Assessing multiscale visual appearance characteristics of neighbourhoods using geographically weighted principal component analysis in Shenzhen,China |
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| Affiliation: | 1. School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China;2. Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China;3. School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China;4. College of Resources and Environmental Science, Hunan Normal University, Changsha, 410081, China;5. Key Laboratory of Geospatial Big Data Mining and Application, Hunan Province, Changsha, 410000, China;6. Shenzhen Municipal Planning & Land Real Estate Information Centre, Shenzhen, 518034, China;1. Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China;2. SpaceTimeLab, Department of Civil, Environmental and Geomatic Engineering, University College London, London WC1E 6BT, United Kingdom;1. School of Resource and Environmental Sciences, Wuhan University, Wuhan, China;2. Institute of Smart Perception and Intelligent Computing, Wuhan University, Wuhan, China;3. Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China;4. School of Information Engineering, China University of Geosciences, Wuhan, China;5. Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing Institute of Surveying and Mapping, Beijing, China;1. Transport, Health and Urban Design, Melbourne School of Design, The University of Melbourne, Parkville, VIC 3010, Australia;2. Melbourne School of Engineering, The University of Melbourne, Parkville, VIC 3010, Australia;3. Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia;1. Leeds Institute for Data Analytics (LIDA) and School of Geography, University of Leeds, Leeds LS2 9JT, UK;2. Rothamsted Research, North Wyke, Okehampton, Devon EX20 2SB, UK;3. Graduate School of Global Environmental Studies, Kyoto University, Kyoto 606-8501, Japan |
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| 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. |
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