Editorial Type:
Article
Article Type:
Research Article

Real-Time Sky-View Factor Calculation and Approximation

L. Chapman Entice Technology Ltd., School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom

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J. E. Thornes Entice Technology Ltd., School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom

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Print Publication:
01 May 2004
DOI:
https://doi.org/10.1175/1520-0426(2004)021<0730:RSFCAA>2.0.CO;2
Page(s):
730–741
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Abstract

Previously, the acquisition of sky-view factor data for climate studies has been time consuming and dependent on postprocessing. However, advances in technology now mean that techniques using fish-eye imagery can be algorithmically processed in real time to provide an instant calculation of the sky-view factor. Although data collection is often limited due to the need to survey under homogenous overcast skies, vast datasets can now be rapidly assembled for the training of proxy “all weather” techniques. An artificial neural network is used to estimate the sky-view factor using raw global positioning system (GPS) data and is shown to explain over 69% of the variation of the sky-view factor in urban areas.

Corresponding author address: Dr. L. Chapman, Entice Technology Ltd., School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom. Email: l.chapman@bham.ac.uk

Abstract

Previously, the acquisition of sky-view factor data for climate studies has been time consuming and dependent on postprocessing. However, advances in technology now mean that techniques using fish-eye imagery can be algorithmically processed in real time to provide an instant calculation of the sky-view factor. Although data collection is often limited due to the need to survey under homogenous overcast skies, vast datasets can now be rapidly assembled for the training of proxy “all weather” techniques. An artificial neural network is used to estimate the sky-view factor using raw global positioning system (GPS) data and is shown to explain over 69% of the variation of the sky-view factor in urban areas.

Corresponding author address: Dr. L. Chapman, Entice Technology Ltd., School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom. Email: l.chapman@bham.ac.uk

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Journal of Atmospheric and Oceanic Technology

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