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| Nighttime Cloud Detection Method in China with Himawari-8 Image |
| Received:November 21, 2018 Revised:June 25, 2019 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7643/ issn.1672-9242.2019.06.002 |
| KeyWord:cloud detection at nighttime Himawari-8 image threshold method CALIPSO |
| Author | Institution |
| AN Ni |
1. National Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences, Beijing , China; 2. School of Resource and Environment, Baotou Teachers’ Collage, Baotou , China |
| SHANG Hua-zhe |
1. National Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences, Beijing , China |
| HU SI Le-tu |
1. National Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences, Beijing , China |
| HAI Quan-sheng |
2. School of Resource and Environment, Baotou Teachers’ Collage, Baotou , China |
| BAO Yu-hai |
3. School of Geographical Science, Inner Mongolia Normal University, Hohhot , China |
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| Abstract: |
| Objective To detect nighttime cloud in China. Methods The threshold method was used to study the nighttime cloud detection in China according to the difference of brightness and temperature between cloud and non-cloud. The difference of topographic elevation in China was obvious, and the difference of surface radiation energy also existed, which affected the accuracy of cloud detection results. Therefore, the cloud detection method based on three elevation steps was proposed. Owing to the lack of visible light at night, the results of cloud detection were qualitatively and quantitatively verified by MODIS cloud products and radar laser CALIPSO data. Results The cloud detection regions were basically consistent with the MOD06 cloud products. The average verification result of CALIPSO radar data in four seasons show that, the average accuracy of extraction clear region was about 77.86%, and the extraction precision of cloud region was 79.67%. The error of extracting cloud region as non-cloud region was about 2.76%, and the error of extracting non-cloud region as cloud area was 12.31%. Conclusion Considered with three elevation steps, the threshold methods have been implemented on cloud detection at nighttime in China by Himawari-8 image data form Japanese geostationary meteorological satellite. |
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