Articles | Volume 5, issue 11
https://doi.org/10.5194/amt-5-2881-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-5-2881-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Nov 2012
Research article |
| 27 Nov 2012
A method for cloud detection and opacity classification based on ground based sky imagery
M. S. Ghonima
Department of Mechanical and Aerospace Engineering, University of California, San Diego, USA
B. Urquhart
Department of Mechanical and Aerospace Engineering, University of California, San Diego, USA
C. W. Chow
Department of Mechanical and Aerospace Engineering, University of California, San Diego, USA
J. E. Shields
Marine Physical Laboratory, Scripps Institution of Oceanography, University of California, San Diego, USA
A. Cazorla
Department of Chemistry and Biochemistry, University of California, San Diego, USA
J. Kleissl
Department of Mechanical and Aerospace Engineering, University of California, San Diego, USA
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- Predicting solar irradiance with all-sky image features via regression C. Fu & H. Cheng https://doi.org/10.1016/j.solener.2013.09.016
- Evaluation of Deep Learning-Based Neural Network Methods for Cloud Detection and Segmentation S. Hensel et al. https://doi.org/10.3390/en14196156
- Diurnal (24 h) cycle and seasonal variability of cloud fraction retrieved from a Whole Sky Imager over a complex terrain in the Western Ghats and comparison with MODIS S. Sunil et al. https://doi.org/10.1016/j.atmosres.2020.105180
- Cloud classification of ground-based infrared images combining manifold and texture features Q. Luo et al. https://doi.org/10.5194/amt-11-5351-2018
- Cloud fraction retrieval and its variability during daytime from ground-based sky imagery over a tropical station in India A. Nikumbh et al. https://doi.org/10.1016/j.jastp.2019.05.002
- Analysis algorithm for sky type and ice halo recognition in all-sky images S. Boyd et al. https://doi.org/10.5194/amt-12-4241-2019
- Towards the intrahour forecasting of direct normal irradiance using sky-imaging data J. Nou et al. https://doi.org/10.1016/j.heliyon.2018.e00598
- Cloudiness retrieved from All-Sky camera and MSG satellite over Reunion Island and Antananarivo Madagascar J. Rivonirina et al. https://doi.org/10.5194/angeo-43-651-2025
- A minutely solar irradiance forecasting method based on real-time sky image-irradiance mapping model F. Wang et al. https://doi.org/10.1016/j.enconman.2020.113075
- ORION software tool for the geometrical calibration of all-sky cameras J. Antuña-Sánchez et al. https://doi.org/10.1371/journal.pone.0265959
- Cloud fraction estimation using random forest classifier on sky images S. Sarangi et al. https://doi.org/10.5194/amt-18-5637-2025
- A novel clear-sky index for color sky imagery used in short-term irradiance forecasting J. Manning & R. Baldick https://doi.org/10.1063/1.5131521
- CloudFU-Net: A Fine-Grained Segmentation Method for Ground-Based Cloud Images Based on an Improved Encoder–Decoder Structure C. Shi et al. https://doi.org/10.1109/TGRS.2024.3389089
- Shadow camera system for the generation of solar irradiance maps P. Kuhn et al. https://doi.org/10.1016/j.solener.2017.05.074
- Detecting clear sky images P. Pawar et al. https://doi.org/10.1016/j.solener.2019.02.069
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