  Location Based Services (LBS) provide a new perspective for spatiotemporally
analyzing dynamic urban systems. Research has investigated urban dynamics using
GSM (Global System for Mobile Communications), GPS (Global Positioning System),
SNS (Social Networking Services) and Wi-Fi techniques. However, less attention
has been paid to the analysis of urban structure (especially commuting pattern)
using smart card data (SCD), which are widely available in most cities.
Additionally, ubiquitous LBS data, although providing rich spatial and temporal
information, lacks rich information on the social dimension, which limits its
in-depth application. To bridge this gap, this paper combines bus SCD for a
one-week period with a one-day household travel survey, as well as a
parcel-level land use map to identify job-housing locations and commuting trip
routes in Beijing. Two data forms (TRIP and PTD) are proposed, with PTD used
for jobs-housing identification and TRIP used for commuting trip route
identification. The results of the identification are aggregated in the bus
stop and traffic analysis zone (TAZ) scales, respectively. Particularly,
commuting trips from three typical residential communities to six main business
zones are mapped and compared to analyze commuting patterns in Beijing. The
identified commuting trips are validated on three levels by comparison with
those from the survey in terms of commuting time and distance, and the positive
validation results prove the applicability of our approach. Our experiment, as
a first step toward enriching LBS data using conventional survey and urban GIS
data, can obtain solid identification results based on rules extracted from
existing surveys or censuses.
