Data mining and spatio-temporal characteristics of urban road traffic emissions: A case study in Shijiazhuang, China.

ABSTRACT: Accurate estimation of traffic emissions and analysis of spatio-temporal distribution on urban roads play a crucial role in the development of low-carbon transportation system. Traditionally, a region's emission characteristics have been studied using numerous emission models with GPS-based spatio-temporal data. Due to the heavy data processing needs of GPS-based data, emission characteristics for a large region have been studied by dividing the region into a limited number of smaller areas or units. Additionally, GPS data are based on a few vehicles in the traffic which does not fully reflect road conditions. This paper proposed an approach that can be used to study and calculate the spatio-temporal emission pattern of a region at a roadway section level by using Baidu's online traffic da

SUBMITTER: Ren L 

PROVIDER: S-EPMC10718443 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature