Quinn James W, Mooney Stephen J, Sheehan Daniel M, Teitler Julien O, Neckerman Kathryn M, Kaufman Tanya K, Lovasi Gina S, Bader Michael D M, Rundle Andrew G
Department of Epidemiology, Mailman School of Public Health, 722 W 168 St 7 Floor, New York NY 10032,
School of Social Work, Columbia University, 1255 Amsterdam Ave, New York NY 10027, New York NY 10027,
J Maps. 2016;12(1):53-60. doi: 10.1080/17445647.2014.978910. Epub 2014 Nov 14.
Neighborhood physical disorder, or the deterioration of urban environments, is associated with negative mental and physical health outcomes. Eleven trained raters used CANVAS, a web-based system for conducting reliable virtual street audits, to collect data on nine indicators of physical disorder using Google Street View imagery of 532 block faces in New York City, New York, USA. We combined the block face indicator data into a disorder scale using item response theory; indicators ranged in severity from presence of litter, a weak indicator of disorder, to abandoned cars, a strong indicator. Using this scale, we estimated disorder at the center point of each sampled block. We then used ordinary kriging to interpolate estimates of disorder levels throughout the city. The resulting map condenses a complex estimation process into an interpretable visualization of the spatial distribution of physical disorder in New York City.
社区物质环境混乱,即城市环境的恶化,与负面的身心健康结果相关。11名经过培训的评估人员使用CANVAS(一个用于进行可靠的虚拟街道审计的网络系统),通过美国纽约市532个街面的谷歌街景图像,收集了关于物质环境混乱的九个指标的数据。我们使用项目反应理论将街面指标数据合并为一个混乱量表;指标的严重程度从垃圾的存在(混乱的一个弱指标)到废弃汽车(一个强指标)不等。使用这个量表,我们估计了每个采样街区中心点的混乱程度。然后,我们使用普通克里金法对整个城市的混乱程度估计值进行插值。生成的地图将一个复杂的估计过程浓缩为纽约市物质环境混乱空间分布的可解释可视化。