Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 781-785, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-781-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
11 Dec 2015
INTRA-URBAN MOVEMENT FLOW ESTIMATION USING LOCATION BASED SOCIAL NETWORKING DATA
A. Kheiri1, F. Karimipour2, and M. Forghani2 1Faculty Technical and Engineering, Eslamic Azad University of Larestan, Larestan, Iran
2Faculty of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Keywords: Location Based Social Network, Check-in Data, O/D Matrix, Mobility Abstract. In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook, which have attracted an increasing number of users and greatly enriched their urban experience. Location-based social network data, as a new travel demand data source, seems to be an alternative or complement to survey data in the study of mobility behavior and activity analysis because of its relatively high access and low cost. In this paper, three OD estimation models have been utilized in order to investigate their relative performance when using Location-Based Social Networking (LBSN) data. For this, the Foursquare LBSN data was used to analyze the intra-urban movement behavioral patterns for the study area, Manhattan, the most densely populated of the five boroughs of New York city. The outputs of models are evaluated using real observations based on different criterions including distance distribution, destination travel constraints. The results demonstrate the promising potential of using LBSN data for urban travel demand analysis and monitoring.
Conference paper (PDF, 1019 KB)


Citation: Kheiri, A., Karimipour, F., and Forghani, M.: INTRA-URBAN MOVEMENT FLOW ESTIMATION USING LOCATION BASED SOCIAL NETWORKING DATA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 781-785, https://doi.org/10.5194/isprsarchives-XL-1-W5-781-2015, 2015.

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