Assessing multiscale visual appearance characteristics of neighbourhoods using geographically weighted principal component analysis in Shenzhen, China

Abstract

The neighbourhood is a basic residential unit and is characterized by its physical setting, functional attributes and visual appearance. The visual appearance of a neighbourhood can directly affect the impression of humans regarding the local living environment. Assessing the characteristics of the visual appearance of a neighbourhood is significance for promoting people's physical activities, improving residents' sense of comfort and even ensuring the equality of facilities. However, studies assessing the spatial characteristics of visual appearance are still limited. Therefore, this article applies street view images to quantify the visual appearance of neighbourhoods at multiple scales in Shenzhen, China. Then, geographically weighted principal component analysis (GWPCA) is employed to explore the varying multivariate structures of visual appearance. The results confirm that GWPCA can be effective in assessing the visual appearance characteristics of neighbourhoods while considering spatial heterogeneity. The visual appearance characteristics of neighbourhoods are sensitive to both the spatial location and analysis scale. The extracted geographically weighted principal components (GWPCs) can represent the original screen elements by emphasizing certain comprehensive concepts, such as walkability, accessibility and vibrancy. The exploratory findings of this article allow for an improvement of studies on spatial quality at the human scale and could potentially guide neighbourhood planning and street design.