IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v417y2020ics0304380019304326.html
   My bibliography  Save this article

Land-use Simulation and Decision-Support system (LandSDS): Seamlessly integrating system dynamics, agent-based model, and cellular automata

Author

Listed:
  • Liu, Dongya
  • Zheng, Xinqi
  • Wang, Hongbin

Abstract

This article aims to construct a Land-use Simulation and Decision-Support system (LandSDS) to comprehensively explore the interference and impact of natural environment, individual choice, and national macro-policies on land use and cover change. LandSDS takes full advantage of system dynamics (SD) model, agent-based model (ABM), cellular automata (CA) model, and Geographic Information System (GIS): (1) On the one hand, SD model controls land-use area change on macro level. On the other hand, by passing the parameters values from SD model to CA model, the iterations of CA model are controlled macroscopically, and at the same time, the transition rules in the CA model are affected microscopically by SD model; (2) By simulating the complex selection behaviors of different agents, ABM enforces or participates in the cells’ transformation behaviors in CA model on the micro evolution scale; (3) Taking CA model as a breakthrough point, the micro-cell unit is used to realize the data exchange and communication between SD-ABM-CA by integrating CA with SD and CA with ABM; and (4) Using GIS’s powerful spatial computing and data processing capabilities, the simulation results are further analyzed and processed to obtain more effective information. LandSDS can solve the top-down data analysis and graphic visualization problems caused by target data or policy mutations, and can also handle the data and graphic visualization problems caused by the temporal and spatial changes of cell units. The system solves the analysis methods and technical problems about the top-down and bottom-up seamless integration of the spatial and temporal models. Beijing urban expansion was taken as an example to demonstrate the availability of the system.

