title: Webcams, Crowdsourcing, and Enhanced Crosswalks: Developing a Novel Method to Analyze Active Transportation.
abstract: BACKGROUND
  Active transportation opportunities and infrastructure are an important component of a community's design, livability, and health. Features of the built environment influence active transportation, but objective study of the natural experiment effects of built environment improvements on active transportation is challenging. The purpose of this study was to develop and present a novel method of active transportation research using webcams and crowdsourcing, and to determine if crosswalk enhancement was associated with changes in active transportation rates, including across a variety of weather conditions.
  
  
  METHODS
  The 20,529 publicly available webcam images from two street intersections in Washington, DC, USA were used to examine the impact of an improved crosswalk on active transportation. A crowdsource, Amazon Mechanical Turk, annotated image data. Temperature data were collected from the National Oceanic and Atmospheric Administration, and precipitation data were annotated from images by trained research assistants.
  
  
  RESULTS
  Summary analyses demonstrated slight, bi-directional differences in the percent of images with pedestrians and bicyclists captured before and after the enhancement of the crosswalks. Chi-square analyses revealed these changes were not significant. In general, pedestrian presence increased in images captured during moderate temperatures compared to images captured during hot or cold temperatures. Chi-square analyses indicated the crosswalk improvement may have encouraged walking and biking in uncomfortable outdoor conditions (P < 0.5).
  
  
  CONCLUSIONS
  The methods employed provide an objective, cost-effective alternative to traditional means of examining the effects of built environment changes on active transportation. The use of webcams to collect active transportation data has applications for community policymakers, planners, and health professionals. Future research will work to validate this method in a variety of settings as well as across different built environment and community policy initiatives.
authors.affiliation: Department of Parks, Recreation, and Tourism Management, Center for Geospatial Analytics, North Carolina State University , Raleigh, NC , USA.
authors.forename: J Aaron
authors.initials: JA
authors.lastname: Hipp
authors.affiliation: Prevention Research Center, Washington University in St. Louis , St. Louis, MO , USA.
authors.forename: Alicia
authors.initials: A
authors.lastname: Manteiga
authors.affiliation: Prevention Research Center, Washington University in St. Louis , St. Louis, MO , USA.
authors.forename: Amanda
authors.initials: A
authors.lastname: Burgess
authors.affiliation: Department of Computer Science and Engineering, Washington University in St. Louis , St. Louis, MO , USA.
authors.forename: Abby
authors.initials: A
authors.lastname: Stylianou
authors.affiliation: Department of Computer Science and Engineering, Washington University in St. Louis , St. Louis, MO , USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Pless
keywords: active transportation; bicyclist detection; built environment; crosswalks; crowdsourcing; pedestrian detection; webcams