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The dynamic spatial multinomial probit model: analysis of land use change using parcel-level data

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  • Wang, Xiaokun (Cara)
  • Kockelman, Kara M.
  • Lemp, Jason D.

Abstract

Many transportation-related behaviors involve multinomial discrete response in a temporal and spatial context. These include quality of paved roadway sections over time, evolution of land use at the parcel level, vehicle purchases by socially networked households, and mode choices by individuals residing across adjacent homes or neighborhoods. Such responses depend on various influential factors, and can have temporal and spatial dependence or autocorrelation. In many cases, dynamic spatial-model specifications based on maximum fitness, profit or utility may be most appropriate.

Suggested Citation

  • Wang, Xiaokun (Cara) & Kockelman, Kara M. & Lemp, Jason D., 2012. "The dynamic spatial multinomial probit model: analysis of land use change using parcel-level data," Journal of Transport Geography, Elsevier, vol. 24(C), pages 77-88.
    • Handle: RePEc:eee:jotrge:v:24:y:2012:i:c:p:77-88
    DOI: 10.1016/j.jtrangeo.2012.06.011
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    Cited by:

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    2. Bonfiglio, Andrea & Arzeni, Andrea, 2019. "Spatial distribution of organic farms and territorial context: An application to an Italian rural region," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 8(3), December.
    3. Chaogui Kang & Dongwan Fan & Hongzan Jiao, 2021. "Validating activity, time, and space diversity as essential components of urban vitality," Environment and Planning B, , vol. 48(5), pages 1180-1197, June.
    4. Páez, Antonio & López, Fernando A. & Ruiz, Manuel & Morency, Catherine, 2013. "Development of an indicator to assess the spatial fit of discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 217-233.
    5. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2016. "Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system," Journal of Transport Geography, Elsevier, vol. 54(C), pages 218-227.
    6. Wrenn, Douglas H. & Sam, Abdoul G., 2014. "Geographically and temporally weighted likelihood regression: Exploring the spatiotemporal determinants of land use change," Regional Science and Urban Economics, Elsevier, vol. 44(C), pages 60-74.
    7. Chen, Cong & Zhang, Su & Zhang, Guohui & Bogus, Susan M. & Valentin, Vanessa, 2014. "Discovering temporal and spatial patterns and characteristics of pavement distress condition data on major corridors in New Mexico," Journal of Transport Geography, Elsevier, vol. 38(C), pages 148-158.
    8. Shen, Yu & de Abreu e Silva, João & Martínez, Luis Miguel, 2014. "Assessing High-Speed Rail’s impacts on land cover change in large urban areas based on spatial mixed logit methods: a case study of Madrid Atocha railway station from 1990 to 2006," Journal of Transport Geography, Elsevier, vol. 41(C), pages 184-196.

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