Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer Model
The extensive existence of high-brightness ice and snow underlying surfaces in polar regions presents notable complexities for cloud detection in remote sensing imagery. To elevate the accuracy of cloud detection in polar regions, a novel polar cloud detection algorithm is proposed in this paper. Em...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/21/5221 |
| _version_ | 1827765398744858624 |
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| author | Shaojin Dong Cailan Gong Yong Hu Fuqiang Zheng Zhijie He |
| author_facet | Shaojin Dong Cailan Gong Yong Hu Fuqiang Zheng Zhijie He |
| author_sort | Shaojin Dong |
| collection | DOAJ |
| description | The extensive existence of high-brightness ice and snow underlying surfaces in polar regions presents notable complexities for cloud detection in remote sensing imagery. To elevate the accuracy of cloud detection in polar regions, a novel polar cloud detection algorithm is proposed in this paper. Employing the MOD09 surface reflectance product, we compiled a database of monthly composite surface reflectance in the shortwave infrared bands specific to polar regions. Through the forward simulation of the correlation between the apparent reflectance and surface reflectance across diverse conditions using the 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) radiative transfer model, we established a dynamic cloud detection model for the shortwave infrared channels. In contrast to a machine learning algorithm and the widely used MOD35 cloud product, the algorithm introduced in this study demonstrates enhanced congruence with the authentic cloud distribution within cloud products. It precisely distinguishes between the cloudy and clear-sky pixels, achieving rates surpassing 90% for both, while maintaining an error rate and a missing rate each under 10%. The algorithm yields positive results for cloud detection in polar regions, effectively distinguishing between ice, snow, and clouds. It provides robust support for comprehensive and long-term cloud detection efforts in polar regions. |
| first_indexed | 2024-03-11T11:22:17Z |
| format | Article |
| id | doaj.art-63d23ae0037048938c9730cba6c63c18 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T11:22:17Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-63d23ae0037048938c9730cba6c63c182023-11-10T15:11:26ZengMDPI AGRemote Sensing2072-42922023-11-011521522110.3390/rs15215221Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer ModelShaojin Dong0Cailan Gong1Yong Hu2Fuqiang Zheng3Zhijie He4Key Laboratory of Infrared System Detection and Imaging Technologies, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaKey Laboratory of Infrared System Detection and Imaging Technologies, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaKey Laboratory of Infrared System Detection and Imaging Technologies, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaKey Laboratory of Infrared System Detection and Imaging Technologies, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaZhejiang Lab, Hangzhou 311100, ChinaThe extensive existence of high-brightness ice and snow underlying surfaces in polar regions presents notable complexities for cloud detection in remote sensing imagery. To elevate the accuracy of cloud detection in polar regions, a novel polar cloud detection algorithm is proposed in this paper. Employing the MOD09 surface reflectance product, we compiled a database of monthly composite surface reflectance in the shortwave infrared bands specific to polar regions. Through the forward simulation of the correlation between the apparent reflectance and surface reflectance across diverse conditions using the 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) radiative transfer model, we established a dynamic cloud detection model for the shortwave infrared channels. In contrast to a machine learning algorithm and the widely used MOD35 cloud product, the algorithm introduced in this study demonstrates enhanced congruence with the authentic cloud distribution within cloud products. It precisely distinguishes between the cloudy and clear-sky pixels, achieving rates surpassing 90% for both, while maintaining an error rate and a missing rate each under 10%. The algorithm yields positive results for cloud detection in polar regions, effectively distinguishing between ice, snow, and clouds. It provides robust support for comprehensive and long-term cloud detection efforts in polar regions.https://www.mdpi.com/2072-4292/15/21/5221cloud maskcloud detectionFY-3Dpolar regionsradiative transfer modelSWIR |
| spellingShingle | Shaojin Dong Cailan Gong Yong Hu Fuqiang Zheng Zhijie He Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer Model Remote Sensing cloud mask cloud detection FY-3D polar regions radiative transfer model SWIR |
| title | Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer Model |
| title_full | Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer Model |
| title_fullStr | Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer Model |
| title_full_unstemmed | Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer Model |
| title_short | Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer Model |
| title_sort | polar cloud detection of fengyun 3d medium resolution spectral imager ii imagery based on the radiative transfer model |
| topic | cloud mask cloud detection FY-3D polar regions radiative transfer model SWIR |
| url | https://www.mdpi.com/2072-4292/15/21/5221 |
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