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| Titel |
A method for cloud detection and opacity classification based on ground based sky imagery |
| VerfasserIn |
M. S. Ghonima, B. Urquhart, C. W. Chow, J. E. Shields, A. Cazorla, J. Kleissl |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 5, no. 11 ; Nr. 5, no. 11 (2012-11-27), S.2881-2892 |
| Datensatznummer |
250003181
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| Publikation (Nr.) |
 copernicus.org/amt-5-2881-2012.pdf |
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| Zusammenfassung |
| Digital images of the sky obtained using a total sky imager (TSI) are
classified pixel by pixel into clear sky, optically thin and optically thick
clouds. A new classification algorithm was developed that compares the pixel
red-blue ratio (RBR) to the RBR of a clear sky library (CSL) generated from
images captured on clear days. The difference, rather than the ratio,
between pixel RBR and CSL RBR resulted in more accurate cloud
classification. High correlation between TSI image RBR and aerosol optical
depth (AOD) measured by an AERONET photometer was observed and motivated the
addition of a haze correction factor (HCF) to the classification model to
account for variations in AOD. Thresholds for clear and thick clouds were
chosen based on a training image set and validated with set of manually
annotated images. Misclassifications of clear and thick clouds into the
opposite category were less than 1%. Thin clouds were classified with an
accuracy of 60%. Accurate cloud detection and opacity classification
techniques will improve the accuracy of short-term solar power forecasting. |
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