A study of the parametric method of sky view factor on complex underlying surface in urban area: A case study of national sport stadium area in Beijing

doi:10.6046/gtzyyg.2019.03.04

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Abstract

Sky view factor (SVF) is a numerical value that describes the three-dimensional characteristics of the city, and hence it is widely used in urban heat island effect, urban energy balance and some other fields. In this study, taking the national sport stadium area as the study area, the authors calculated the SVFs based on the digital surface model (DSM) in the urban areas. Furthermore, fisheye photos were used to extract the in-situ SVFs. Finally, the authors compared and analyzed the results between these two methods. The main conclusions are as follows: ①The SVF value calculated based on the DSM is affected by the search radius and the search direction number. SVFs are decreasing with the increasing of the search radius and the search direction number; ②Specifically, when the search direction is 32 and the search radius is 80 pixels, the value of RMSE is 0.064 (noting that it is the lowest value). The SVF values calculated using the DSM are most similar to those calculated using fisheye photos; ③A certain correlation is observed between the SVF values calculated using the fisheye photos and those calculated based on the DSM, indicating the feasibility of using DSM to calculate the SVF in large urban areas.

Keywords SVF digital surface model fisheye photos urban areas

TP79

Corresponding Authors: Deyong HU E-mail: deyonghu@cnu.edu.cn

Issue Date: 30 August 2019

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	Xin DUAN
	Deyong HU
	Shisong CAO
	Chen YU
	Yani ZHANG

Cite this article:

Xin DUAN,Deyong HU,Shisong CAO, et al. A study of the parametric method of sky view factor on complex underlying surface in urban area: A case study of national sport stadium area in Beijing[J]. Remote Sensing for Land & Resources, 2019, 31(3): 29-35.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2019.03.04 OR https://www.gtzyyg.com/EN/Y2019/V31/I3/29

Fig.1 Overview of the study area

Fig.2 Fisheye photos at sampling points

Fig.3 Schematic diagram of solid angle

Fig.4 Technological workflow

Fig.5 Calculated SVF values when the number of search directions is 32 with the different search radii

Fig.6 SVF values when search radius is 50 pixels

Tab.1 Calculation results of the SVF of sampling points

Fig.7 Comparison of SVF values of two methods

Fig.8 Linear regression fitting of two methods with different radii

Fig.9 Trend of RMSE with different search radii and number of search directions

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