Sky View Factor footprints for urban climate modeling
Sky View Factor footprints for urban climate modeling
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DOI：
10.1016/j.uclim.2018.05.004
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发表时间：
2018-09
期刊：
影响因子：
6.4
通讯作者：
Ariane Middel;Jonas Lukasczyk;Ross Maciejewski;M. Demuzere;M. Roth
中科院分区：
文献类型：
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作者：
Ariane Middel;Jonas Lukasczyk;Ross Maciejewski;M. Demuzere;M. Roth
在气候模拟和观测中，城市形态是一个重要的多维变量，因为它显著地驱动着城市局部和微尺度的气候变率。城市形态可以通过城市冠层参数（ucp）来描述，ucp通过指定城市特征的三维几何、排列和材料来解决城市的空间异质性。天空视图因子（SVF）是通过地平线限制分数捕获三维形式的降维UCP。SVF已成为一种流行的参数化城市形态的度量，但目前的方法难以扩大到全球覆盖范围。本研究引入了一种基于谷歌街景（GSV）的大数据方法来计算城市地区的svf。检索90度视场的GSV照片，并通过等角投影转换为半球面视图。采用图像处理方法将鱼眼分割为天空像素和非天空像素，并采用环空法计算SVF。将结果与使用深度学习分割的GSV图像检索到的svf进行比较。世界各地的城市地区总共有15,938,172个GSV地点。介绍了两个用例：(1)对谷歌Earth Engine分类的新加坡本地气候带地图进行评估；(2)纽约和旧金山每小时太阳时数图。
Urban morphology is an important multidimensional variable to consider in climate modeling and observations, because it significantly drives the local and micro-scale climatic variability in cities. Urban form can be described through urban canopy parameters (UCPs) that resolve the spatial heterogeneity of cities by specifying the 3-dimensional geometry, arrangement, and materials of urban features. The sky view factor (SVF) is a dimension-reduced UCP capturing 3-dimensional form through horizon limitation fractions. SVF has become a popular metric to parameterize urban morphology, but current approaches are difficult to scale up to global coverage. This study introduces a Big-Data approach to calculate SVFs for urban areas from Google Street View (GSV). 90-degree field-of-view GSV photos are retrieved and converted into hemispherical views through equiangular projection. The fisheyes are segmented into sky and non-sky pixels using image processing, and the SVF is calculated using an annulus method. Results are compared to SVFs retrieved from GSV images segmented using deep learning. SVF footprints are presented for urban areas around the world tallying 15,938,172 GSV locations. Two use cases are introduced: (1) an evaluation of a Google Earth Engine classified Local Climate Zone map for Singapore; (2) hourly sun duration maps for New York and San Francisco.