Abstract
This work describes the development of a simple method of field estimating the sky cloud coverage percentage for several applications at the Brazilian Antarctic Station, Ferraz (62°05′S, 58°23.5′W). The database of this method was acquired by a digital color camera in the visible range of the spectrum. A new algorithm was developed to classify each pixel according to a criteria decision process. The information on the pixel contamination by clouds was obtained from the saturation component of the intensity, hue, and saturation space (IHS). For simplicity, the images were acquired with a limited field of view of 36° pointing to the camera’s zenith to prevent direct sunlight from reaching the internal charge-coupled device (CCD) on the camera. For a priori–classified clear-sky images, the accuracy of the method was superior to 94%. For overcast-sky conditions, the corresponding accuracy was larger than 99%.
A comparison test was performed with two human observers and our method. The results for the 29 images collected for several time of days during 50 days in 1999 summer were compared to visual observations of these same digital images by two trained field meteorologists. Correlation coefficients between human observers and the automatic method ranged from 0.84 for clear-sky conditions, and the lowest was 0.09 for undefined-sky conditions.
Daylighting design with lightscoop skylights: Towards an optimization of proportion and spacing under overcast sky conditions