Parisi, A. V. and Downs, N. and Igoe, D. and Turner, J. (2016) Characterization of cloud cover with a smartphone camera. Instrumentation Science and Technology, 44 (1). pp. 23-34. ISSN 1073-9149
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Abstract
A smartphone sky camera and associated image analysis algorithm has been developed and validated for the determination of the percentage of cloud cover. This provides the total cloud cover and the percentage of thick and thin cloud in the image. The system has been validated and tested using supervised image classification for a range of cloud types and cloud cover ranging from 4% to 98% and solar zenith angles between 6o and 49o. Additionally, this system provides the percentage of total cloud and thick and thin cloud in proximity to the solar disc. The size of the errors is comparable to those associated with the cloud fractions determined with commercial sky camera systems. The benefits of increasing the availability of cloud fraction measurements through the system described include the potential to develop improved local ultraviolet index and weather forecasts and contribute toward better understanding of local trends in cloud patterns that is required to be considered in the generation of solar energy.
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| Item Type: | Article (Commonwealth Reporting Category C) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | Access to published version in accordance with the copyright policy of the publisher. |
| Faculty / Department / School: | Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences |
| Date Deposited: | 03 Jul 2016 23:49 |
| Last Modified: | 20 Mar 2017 00:33 |
| Uncontrolled Keywords: | cloud; smartphone; sky; image; sky camera; cloud fraction |
| Fields of Research : | 02 Physical Sciences > 0299 Other Physical Sciences > 029999 Physical Sciences not elsewhere classified |
| Socio-Economic Objective: | E Expanding Knowledge > 97 Expanding Knowledge > 970102 Expanding Knowledge in the Physical Sciences |
| Identification Number or DOI: | 10.1080/10739149.2015.1055577 |
| URI: | http://eprints.usq.edu.au/id/eprint/28208 |
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