基于街景图的中国省会城市天空开阔度研究
首发时间:2019-05-17
摘要:城市作为人类的主要活动场所,其存在和发展会对当地的气候环境带来巨大影响,更是产生以城市热岛效应为主的城市气候问题。在解决城市气候问题方面,城市的空间形态的影响逐渐受到重视。在城市热辐射和热环境研究中,天空开阔度(SVF)是最有用的城市空间指标之一。为揭示城市空间与城市气候之间的关系,本文以中国29个省会城市为研究对象,采用网络街景图测算法,以Python语言和OpenCV开源计算机图像视频处理库为基础,开发出一个可以批量进行天空区域检测及SVF计算的工具,可以获取沿主城路网获得的街景图像并计算,由此得到了各个省会城市研究区域的大量SVF值,并分析了SVF值所反映的城市空间分布,以及城市气候因素、经济、人口因素对城市SVF分布的影响。研究发现,SVF的低值区和高值区分布可以放映处城市空间的遮蔽度和紧凑度,且SVF均值越低的城市,空间格局也会更丰富。在气候因素和经济人口因素方面,年总太阳辐射与SVF均值呈现较好正相关性,年均温度、人口密度、地区GDP与SVF均值呈现较好负相关性,后两个在亚热带湿润气候区的相关性更高。这中大数据的城市形态研究对城市气候研究和建设规划都有着很重要的意义。
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A survey of SVF distributions in Chinese cities using street view images
Abstract:As the main activity place of human beings, the existence and development of the city will have a great impact on the local climate and environment, and it will also produce urban climate problems based on the urban heat island effect. In addressing urban climate issues, the impact of urban spatial patterns has gradually gained attention. In the study of urban thermal radiation and urban thermal environment, sky view factor (SVF) is one of the most useful urban spatial indicators. In order to reveal the relationship between urban space and urban climate, this paper takes 29 provincial capitals in China as the research object, adopts the network street view mapping algorithm, and develops a tool for sky area detection and SVF calculation in batches based on Python language and OpenCV open source. This tool can obtain and calculate the street viA survey of Sky View Factor distributions in Chinese cities using street view imagesew images obtained along the main city road network, and thus obtain a large number of SVF values in the research areas of provincial capital city. The urban spatial distribution and the correlations between SVF and urban climate, economy and population were analyzed.The study found that the distribution of SVF low-value areas and SVF high-value areas can show the shielding and compactness of urban space. A lower the SVF mean indicate a more spatial patterns. The annual total solar radiation is positively correlated with the SVF mean, instead, the annual average temperature, population density, regional GDP and the SVF mean are negatively correlated, while the latter two are more correlated in humid subtropical climate areas. The urban morphology research of big data has important significance for urban climate research and construction planning.
Keywords: urban heat environment Sky View Factor street scene urban form
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