Vol. 79 (2021)
Original Articles - Urban, Land, Environmental Appraisal and Economics

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

Veronica Alampi Sottini
Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence
Elena Barbierato
Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence
Irene Capecchi
Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence
Tommaso Borghini
Department of Architecture (DIDA), University of Florence
Claudio Saragosa
Department of Architecture (DIDA), University of Florence
Published March 8, 2022
Keywords
  • urban visual quality,
  • urban indicators,
  • Geographically Weighted Regression,
  • Random Forest,
  • Google Street View,
  • Flickr,
  • urban planning
  • ...More
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Abstract

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.

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