Your browser doesn't support javascript.
loading
Understanding heat patterns produced by vehicular flows in urban areas.
Zhu, Rui; Wong, Man Sing; Guilbert, Éric; Chan, Pak-Wai.
Affiliation
  • Zhu R; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, 181 Chatham Road South, Kowloon, Hong Kong.
  • Wong MS; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, 181 Chatham Road South, Kowloon, Hong Kong. lswong@polyu.edu.hk.
  • Guilbert É; Department of Geomatics Sciences, Laval University, 1055 Avenue du séminaire, Local 1327, Québec (Québec), G1V 0A6, Canada.
  • Chan PW; Hong Kong Observatory, 13A Nathan Road, Kowloon, Hong Kong.
Sci Rep ; 7(1): 16309, 2017 11 24.
Article in En | MEDLINE | ID: mdl-29176562
Vehicular traffic has strong implication in the severity and degree of Urban Heat Island (UHI) effect in a city. It is crucial to map and monitor the spatio-temporal heat patterns from vehicular traffic in a city. Data observed from traffic counting stations are readily available for mapping the traffic-related heat across the stations. However, macroscopic models utilizing traffic counting data to estimate dynamic directional vehicular flows are rarely established. Our work proposes a simple and robust cell-transmission-model to simulate all the possible cell-based origin-destination trajectories of vehicular flows over time, based on the traffic counting stations. Result shows that the heat patterns have notable daily and weekly periodical circulation/pattern, and volumes of heat vary significantly in different grid cells. The findings suggest that vehicular flows in some places are the dominating influential factor that make the UHI phenomenon more remarkable.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Sci Rep Year: 2017 Document type: Article Affiliation country: Hong Kong Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Sci Rep Year: 2017 Document type: Article Affiliation country: Hong Kong Country of publication: United kingdom