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Remote Sens. 2016, 8(7), 568; doi:10.3390/rs8070568

Estimation of Continuous Urban Sky View Factor from Landsat Data Using Shadow Detection

1
Department of Geography, Environment and Geomatics, University of Ottawa, Ottawa, ON K1N 6N5, Canada
2
Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
*
Author to whom correspondence should be addressed.
Academic Editors: Yuhong He, Qihao Weng, Parth Sarathi Roy and Prasad S. Thenkabail
Received: 29 April 2016 / Revised: 20 June 2016 / Accepted: 28 June 2016 / Published: 6 July 2016
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Abstract

Sky View Factor (SVF, a dimensionless value between 0 and 1 representing obstructed and unobstructed sky, respectively) has an important influence on urban energy balance, and is a key contributor to the Urban Heat Island (UHI) effect experienced by heavily built up regions. Continuous urban SVF maps used in modeling the spatial distribution of UHI can be derived analytically using Lidar data; however, Lidar data are costly to obtain and often lack complete coverage of large cities or metropolitan areas. This study develops and validates a method for estimating continuous urban SVF from globally available Landsat TM data, based on the presence of shadows cast by SVF-reducing urban features. SVF and per-pixel shadow proportion (SP) were first calculated for synthetic grid cities to confirm a logarithmic relationship between the two properties; then Lidar data from four US cities were used to determine an empirical regression relating SP to SVF. Spectral Mixture Analysis was then used to estimate per-pixel SP in a Landsat 5 TM image covering the Greater Vancouver Area, Canada, and the empirical regression was used to calculate SVF from per-pixel SP. The accuracy of the resulting SVF map was validated using independent Lidar-derived SVF data (R2 = 0.78; RMSE = 0.056). View Full-Text
Keywords: Sky View Factor; urban remote sensing; urban heat island; Landsat TM; shadow detection; spectral mixture analysis; shadow proportion; Vancouver Sky View Factor; urban remote sensing; urban heat island; Landsat TM; shadow detection; spectral mixture analysis; shadow proportion; Vancouver
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Hodul, M.; Knudby, A.; Ho, H.C. Estimation of Continuous Urban Sky View Factor from Landsat Data Using Shadow Detection. Remote Sens. 2016, 8, 568.

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