期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 114, 期 29, 页码 7571-7576出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1619003114
关键词
urban economics; gentrification; urban studies; computer vision; neighborhood effects
资金
- International Growth Center
- Alfred P. Sloan Foundation
- Star Family Challenge grant
- National Science Foundation [CCF-1216095, SES-1459912]
- Harvard Milton Fund
- Ng Fund of the Harvard Center of Mathematical Sciences and Applications
- Human Capital and Economic Opportunity Working Group - Institute for New Economic Thinking
- Taubman Center for State and Local Government
- Google Living Labs Award
- Divn Of Social and Economic Sciences
- Direct For Social, Behav & Economic Scie [1459912] Funding Source: National Science Foundation
Which neighborhoods experience physical improvements? In this paper, weintroduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the physical appearance of five US cities with economic and demographic data and find three factors that predict neighborhood improvement. First, neighborhoods that are densely populated by college-educated adults are more likely to experience physical improvements-an observation that is compatible with the economic literature linking human capital and local success. Second, neighborhoods with better initial appearances experience, on average, larger positive improvements-an observation that is consistent with tipping theories of urban change. Third, neighborhood improvement correlates positively with physical proximity to the central business district and to other physically attractive neighborhoods-an observation that is consistent with the invasion theories of urban sociology. Together, our results provide support for three classical theories of urban change and illustrate the value of using computer vision methods and street-level imagery to understand the physical dynamics of cities.
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