Urban morphology in China: Dataset development and spatial pattern characterization

• Published in: Sustainable cities and society 2021-08, Vol.71, p.102981, Article 102981
• Main Authors: Li, Huidong, Liu, Yage, Zhang, Huiwen, Xue, Bing, Li, Wenliang
• Format: Article
• Language: English
• Subjects: Canopy geometry; Chinese cities; Urban canopy; Urban climate; Urban morphology
• ISSN: 2210-6707; 2210-6715
• DOI: 10.1016/j.scs.2021.102981

•We developed a 100 m resolution urban morphological dataset for 36 major cities in China.•We proposed a framework to extract morphological parameters from building vectors.•City center showed larger building height and FAI, but smaller street width and SVF.•Southern cities showed larger building height and FAI, but smaller street width and SVF. Characterizing urban morphology is critical for urban climate examination and modeling. However, high-resolution urban morphological datasets are lacking, especially in Chinese cities that undergoing fast-urbanization. We proposed a two-step rasterization method to develop an urban morphological dataset at a resolution of 100 m for 36 major cities in China. The morphological dataset includes building height, width, fraction, and street width as well as sky view factor and frontal area index. We then characterized the spatial patterns of these morphological parameters within and across cities. In general, the derived morphological parameters match the raw vector data well in terms of both magnitude and spatial distribution at the block, district, and city scales. The morphological parameters show large spatial variations within and across cities. On the city scale, the city center shows a larger building height and frontal area index, but smaller street width and sky view factor, compared to the city edge. Across cities, the morphological parameters generally show latitudinal variations, with higher building height and frontal area index, but smaller street width and sky view factor in the south. This new morphological dataset provides fundamental data to examine urban climate mechanism, classify urban land use, and drive urban climate model.