lu Lijian Shi Bin Zou Qing Wang Ling Li Jun Tang Weimin Ju Manchun Li Discrimination between sea ice and clouds over the Chukchi Sea via China’s ultraviolet–visible-infrared observations International Journal of Applied Earth Observations and Geoinformation Sea ice Cloud Chukchi Sea Ultraviolet (UV) Haiyang-1C/D (HY-1C/D) |
| title | Discrimination between sea ice and clouds over the Chukchi Sea via China’s ultraviolet–visible-infrared observations |
| title_full | Discrimination between sea ice and clouds over the Chukchi Sea via China’s ultraviolet–visible-infrared observations |
| title_fullStr | Discrimination between sea ice and clouds over the Chukchi Sea via China’s ultraviolet–visible-infrared observations |
| title_full_unstemmed | Discrimination between sea ice and clouds over the Chukchi Sea via China’s ultraviolet–visible-infrared observations |
| title_short | Discrimination between sea ice and clouds over the Chukchi Sea via China’s ultraviolet–visible-infrared observations |
| title_sort | discrimination between sea ice and clouds over the chukchi sea via china s ultraviolet visible infrared observations |
| topic | Sea ice Cloud Chukchi Sea Ultraviolet (UV) Haiyang-1C/D (HY-1C/D) |
| url | http://www.sciencedirect.com/science/article/pii/S1569843225001554 |
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