220 likes | 370 Views
Introduction of “People flow project” ---Understanding of dynamic change about people in the city. Yoshihide Sekimoto, Project Associate Prof. Center for Spatial Information Science, The University of Tokyo. Center for Spatial Information Science, the University of Tokyo. History of CSIS.
E N D
Introduction of “People flow project” ---Understanding of dynamic change about people in the city Yoshihide Sekimoto,Project Associate Prof. Center for Spatial Information Science, The University of Tokyo
Center for Spatial Information Science,the University of Tokyo History of CSIS 1988 “National cartography museum” Recommendation by the Science Council of Japan Launch of Joint research program using spatial data platform 1998 Enhancement of Center functions as joint facility Spatial data sharing system Spatial data clearinghouse 1996 National committee for a research center for GIS CSIS Catalogue service Address matching service 1998 CSIS established Academic Portal of GIS GISSchool Design studio for GI 2005 Moved to new Kashiwa campus Spatial data platform for joint research 2006 Re-launch of CSIS as a National (inter-university) joint-research facility History Geospatially-enabled society 2007
Needs of People flow data Needs of time-based location information of many people are increasing… Prevention of secondary disaster in the complex urban space Stimulation of the economy by people gathering Flood disaster to underground mall Events like Festival Big earthquake Outdoor advertising
People flow project in CSIS • People flow project since 2008 in CSIS introduces some technologies and results about people flow http://pflow.csis.u-tokyo.ac.jp
Existing our research * Y. Sekimoto et al. PFLOW: Reconstruction of people flow by recycling large-scale fragmentary social survey data, IEEE Pervasive Computing, Vol.10(4) pp.27-35, 2011. Sekimoto et al. (2011)* had proposed reconstruction method using large-scale fragmentary social survey data Reconstruction of macroscopic people flow in Central Tokyo using person trip (PT) survey data
3D visualization 3D visualization with 1-km2 mesh
Data source: questionnaire(e.g. Person trip data) Main part of PT survey sheet (from the Tokyo Metropolitan Region Transportation Planning Commission web site "http://www.tokyo-pt.jp/data/file/tebiki.pdf")
Spatio-temporal interpolation from OD data • XXXX a) Geocoded OD of each sub trip c) Interpolation at each 1 minute-intervals b) Route choice along road/railway topology
Project structure Activity model of each people Observation data PT data ・・・・ Aggregated distribution Disaggregated moving model + Estimation Observe People flow in real world
Classification of each data source Quality of sample PT data Real-time property
Data source: Twitter Tweet per hour Daily fluctuation for two weeks Time From Dr. Fujita in CSIS
Data source: Four square Four square mapping data of one person for two years in SF http://www.weeplaces.com
Data source: mobile phone base station Mobile Spatial Statistics Operational data De-identification Privilege Aggregation Aggregated population Mobile Spatial Statistics(From NTTDocomo web site: http://www.nttdocomo.co.jp/corporate/disclosure/mobile_spatial_statistics/)
Data source: mobile phone GPS data Density map from Auto-GPS data(ZENRIN DataCom CO.,LTD. http://lab.its-mo.com/densitymap/)
Data assimilation technology using observation data • Data assimilation is integration of model and observation data (based on e.g. Recursive Baysian Estimation…) RMSE of the number of people Red: No assimulation Blue: Assimulation Time(hour) Total RMSE of roads between observed and estimated data Total RMSE of stations between observed and estimated data
Many joint researches through “People Flow Data Set” 【Transportation】 # Research on improving the efficiency of urban transport systems using portable personal mobility.(iTransport Lab, Ltd.) # A simulation of tourist flow patterns in the Sendai metropolitan area using the People Flow Analysis Platform. Masayoshi Tanishita (Chuo University) # Utilization of statistical data in urban transport planning. (Ritsumeikan Asia Pacific University Department of Asian Pacific Studies) 【spatio-temporal analysis】 # Detection of patterns in travel routes using position information and travel times (Kobe University Graduate School of Engineering) # Development of a spatio-temporal data model for analysis of spatio-temporal behavior using GIS. (Tokyo Metropolitan University) 【Risk analysis】 # A model for the transmission of novel infectious diseases. (University of Tokyo Institute of Industrial Science) # An investigation of of disaster risk using GIS. (Aichi Institute of Technology Department of Environmental Engineering) 【Personal information and security】 # On the anonymization of personal information and its two-dimensional use (Information Grand Voyage Project). (Mitsubishi Research Institute, Inc.) 【Environment】 # Development of a scenario for fine spatial output and changes in land use via unified system analysis. (National Institute for Environmental Studies) 【Marketing】 # A study of consumer respiration models using person-trip data. (Fine Analysis, LLC)
Influenza Day 3 Day 27 Day 46 Aihara & Suzuki lab in IIS, Univ. of Tokyo