Department of Family Medicine and Community Health
Behavior and Behavior Mechanisms | Community Health and Preventive Medicine | Preventive Medicine
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.
Big data, Emerging technology, Locative data, Microclimates, Mobile phones, Pedestrian activity, Spatial behavior, Walking, Weather, Weather conditions and active transportation
Rights and Permissions
© 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
DOI of Published Version
Prev Med Rep. 2017 Jul 27;8:30-37. doi: 10.1016/j.pmedr.2017.07.002. eCollection 2017 Dec. Link to article on publisher's site
Preventive medicine reports
Vanky, Anthony P.; Verma, Santosh K.; Courtney, Theodore K.; Santi, Paolo; and Ratti, Carlo, "Effect of weather on pedestrian trip count and duration: City-scale evaluations using mobile phone application data" (2017). Open Access Articles. 3197.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.