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LandSys: an agent-based Cellular Automata model of land use change developed for transportation analysis

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  • Zhao, Liyuan
  • Peng, Zhong-Ren

Abstract

This paper reports on LandSys, a land use model that integrates a Cellular Automata (CA) model and agent-based models to facilitate transportation demand modeling and analysis. The LandSys model simulates the spatial suitability of land use change over time based on both the land use suitability and the impacts of neighboring land use types in a CA model framework, coupled with individual decision-makers’ behaviors with agent-based models (e.g., household, employment, and developer agents). To generate inputs for transportation models, two equilibriums in the land use market are considered: land development equilibrium simulates land use change at a manageable cell level (50m×50m), while land supply–demand equilibrium allocates firms and agents based on the bid-rent theory. Data from Orange County, FL, are used in a case study for model estimation and validation. A comparison of model results with actual data from 2000 shows that the proposed LandSys model is effective in estimating land use change, with an accuracy of 85.4%. The model is also responsive to land use policies and could be used for what–if analysis.

Suggested Citation

  • Zhao, Liyuan & Peng, Zhong-Ren, 2012. "LandSys: an agent-based Cellular Automata model of land use change developed for transportation analysis," Journal of Transport Geography, Elsevier, vol. 25(C), pages 35-49.
    • Handle: RePEc:eee:jotrge:v:25:y:2012:i:c:p:35-49
    DOI: 10.1016/j.jtrangeo.2012.07.006
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    References listed on IDEAS

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    2. Luis Briceño & Roberto Cominetti & Cristián Cortés & Francisco Martínez, 2008. "An Integrated Behavioral Model of Land Use and Transport System: A Hyper-network Equilibrium Approach," Networks and Spatial Economics, Springer, vol. 8(2), pages 201-224, September.
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    4. Felsenstein, Daniel & Axhausen, Kay & Waddell, Paul, 2010. "Land use-transportation modeling with UrbanSim: Experiences and progress," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(2), pages 1-3.
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    Citations

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    Cited by:

    1. Gang Lin & Dong Jiang & Jingying Fu & Chenglong Cao & Dongwei Zhang, 2020. "Spatial Conflict of Production–Living–Ecological Space and Sustainable-Development Scenario Simulation in Yangtze River Delta Agglomerations," Sustainability, MDPI, vol. 12(6), pages 1-11, March.
    2. Yu Chen & Shuangshuang Liu & Wenbo Ma & Qian Zhou, 2023. "Assessment of the Carrying Capacity and Suitability of Spatial Resources and the Environment and Diagnosis of Obstacle Factors in the Yellow River Basin," IJERPH, MDPI, vol. 20(4), pages 1-26, February.
    3. Auwalu Faisal Koko & Wu Yue & Ghali Abdullahi Abubakar & Roknisadeh Hamed & Akram Ahmed Noman Alabsi, 2020. "Monitoring and Predicting Spatio-Temporal Land Use/Land Cover Changes in Zaria City, Nigeria, through an Integrated Cellular Automata and Markov Chain Model (CA-Markov)," Sustainability, MDPI, vol. 12(24), pages 1-21, December.
    4. Kai Zhu & Yufeng Cheng & Weiye Zang & Quan Zhou & Youssef El Archi & Hossein Mousazadeh & Moaaz Kabil & Katalin Csobán & Lóránt Dénes Dávid, 2023. "Multiscenario Simulation of Land-Use Change in Hubei Province, China Based on the Markov-FLUS Model," Land, MDPI, vol. 12(4), pages 1-27, March.
    5. Jie Song & Xinyu Fu & Ruoniu Wang & Zhong-Ren Peng & Zongni Gu, 2018. "Does planned retreat matter? Investigating land use change under the impacts of flooding induced by sea level rise," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(5), pages 703-733, June.
    6. Zhao, Liyuan & Shen, Le, 2019. "The impacts of rail transit on future urban land use development: A case study in Wuhan, China," Transport Policy, Elsevier, vol. 81(C), pages 396-405.
    7. Wang, Ling & Wang, Ke & Zhang, Jianjun & Zhang, Di & Wu, Xia & Zhang, Lijun, 2020. "Multiple objective-oriented land supply for sustainable transportation: A perspective from industrial dependence, dominance and restrictions of 127 cities in the Yangtze River Economic Belt of China," Land Use Policy, Elsevier, vol. 99(C).

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