The MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
PLoS One. 2013 Jul 24;8(7):e68400. doi: 10.1371/journal.pone.0068400. Print 2013.
A traveler visiting Rio, Manila or Caracas does not need a report to learn that these cities are unequal; she can see it directly from the taxicab window. This is because in most cities inequality is conspicuous, but also, because cities express different forms of inequality that are evident to casual observers. Cities are highly heterogeneous and often unequal with respect to the income of their residents, but also with respect to the cleanliness of their neighborhoods, the beauty of their architecture, and the liveliness of their streets, among many other evaluative dimensions. Until now, however, our ability to understand the effect of a city's built environment on social and economic outcomes has been limited by the lack of quantitative data on urban perception. Here, we build on the intuition that inequality is partly conspicuous to create quantitative measure of a city's contrasts. Using thousands of geo-tagged images, we measure the perception of safety, class and uniqueness; in the cities of Boston and New York in the United States, and Linz and Salzburg in Austria, finding that the range of perceptions elicited by the images of New York and Boston is larger than the range of perceptions elicited by images from Linz and Salzburg. We interpret this as evidence that the cityscapes of Boston and New York are more contrasting, or unequal, than those of Linz and Salzburg. Finally, we validate our measures by exploring the connection between them and homicides, finding a significant correlation between the perceptions of safety and class and the number of homicides in a NYC zip code, after controlling for the effects of income, population, area and age. Our results show that online images can be used to create reproducible quantitative measures of urban perception and characterize the inequality of different cities.
游客在游览里约热内卢、马尼拉或加拉加斯时，无需报告就能了解到这些城市是不平等的；从出租车窗口就能直接看到。这不仅是因为在大多数城市，不平等现象显而易见，还因为城市表现出了各种形式的不平等，这些不平等对于偶然的观察者来说是显而易见的。城市在居民收入、社区清洁度、建筑美观度以及街道活力等诸多评价维度上高度异质且往往不平等。然而，到目前为止，我们理解城市建成环境对社会经济结果的影响的能力一直受到缺乏城市感知的定量数据的限制。在这里，我们基于不平等现象在某种程度上是显而易见的这一直觉，来创建城市对比的定量衡量标准。我们利用数千张带有地理标签的图像来衡量对安全、阶层和独特性的感知；这些图像来自美国的波士顿和纽约，以及奥地利的林茨和萨尔茨堡，我们发现，纽约和波士顿的图像所引发的感知范围比林茨和萨尔茨堡的图像所引发的感知范围要大。我们将这解释为波士顿和纽约的城市景观比林茨和萨尔茨堡的城市景观更具对比性，或者说更不平等。最后，我们通过探索感知与凶杀案之间的联系来验证我们的衡量标准，发现在控制了收入、人口、面积和年龄等因素的影响后，安全和阶层感知与纽约市邮政编码凶杀案数量之间存在显著相关性。我们的研究结果表明，在线图像可用于创建城市感知的可重现定量衡量标准，并描述不同城市之间的不平等现象。
