Articles | Volume 17, issue 12
https://doi.org/10.5194/amt-17-3765-2024
https://doi.org/10.5194/amt-17-3765-2024
Research article
 | 
25 Jun 2024
Research article |  | 25 Jun 2024

Innovative cloud quantification: deep learning classification and finite-sector clustering for ground-based all-sky imaging

Jingxuan Luo, Yubing Pan, Debin Su, Jinhua Zhong, Lingxiao Wu, Wei Zhao, Xiaoru Hu, Zhengchao Qi, Daren Lu, and Yinan Wang

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Cited articles

Alonso-Montesinos, J.: Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera, Remote Sens.-Basel, 12, 1382, https://doi.org/10.3390/rs12091382, 2020. 
Changhui, Y., Yuan, Y., Minjing, M., and Menglu, Z.: CLOUD DETECTION METHOD BASED ON FEATURE EXTRACTION IN REMOTE SENSING IMAGES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W1, 173–177, https://doi.org/10.5194/isprsarchives-XL-2-W1-173-2013, 2013. 
Chen, B., Xu, X. D., Yang, S., and Zhao, T. L.: Climatological perspectives of air transport from atmospheric boundary layer to tropopause layer over Asian monsoon regions during boreal summer inferred from Lagrangian approach, Atmos. Chem. Phys., 12, 5827–5839, https://doi.org/10.5194/acp-12-5827-2012, 2012. 
Chi, Y., Zhao, C., Yang, Y., Zhao, X., and Yang, J.: Global characteristics of cloud macro-physical properties from active satellite remote sensing, Atmos. Res., 302, 107316, https://doi.org/10.1016/j.atmosres.2024.107316, 2024. 
Dev, S., Lee, Y. H., and Winkler, S.: Color-Based Segmentation of Sky/Cloud Images From Ground-Based Cameras, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.-Basel, 10, 231–242, https://doi.org/10.1109/JSTARS.2016.2558474, 2017. 
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Short summary
Accurate cloud quantification is critical for climate research. We developed a novel computer vision framework using deep neural networks and clustering algorithms for cloud classification and segmentation from ground-based all-sky images. After a full year of observational training, our model achieves over 95 % accuracy on four cloud types. The framework enhances quantitative analysis to support climate research by providing reliable cloud data.
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