Suggested Citation

  • Liu, Dongya & Zheng, Xinqi & Wang, Hongbin, 2020. "Land-use Simulation and Decision-Support system (LandSDS): Seamlessly integrating system dynamics, agent-based model, and cellular automata," Ecological Modelling, Elsevier, vol. 417(C).
    • Handle: RePEc:eee:ecomod:v:417:y:2020:i:c:s0304380019304326
    DOI: 10.1016/j.ecolmodel.2019.108924
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380019304326
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2019.108924?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yang, Xin & Zheng, Xin-Qi & Lv, Li-Na, 2012. "A spatiotemporal model of land use change based on ant colony optimization, Markov chain and cellular automata," Ecological Modelling, Elsevier, vol. 233(C), pages 11-19.
    2. Liu, Xiaoping & Ou, Jinpei & Li, Xia & Ai, Bin, 2013. "Combining system dynamics and hybrid particle swarm optimization for land use allocation," Ecological Modelling, Elsevier, vol. 257(C), pages 11-24.
    3. R White & G Engelen, 1993. "Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns," Environment and Planning A, , vol. 25(8), pages 1175-1199, August.
    4. Tian, Guangjin & Ouyang, Yun & Quan, Quan & Wu, Jianguo, 2011. "Simulating spatiotemporal dynamics of urbanization with multi-agent systems—A case study of the Phoenix metropolitan region, USA," Ecological Modelling, Elsevier, vol. 222(5), pages 1129-1138.
    5. Jan K. Kazak, 2018. "The Use of a Decision Support System for Sustainable Urbanization and Thermal Comfort in Adaptation to Climate Change Actions—The Case of the Wrocław Larger Urban Zone (Poland)," Sustainability, MDPI, vol. 10(4), pages 1-15, April.
    6. Tong Wang & Jan Kazak & Qi Han & Bauke de Vries, 2019. "A framework for path-dependent industrial land transition analysis using vector data," European Planning Studies, Taylor & Francis Journals, vol. 27(7), pages 1391-1412, July.
    7. Liu, Dongya & Zheng, Xinqi & Wang, Hongbin & Zhang, Chunxiao & Li, Jiayang & Lv, Yongqiang, 2018. "Interoperable scenario simulation of land-use policy for Beijing–Tianjin–Hebei region, China," Land Use Policy, Elsevier, vol. 75(C), pages 155-165.
    8. Yaobin Liu & Lu Dai & Huanhuan Xiong, 2015. "Simulation of urban expansion patterns by integrating auto-logistic regression, Markov chain and cellular automata models," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 58(6), pages 1113-1136, June.
    9. Liu, Dongya & Zheng, Xinqi & Zhang, Chunxiao & Wang, Hongbin, 2017. "A new temporal–spatial dynamics method of simulating land-use change," Ecological Modelling, Elsevier, vol. 350(C), pages 1-10.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yabo Zhao & Dixiang Xie & Xiwen Zhang & Shifa Ma, 2021. "Integrating Spatial Markov Chains and Geographically Weighted Regression-Based Cellular Automata to Simulate Urban Agglomeration Growth: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area," Land, MDPI, vol. 10(6), pages 1-19, June.
    2. Yin Ma & Minrui Zheng & Xinqi Zheng & Yi Huang & Feng Xu & Xiaoli Wang & Jiantao Liu & Yongqiang Lv & Wenchao Liu, 2023. "Land Use Efficiency Assessment under Sustainable Development Goals: A Systematic Review," Land, MDPI, vol. 12(4), pages 1-21, April.
    3. Zhao, Xiang & Cai, Bocheng & He, Jianhua & Kong, Xuesong, 2024. "Identifying potential rural residential areas for land consolidation using a data driven agent-based model," Land Use Policy, Elsevier, vol. 145(C).
    4. Alysha van Duynhoven & Suzana Dragićević, 2021. "Exploring the Sensitivity of Recurrent Neural Network Models for Forecasting Land Cover Change," Land, MDPI, vol. 10(3), pages 1-29, March.
    5. Heng Liu & Lu Zhou & Diwei Tang, 2022. "Urban Expansion Simulation Coupled with Residential Location Selection and Land Acquisition Bargaining: A Case Study of Wuhan Urban Development Zone, Central China’s Hubei Province," Sustainability, MDPI, vol. 15(1), pages 1-20, December.
    6. Qihao Wang & Dongya Liu & Feiyao Gao & Xinqi Zheng & Yiqun Shang, 2023. "A Partitioned and Heterogeneous Land-Use Simulation Model by Integrating CA and Markov Model," Land, MDPI, vol. 12(2), pages 1-20, February.
    7. Li Yuan & Jing Xu & Binrui Feng, 2024. "Evaluation and Prediction of Carbon Storage in the Qinghai-Tibet Plateau by Coupling the GMMOP and PLUS Models," Sustainability, MDPI, vol. 16(13), pages 1-19, July.
    8. Yang Yi & Chen Zhang & Guilian Zhang & Luqi Xing & Qicheng Zhong & Jialin Liu & Yichen Lin & Xiewei Zheng & Na Yang & Hao Sun & Mingchang Shi & Hongzhang Kang, 2021. "Effects of Urbanization on Landscape Patterns in the Middle Reaches of the Yangtze River Region," Land, MDPI, vol. 10(10), pages 1-17, September.
    9. Hao Wang & Yunfeng Hu, 2021. "Simulation of Biocapacity and Spatial-Temporal Evolution Analysis of Loess Plateau in Northern Shaanxi Based on the CA–Markov Model," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    10. Jiang, Xue & Li, Bingxin & Zhao, Hongyu & Zhang, Qiqi & Song, Xiaoya & Zhang, Haoran, 2022. "Examining the spatial simulation and land-use reorganisation mechanism of agricultural suburban settlements using a cellular-automata and agent-based model: Six settlements in China," Land Use Policy, Elsevier, vol. 120(C).
    11. Chasia, Stanley & Olang, Luke O. & Sitoki, Lewis, 2023. "Modelling of land-use/cover change trajectories in a transboundary catchment of the Sio-Malaba-Malakisi Region in East Africa using the CLUE-s model," Ecological Modelling, Elsevier, vol. 476(C).
