Daily Accessed Street Greenery and Housing Price: Measuring Economic Performance of Human-Scale Streetscapes via New Urban Data

• Published in: Sustainability Vol. 11; no. 6; p. 1741
• Main Authors: Ye, Yu, Xie, Hanting, Fang, Jia, Jiang, Hetao, Wang, De
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 22.03.2019
• Subjects: Air pollution; Algorithms; City centres; Ecological effects; Economic impact; Geographic information systems; Housing; Housing prices; Learning algorithms; Neighborhoods; Outdoor air quality; Real estate; Regression coefficients; Sustainability; Urban planning; Vegetation
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su11061741

The protective effects of street greenery on ecological, psychological, and behavioral phenomena have been well recognized. Nevertheless, the potential economic effect of daily accessed street greenery, i.e., a human-scale and perceptual-oriented quality focusing on exposure to street greenery in people’s daily lives, has not been fully studied because a quantitative measuring of this human-scale indicator is hard to achieve. This study was an attempt in this direction with the help of new urban data and new analytical tools. Shanghai, which has a mature real estate market, was selected for study, and the housing prices of 1395 private neighborhoods in its city center were collected. We selected more than forty variables that were classified under five categories—location features, distances to the closest facilities, density of facilities within a certain radius, housing and neighborhood features, and daily accessed street greenery—in a hedonic pricing model. The distance and density of facilities were computed through a massive number of points-of-interest and a geographical information system. The visible street greenery was collected from Baidu street view images and then measured via a machine-learning algorithm, while accessibility was measured through space syntax. In addition to the well-recognized effects previously discovered, the results show that visible street greenery and street accessibility at global scale hold significant positive coefficients for housing prices. Visible street greenery even obtains the second-highest regression coefficient in the model. Moreover, the combined assessment, the co-presence of local-scale accessibility and eye-level greenery, is significant for housing price as well. This study provides a scientific and quantitative support for the significance of human-scale street greenery, making it an important issue in urban greening policy for urban planners and decision makers.