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Evolution of a synthetic population and its daily mobility patterns under spatial strategies for urban growth

Journal Article


Abstract


  • This chapter proposes and tests an innovative method to integrate a spatial scenario-based approach with a synthetic population evolution model and a mobility assignment model. Results are applied to assess future housing demand by dwelling type, and to identify future hubs for daily trips associated to an urban growth scenario in a case study. Main contributions of this research include the generation of urban population data at fine spatial and temporal scales and the inclusion of spatial planning into a synthetic population evolution model. Although current limitations associated to model assumptions and data availability are identified, the model is built in a platform flexible to adapt to new parameters and datasets. Big data is envisioned as a potential source of future improvements, through better and more frequent characterisation of population behaviour and interdependencies between demographics, land use and transportation.

Authors


  •   Leao, Simone (external author)
  •   Huynh, Nam N. (external author)
  •   Taylor, Alison (external author)
  •   Pettit, Christopher (external author)
  •   Perez, Pascal

Publication Date


  • 2017

Citation


  • Leao, S. Z., Huynh, N., Taylor, A., Pettit, C. & Perez, P. (2017). Evolution of a synthetic population and its daily mobility patterns under spatial strategies for urban growth. Lecture Notes in Geoinformation and Cartography, 399-417.

Scopus Eid


  • 2-s2.0-85028650671

Number Of Pages


  • 18

Start Page


  • 399

End Page


  • 417

Place Of Publication


  • Heidelberg

Abstract


  • This chapter proposes and tests an innovative method to integrate a spatial scenario-based approach with a synthetic population evolution model and a mobility assignment model. Results are applied to assess future housing demand by dwelling type, and to identify future hubs for daily trips associated to an urban growth scenario in a case study. Main contributions of this research include the generation of urban population data at fine spatial and temporal scales and the inclusion of spatial planning into a synthetic population evolution model. Although current limitations associated to model assumptions and data availability are identified, the model is built in a platform flexible to adapt to new parameters and datasets. Big data is envisioned as a potential source of future improvements, through better and more frequent characterisation of population behaviour and interdependencies between demographics, land use and transportation.

Authors


  •   Leao, Simone (external author)
  •   Huynh, Nam N. (external author)
  •   Taylor, Alison (external author)
  •   Pettit, Christopher (external author)
  •   Perez, Pascal

Publication Date


  • 2017

Citation


  • Leao, S. Z., Huynh, N., Taylor, A., Pettit, C. & Perez, P. (2017). Evolution of a synthetic population and its daily mobility patterns under spatial strategies for urban growth. Lecture Notes in Geoinformation and Cartography, 399-417.

Scopus Eid


  • 2-s2.0-85028650671

Number Of Pages


  • 18

Start Page


  • 399

End Page


  • 417

Place Of Publication


  • Heidelberg