    12. Dongya Liu & Xinqi Zheng & Lei Zhang, 2021. "Simulation of Spatiotemporal Relationship between COVID-19 Propagation and Regional Economic Development in China," Land, MDPI, vol. 10(6), pages 1-15, June.
    13. Wang, Han & Lu, Siying & Lu, Bo & Nie, Xin, 2021. "Overt and covert: The relationship between the transfer of land development rights and carbon emissions," Land Use Policy, Elsevier, vol. 108(C).
    14. Jingjie Liu & Min Xia, 2023. "Influencing Factors Analysis and Optimization of Land Use Allocation: Combining MAS with MOPSO Procedure," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
    15. Xu, Hongtao & Song, Youcheng & Tian, Yi, 2022. "Simulation of land-use pattern evolution in hilly mountainous areas of North China: A case study in Jincheng," Land Use Policy, Elsevier, vol. 112(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Dongya & Zheng, Xinqi & Zhang, Chunxiao & Wang, Hongbin, 2017. "A new temporal–spatial dynamics method of simulating land-use change," Ecological Modelling, Elsevier, vol. 350(C), pages 1-10.
    2. Liu, Dongya & Zheng, Xinqi & Wang, Hongbin & Zhang, Chunxiao & Li, Jiayang & Lv, Yongqiang, 2018. "Interoperable scenario simulation of land-use policy for Beijing–Tianjin–Hebei region, China," Land Use Policy, Elsevier, vol. 75(C), pages 155-165.
    3. Michel Opelele Omeno & Ying Yu & Wenyi Fan & Tolerant Lubalega & Chen Chen & Claude Kachaka Sudi Kaiko, 2021. "Analysis of the Impact of Land-Use/Land-Cover Change on Land-Surface Temperature in the Villages within the Luki Biosphere Reserve," Sustainability, MDPI, vol. 13(20), pages 1-23, October.
    4. Shivangi S. Somvanshi & Oshin Bhalla & Phool Kunwar & Madhulika Singh & Prafull Singh, 2020. "Monitoring spatial LULC changes and its growth prediction based on statistical models and earth observation datasets of Gautam Budh Nagar, Uttar Pradesh, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 1073-1091, February.
    5. Yan Liu & Yongjiu Feng, 2016. "Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China," Sustainability, MDPI, vol. 8(10), pages 1-16, October.
    6. Selamawit Haftu Gebresellase & Zhiyong Wu & Huating Xu & Wada Idris Muhammad, 2023. "Scenario-Based LULC Dynamics Projection Using the CA–Markov Model on Upper Awash Basin (UAB), Ethiopia," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    7. Zhen Li & Songlin Wu & Shiwen Zhang & Chaojia Nie & Yong Li & Yuanfang Huang, 2020. "Optimization of Land Reuse Structure in Coal Mining Subsided Areas Considering Regional Economic Development: A Case Study in Pei County, China," Sustainability, MDPI, vol. 12(8), pages 1-16, April.
    8. Yang, Xin & Zheng, Xin-Qi & Lv, Li-Na, 2012. "A spatiotemporal model of land use change based on ant colony optimization, Markov chain and cellular automata," Ecological Modelling, Elsevier, vol. 233(C), pages 11-19.
    9. Yaolin Liu & Xuesong Kong & Yanfang Liu & Yiyun Chen, 2013. "Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-14, November.
    10. Yabo Zhao & Dixiang Xie & Xiwen Zhang & Shifa Ma, 2021. "Integrating Spatial Markov Chains and Geographically Weighted Regression-Based Cellular Automata to Simulate Urban Agglomeration Growth: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area," Land, MDPI, vol. 10(6), pages 1-19, June.
    11. Yang, Xin & Zheng, Xin-Qi & Chen, Rui, 2014. "A land use change model: Integrating landscape pattern indexes and Markov-CA," Ecological Modelling, Elsevier, vol. 283(C), pages 1-7.
    12. Anasua Chakraborty & Sujit Sikder & Hichem Omrani & Jacques Teller, 2022. "Cellular Automata in Modeling and Predicting Urban Densification: Revisiting the Literature since 1971," Land, MDPI, vol. 11(7), pages 1-19, July.
    13. Mingruo Chu & Jiayi Lu & Dongqi Sun, 2022. "Influence of Urban Agglomeration Expansion on Fragmentation of Green Space: A Case Study of Beijing-Tianjin-Hebei Urban Agglomeration," Land, MDPI, vol. 11(2), pages 1-19, February.
    14. Gerrit Günther & Thomas Clemen & Rainer Duttmann & Brigitta Schütt & Daniel Knitter, 2021. "Of Animal Husbandry and Food Production—A First Step towards a Modular Agent-Based Modelling Platform for Socio-Ecological Dynamics," Land, MDPI, vol. 10(12), pages 1-25, December.
    15. Ye Zhou & Feng Zhang & Zhenhong Du & Xinyue Ye & Renyi Liu, 2017. "Integrating Cellular Automata with the Deep Belief Network for Simulating Urban Growth," Sustainability, MDPI, vol. 9(10), pages 1-19, October.
    16. Wang, Han & Tian, Fuan & Wu, Jianxian & Nie, Xin, 2023. "Is China forest landscape restoration (FLR) worth it? A cost-benefit analysis and non-equilibrium ecological view," World Development, Elsevier, vol. 161(C).
    17. Guadalupe Azuara García & Efrén Palacios Rosas & Alfonso García-Ferrer & Pilar Montesinos Barrios, 2017. "Multi-Objective Spatial Optimization: Sustainable Land Use Allocation at Sub-Regional Scale," Sustainability, MDPI, vol. 9(6), pages 1-21, June.
    18. Kwok Hung Lau & Booi Hon Kam, 2005. "A Cellular Automata Model for Urban Land-Use Simulation," Environment and Planning B, , vol. 32(2), pages 247-263, April.
    19. Yang, Yuanyuan & Bao, Wenkai & Liu, Yansui, 2020. "Scenario simulation of land system change in the Beijing-Tianjin-Hebei region," Land Use Policy, Elsevier, vol. 96(C).
    20. Shuangqing Sheng & Wei Song & Hua Lian & Lei Ning, 2022. "Review of Urban Land Management Based on Bibliometrics," Land, MDPI, vol. 11(11), pages 1-25, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:417:y:2020:i:c:s0304380019304326. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.