Vanky Anthony P, Verma Santosh K, Courtney Theodore K, Santi Paolo, Ratti Carlo
Senseable City Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.
Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, USA.
Prev Med Rep. 2017 Jul 27;8:30-37. doi: 10.1016/j.pmedr.2017.07.002. eCollection 2017 Dec.
We examined the association between meteorological (weather) conditions in a given locale and pedestrian trips frequency and duration, through the use of locative digital data. These associations were determined for seasonality, urban microclimate, and commuting. We analyzed GPS data from a broadly available activity tracking mobile phone application that automatically recorded 247,814 trips from 5432 unique users in Boston and 257,697 trips from 8256 users in San Francisco over a 50-week period. Generally, we observed increased air temperature and the presence of light cloud cover had a positive association with hourly trip frequency in both cities, regardless of seasonality. Temperature and weather conditions generally showed greater associations with weekend and discretionary travel, than with weekday and required travel. Weather conditions had minimal association with the duration of the trip, once the trip was initiated. The observed associations in some cases differed between the two cities. Our study illustrates the opportunity that emerging technology presents to study active transportation, and exposes new methods to wider consideration in preventive medicine.
我们通过使用定位数字数据,研究了特定地区的气象(天气)条件与行人出行频率和时长之间的关联。确定了这些关联在季节性、城市微气候和通勤方面的情况。我们分析了一款广泛使用的活动跟踪手机应用程序的GPS数据,该应用程序在50周内自动记录了波士顿5432名独特用户的247,814次出行以及旧金山8256名用户的257,697次出行。总体而言,我们观察到,无论季节性如何,气温升高和有少量云层覆盖与两个城市的每小时出行频率均呈正相关。温度和天气条件与周末及非必要出行的关联通常比与工作日及必要出行的关联更强。一旦行程开始,天气条件与行程时长的关联极小。在某些情况下,两个城市观察到的关联有所不同。我们的研究说明了新兴技术为研究主动式交通提供的机会,并使新方法在预防医学中得到更广泛的考虑。