Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 53-57, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-53-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 53-57, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-53-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  12 Sep 2017

12 Sep 2017

REVEALING SPATIAL VARIATION AND CORRELATION OF URBAN TRAVELS FROM BIG TRAJECTORY DATA

X. Li2, W. Tu1,3, S. Shen1, Y. Yue3, N. Luo2, and Q. Li3,4 X. Li et al.
  • 1Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 518040, China
  • 2School of Geodesy and Geomatics , Wuhan University, Wuhan 430079, China
  • 3Shenzhen Key Lab of Spatial Smart Sensing and Service & Institute of Smart City, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
  • 4State Key Lab of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Keywords: Human travel, Big data, Trajectory, Spatial Variation, Smart card data, Correlation

Abstract. With the development of information and communication technology, spatial-temporal data that contain rich human mobility information are growing rapidly. However, the consistency of multi-mode human travel behind multi-source spatial-temporal data is not clear. To this aim, we utilized a week of taxies’ and buses’ GPS trajectory data and smart card data in Shenzhen, China to extract city-wide travel information of taxi, bus and metro and tested the correlation of multi-mode travel characteristics. Both the global correlation and local correlation of typical travel indicator were examined. The results show that: (1) Significant differences exist in of urban multi-mode travels. The correlation between bus travels and taxi travels, metro travel and taxi travels are globally low but locally high. (2) There are spatial differences of the correlation relationship between bus, metro and taxi travel. These findings help us understanding urban travels deeply therefore facilitate both the transport policy making and human-space interaction research.