Webcams, crowdsourcing, and enhanced crosswalks: Developing a novel method to analyze active transportation

Frontiers in Public Health

J. Aaron eHipp¹  Robert ePless²  Alicia eManteiga²  Amanda eBurgess²  Abby eStylianou² 

[1] North Carolina State University;Washington University in St. Louis;

关键词: crowdsourcing;    built environment;    pedestrian detection;    Active Transportation;    Crosswalks;    Webcams;   

DOI  :  10.3389/fpubh.2016.00097

来源: DOAJ

【 摘 要 】

Introduction: 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: 20,529 publicly available webcam images from two street intersections in Washington, D.C., were used to examine the impact of an improved crosswalk on active transportation. A crowdsource, Amazon Mechanical Turk, annotated image data. Temperature data was collected from the National Oceanic and Atmospheric Administration, and precipitation data was 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). Conclusion: 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.

【 授权许可】

Unknown