Assessing the perception of urban visual quality: an approach integrating big data and geostatistical techniques

Human well-being is affected by the design quality of the city in which they live and walk. This depends primarily on specific physical characteristics and how they are aggregated together. Many studies have highlighted the great potential of photographic data shared on the Flickr platform for analy...

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Bibliographic Details
Published in:Ce.S.E.T. Aestimum 2021-12, Vol.79 (79), p.75-102
Main Authors: Alampi Sottini, Veronica, Barbierato, Elena, Capecchi, Irene, Borghini, Tommaso, Saragosa, Claudio
Format: Article
Language:English
Subjects:
Architecture
Big Data
Cities
Flickr
Geographically Weighted Regression
Geography
Geostatistics
Google Street View
Internet
Physical characteristics
Physical properties
Questionnaires
Random Forest
Social networks
Urban areas
urban indicators
Urban planning
urban visual quality
Visual perception
Web services
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Summary:Human well-being is affected by the design quality of the city in which they live and walk. This depends primarily on specific physical characteristics and how they are aggregated together. Many studies have highlighted the great potential of photographic data shared on the Flickr platform for analyzing environmental perceptions in landscape and urban planning. Other researchers have used panoramic images from the Google Street View (GSV) web service to extract data on urban quality. However, at the urban level, there are no studies correlating quality perceptions detected by social media platforms with spatial geographic characteristics through geostatistical models. This work proposes the analysis of urban quality in different areas of the Livorno city through a methodological approach based on Geographical Random Forest regression. The result offers important insights into the physical characteristics of a street environment that contribute to the more abstract qualities of urban design.
ISSN:1592-6117
1724-2118
DOI:10.36253/aestim-12093