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国土资源遥感  2019, Vol. 31 Issue (3): 29-35    DOI: 10.6046/gtzyyg.2019.03.04
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
城区复杂下垫面天空视域因子参数化方法——以北京鸟巢周边地区为例
段欣1,2, 胡德勇1,2(), 曹诗颂1,2, 于琛1,2, 张亚妮1,2
1. 首都师范大学资源环境与旅游学院,北京 100048
2. 资源环境与地理信息系统北京市重点实验室,北京 100048
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
Xin DUAN1,2, Deyong HU1,2(), Shisong CAO1,2, Chen YU1,2, Yani ZHANG1,2
1. College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
2. Beijing Key Laboratory of Resources, Environment and Geographic Information System, Beijing 100048, China
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摘要 

天空视域因子(sky view factor, SVF)是一个描述三维空间形态的数值,可以反映复杂的城市形态,被广泛应用于城市热岛效应、城市能量平衡等方面的研究。利用数字表面模型(digital surface model, DSM),以北京鸟巢周边地区为例,计算该地区的SVF; 同时还利用鱼眼相片提取SVF,并对2种方法的计算结果进行比较分析。结果表明,利用DSM数据计算的SVF受搜索半径大小、搜索方向数量的影响,SVF随着搜索半径的增大而减小,随着搜索方向数量增加而减小; 当搜索方向为32个、搜索半径为80个像元时,DSM提取的SVF结果最准确,与鱼眼相片计算得到的SVF最接近,均方根误差为0.064; 2种方法计算的SVF具有线性相关关系,表明利用DSM计算大范围城市SVF的方法具体一定的可行性。

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段欣
胡德勇
曹诗颂
于琛
张亚妮
关键词 天空视域因子数字表面模型鱼眼相片城市区域    
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.

Key wordsSVF    digital surface model    fisheye photos    urban areas
收稿日期: 2018-05-16      出版日期: 2019-08-30
:  TP79  
基金资助:国家自然科学基金项目“基于三维建模与天空视域系数的城市地表辐射和能量收支参数化”(41671339);国家重点研发计划项目“重特大灾害应急评估与动态决策支持关键技术”共同资助(2017YFB0504102)
通讯作者: 胡德勇
作者简介: 段 欣(1992-),女,硕士研究生,研究方向为资源环境遥感。Email: 1007466766@qq.com.。
引用本文:   
段欣, 胡德勇, 曹诗颂, 于琛, 张亚妮. 城区复杂下垫面天空视域因子参数化方法——以北京鸟巢周边地区为例[J]. 国土资源遥感, 2019, 31(3): 29-35.
Xin DUAN, Deyong HU, Shisong CAO, Chen YU, Yani ZHANG. 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. Remote Sensing for Land & Resources, 2019, 31(3): 29-35.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2019.03.04      或      https://www.gtzyyg.com/CN/Y2019/V31/I3/29
Fig.1  研究区概况
Fig.2  采样点鱼眼相片示例
Fig.3  立体角示意图
Fig.4  技术路线
Fig.5  搜索方向为32个像元时不同搜索半径所计算得到的SVF
Fig.6  搜索半径为50个像元时的SVF
拍摄位置 点数 SVF范围 平均SVF
空地 10 0.789~0.969 0.911
居民区 13 0.427~0.788 0.594
路口 17 0.725~0.944 0.887
操场 8 0.630~0.926 0.803
Tab.1  采样点的SVF计算结果
Fig.7  2种方法SVF比较
Fig.8  不同搜索半径下2种方法线性回归拟合
Fig.9  不同搜索半径、搜索方向数量下的RMSE趋势
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