Spatiotemporal patterns of street-level solar radiation estimated using Google Street View in a high-density urban environment
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AbstractThis study presents a method for calculating solar irradiance of street canyons using Google Street View (GSV)
images and investigates its spatiotemporal patterns in a high-density urban environment. In this method, GSV
images provide a unique way to characterize the street morphology from which the diurnal solar path and solar
radiation exposure can be estimated in a street canyon. Verifications of our developed method using free-horizon
HKO observations and street-level field measurements show that both the calculated clear-sky and all-sky solar
irradiance of street canyons well capture the diurnal and seasonal cycles. In the high-density urban areas of Hong
Kong, we found that (1) the lowest monthly averaged solar irradiations in winter are 6.6 (December) and 4.6 (February) MJ/m^2/day, and the highest values in summer are 17.3 (July) and 10.8 (June) MJ/m^2/day for clear sky
and all-sky calculations, respectively; (2) The spatial variability of solar irradiation is closely related to sky
view factor (SVF). In summer, the irradiation in a low-rise region (SVF≥0.7) on average is about three times that
in a high-rise region (SVF≤0.3), and they differ by about five times in winter; (3) Street orientation has a
significant impact on the solar radiation received in a high-density street canyon. In general, street canyons with
West-East orientation receive higher solar irradiation during summer and lower during winter compared to those
with South-North orientation. The generated maps of street-level solar irradiation may help researchers investigate
the interactions between solar radiation, human health and urban thermal balance in high-density
urban environments.
Acceptance Date12/10/2018
All Author(s) ListFang-Ying Gong, Zhao-Cheng Zeng, Edward Ng, Leslie K. Norford
Journal nameBuilding and Environment
Year2019
Month1
Day15
Volume Number148
PublisherElsevier
Pages547 - 566
ISSN0360-1323
eISSN1873-684X
LanguagesEnglish-United States
KeywordsSolar radiation, Sky view factor, Street canyon, Google Street View, Deep learning, Hong Kong

Last updated on 2020-15-01 at 03:02