Articles | Volume 15, issue 11
https://doi.org/10.5194/amt-15-3629-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-3629-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jun 2022
Research article |
| 16 Jun 2022
| 16 Jun 2022
An all-sky camera image classification method using cloud cover features
Xiaotong Li
School of Electronics and Information Engineering, Hebei University of
Technology, Tianjin, 300401, China
Baozhu Wang
School of Electronics and Information Engineering, Hebei University of
Technology, Tianjin, 300401, China
Bo Qiu
CORRESPONDING AUTHOR
School of Electronics and Information Engineering, Hebei University of
Technology, Tianjin, 300401, China
Chao Wu
School of Electronics and Information Engineering, Hebei University of
Technology, Tianjin, 300401, China
Viewed
Total article views: 4,435 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Dec 2021)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,907 | 1,426 | 102 | 4,435 | 106 | 122 |
- HTML: 2,907
- PDF: 1,426
- XML: 102
- Total: 4,435
- BibTeX: 106
- EndNote: 122
Total article views: 3,305 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 16 Jun 2022)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,397 | 829 | 79 | 3,305 | 89 | 96 |
- HTML: 2,397
- PDF: 829
- XML: 79
- Total: 3,305
- BibTeX: 89
- EndNote: 96
Total article views: 1,130 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Dec 2021)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 510 | 597 | 23 | 1,130 | 17 | 26 |
- HTML: 510
- PDF: 597
- XML: 23
- Total: 1,130
- BibTeX: 17
- EndNote: 26
Viewed (geographical distribution)
Total article views: 4,435 (including HTML, PDF, and XML)
Thereof 4,406 with geography defined
and 29 with unknown origin.
Total article views: 3,305 (including HTML, PDF, and XML)
Thereof 3,305 with geography defined
and 0 with unknown origin.
Total article views: 1,130 (including HTML, PDF, and XML)
Thereof 1,097 with geography defined
and 33 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
19 citations as recorded by crossref.
- Deep learning-based identification of precipitation clouds from all-sky camera data for observatory safety M. Zhoolideh Haghighi et al.
- Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey Y. Nie et al.
- CAU-Net: An attention-based feature enhancement model for ground-based cloud image segmentation applicable to peri-solar regions J. Zhu et al.
- Day–Night All-Sky Scene Classification with an Attention-Enhanced EfficientNet W. Boonpook et al.
- Hybrid modeling of direct normal irradiance for rooftop photovoltaic systems using multi-feature extraction from cloud images J. Zhu et al.
- Automated Nighttime Cloud Detection Using Keograms When Aurora Is Present A. English et al.
- Automatic Classification of All-Sky Nighttime Cloud Images Based on Machine Learning X. Zhong et al.
- CIE standard general sky model: A review of research landscape, modelling techniques and building energy applications E. Aghimien et al.
- Cloud cover changes over Indian subcontinent using INSAT-3D during the recent decade (2014–2023) S. Verma et al.
- Astronomical site selection for Antarctica with astro-meteorological parameters N. Aksaker et al.
- ASCNet: Research on All-sky Camera Image Classification at the Muztagh-ata Site S. Wang et al.
- HDR Merging of RAW Exposure Series for All-Sky Cameras: A Comparative Study for Circumsolar Radiometry P. Matteschk et al.
- Synergy of Traditional Techniques and Convolutional Neural Networks for Classification of Cloudless Conditions by All-Sky Imagers Š. Mackovjak et al.
- Infrared radiometric image classification and segmentation of cloud structures using a deep-learning framework from ground-based infrared thermal camera observations K. Sommer et al.
- Cloud fraction estimation using random forest classifier on sky images S. Sarangi et al.
- Dual-Branch Attention Photovoltaic Power Forecasting Model Integrating Ground-Based Cloud Image Features L. Zou et al.
- Cloud Identification and Reconstruction from All-sky Camera Images Based on Star Photometry Estimation H. Zhi 支 et al.
- Experimental review and recent advances in deep learning techniques for solar irradiance forecasting and prediction C. Otuka et al.
- Ultra-short-term photovoltaic power prediction based on ground-based cloud images: A review C. Shi et al.
19 citations as recorded by crossref.
- Deep learning-based identification of precipitation clouds from all-sky camera data for observatory safety M. Zhoolideh Haghighi et al.
- Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey Y. Nie et al.
- CAU-Net: An attention-based feature enhancement model for ground-based cloud image segmentation applicable to peri-solar regions J. Zhu et al.
- Day–Night All-Sky Scene Classification with an Attention-Enhanced EfficientNet W. Boonpook et al.
- Hybrid modeling of direct normal irradiance for rooftop photovoltaic systems using multi-feature extraction from cloud images J. Zhu et al.
- Automated Nighttime Cloud Detection Using Keograms When Aurora Is Present A. English et al.
- Automatic Classification of All-Sky Nighttime Cloud Images Based on Machine Learning X. Zhong et al.
- CIE standard general sky model: A review of research landscape, modelling techniques and building energy applications E. Aghimien et al.
- Cloud cover changes over Indian subcontinent using INSAT-3D during the recent decade (2014–2023) S. Verma et al.
- Astronomical site selection for Antarctica with astro-meteorological parameters N. Aksaker et al.
- ASCNet: Research on All-sky Camera Image Classification at the Muztagh-ata Site S. Wang et al.
- HDR Merging of RAW Exposure Series for All-Sky Cameras: A Comparative Study for Circumsolar Radiometry P. Matteschk et al.
- Synergy of Traditional Techniques and Convolutional Neural Networks for Classification of Cloudless Conditions by All-Sky Imagers Š. Mackovjak et al.
- Infrared radiometric image classification and segmentation of cloud structures using a deep-learning framework from ground-based infrared thermal camera observations K. Sommer et al.
- Cloud fraction estimation using random forest classifier on sky images S. Sarangi et al.
- Dual-Branch Attention Photovoltaic Power Forecasting Model Integrating Ground-Based Cloud Image Features L. Zou et al.
- Cloud Identification and Reconstruction from All-sky Camera Images Based on Star Photometry Estimation H. Zhi 支 et al.
- Experimental review and recent advances in deep learning techniques for solar irradiance forecasting and prediction C. Otuka et al.
- Ultra-short-term photovoltaic power prediction based on ground-based cloud images: A review C. Shi et al.
Saved (final revised paper)
Latest update: 02 May 2026
Short summary
The all-sky camera images can reflect the local cloud cover, which is considerable for astronomical observatory site selection. Therefore, the realization of automatic classification of the images is very important. In this paper, three cloud cover features are proposed to classify the images. The proposed method is evaluated on a large dataset, and the method achieves an accuracy of 96.58 % and F1_score of 96.24 %, which greatly improves the efficiency of automatic processing of the images.
The all-sky camera images can reflect the local cloud cover, which is considerable for...
