城市天空开阔度矢量/栅格估算方法对比

doi:10.7522/j.issn.1000-694X.2017.00021

摘要/Abstract

摘要： 城市天空开阔度（Sky View Factor，SVF）是重要的城市形态学参数，为了找出高效可靠的方法定量分析城市天空开阔度，对比了矢量与栅格两种估算方法在城市天空开阔度估算与制图中的表现。以福建省晋江市为例，选取了软件计算法中的矢量计算法和栅格计算法对天空开阔度进行估算，并在结果的宏观分布规律、不同方法结果数值差异、不同分辨率结果一致性几方面进行对比分析。结果表明：与栅格估算法相比，矢量估算方法估算结果与城市建筑结构相符合，估算结果数据分布规律更合理，不同分辨率结果一致性更高，在较高的分辨率下更适应城市天空开阔度定量分析与制图的需要；但在低分辨率情况下，两种方法直接计算结果的代表性都极低。

关键词: 天空开阔度, 建筑分布数据, 城市形态学参数, 城市微气候, 晋江

Abstract: Urban Sky View Factor (SVF) is one of the most important urban morphological parameters.In order to find an efficient and reliable method to quantitatively analyze the distribution of urban SVF,the performance of vector method and raster method in estimating and mapping urban SVF had been compared.Taking Jinjiang City of Fujian Province as an example,the vector and raster calculation method in the software calculation method has been chosen to estimate the SVF.The results has been compared and analyzed in the macroscopic distribution,numerical differences of different methods and consistency at different resolution.It is found that the macroscopic distribution trend of SVF calculated with both vector and raster method are consistent,and the higher the resolution is,the more similar the results of two methods are.The results of vector method are more reasonable than those of the raster method,and the consistency of results under different resolutions is higher than that of the raster method.Compare to raster estimation method,vector SVF estimation method is more suitable for the need of quantitative analysis and mapping of SVF at high resolution.However,in low resolution cases,the representatives of results directly estimated from both methods are extremely low.

Key words: Sky View Factor (SVF), Building distribution data, urban morphological parameters, urban microclimate, Jinjiang

中图分类号:

TU984.11

李梦溪, 邱新法, 曾燕, 祝善友. 城市天空开阔度矢量/栅格估算方法对比[J]. 中国沙漠, 2017, 37(4): 811-819.

Li Mengxi, Qiu Xinfa, Zeng Yan, Zhu Shanyou. Comparison of Vector/Raster Estimation Methods for Urban Sky View Factor[J]. JOURNAL OF DESERT RESEARCH, 2017, 37(4): 811-819.

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