Cloud segmentation property extraction from total sky image repositories using Python

Igoe, Damien P. and Parisi, Alfio V. and Downs, Nathan J. (2019) Cloud segmentation property extraction from total sky image repositories using Python. Instrumentation Science and Technology, 47 (5). pp. 522-534. ISSN 1073-9149

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Abstract

Acquiring the reflectance, radiance and related structural cloud properties from repositories of historical sky images can be a challenging and a computationally intensive task, especially when performed manually or by means of non-automated approaches. In this paper, a quick and efficient, self-adaptive Python tool for the acquisition and analysis of cloud segmentation properties that is applicable to images from all-sky image repositories is presented and a case study demonstrating its usage and the overall efficacy of the technique is demonstrated. The proposed Python tool aims to build a new data extraction technique and to improve the accessibility of data to future researchers, utilizing the freely available libraries in the Python programming language with the ability to be translated into other programming languages. After development and testing of the Python tool in determining cloud and whole sky segmentation properties, over 42,000 sky images were analysed in a relatively short time of just under 40 minutes, with an average execution time of about 0.06 seconds to complete each image analysis.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Submitted version made available in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sept 2019 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sept 2019 -)
Date Deposited: 26 Aug 2019 03:09
Last Modified: 26 Sep 2019 02:27
Uncontrolled Keywords: atmospheric composition analysis; sky imagers; Python; cloud cover; UV
Fields of Research : 04 Earth Sciences > 0401 Atmospheric Sciences > 040199 Atmospheric Sciences not elsewhere classified
05 Environmental Sciences > 0599 Other Environmental Sciences > 059999 Environmental Sciences not elsewhere classified
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: 10.1080/10739149.2019.1603996
URI: http://eprints.usq.edu.au/id/eprint/36585

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