IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i8p1370-d106832.html
   My bibliography  Save this article

A Spatial-Territorial Reorganization Model of Rural Settlements Based on Graph Theory and Genetic Optimization

Author

Listed:
  • Yan Mao

    (School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

  • Yanfang Liu

    (School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
    Key Laboratory of Geographic Information System, Ministry of Education, Wuhan University, Wuhan 430079, China)

  • Haofeng Wang

    (School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

  • Wei Tang

    (School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

  • Xuesong Kong

    (School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

Abstract

Rural China has experienced rapid urbanization and industrialization, accompanied with rural–urban migration since 1978. This tremendous transition has caused a series of negative consequences, necessitating a spatial-territorial reorganization of rural settlements. Previous studies on the restructuring of rural settlements are insufficient for inter-settlement connection consideration and practical and dynamic decision-making techniques. To overcome these concerns, a dynamic spatial-territorial reorganization model (SRM) of rural settlement is proposed herein based on graph theory and genetic algorithm (GA). The model involves two parts. In Part 1, consolidated settlements are identified according to the socio-economic network performance under four types of attack. In Part 2, GA model is repeatedly executed to scientifically resettle consolidated settlements into nearby townships or central settlements with objectives of suitability, compactness, and local connectivity under the control of the constraints. This paper presents an application of SRM to Chengui Town, Hubei Province. Empirical results suggest that: (1) removing settlements in order of node degree is the least efficient way to destroy the entire functional system; and (2) the proposed model can yield satisfactory solutions in terms of spatial reorganization of settlements. The SRM may also serve as a valuable reference for planners in devising plans and making decisions.

Suggested Citation

  • Yan Mao & Yanfang Liu & Haofeng Wang & Wei Tang & Xuesong Kong, 2017. "A Spatial-Territorial Reorganization Model of Rural Settlements Based on Graph Theory and Genetic Optimization," Sustainability, MDPI, vol. 9(8), pages 1-18, August.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:8:p:1370-:d:106832
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/8/1370/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/9/8/1370/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    2. Fotakis, Dimitris G. & Sidiropoulos, Epameinondas & Myronidis, Dimitriοs & Ioannou, Kostas, 2012. "Spatial genetic algorithm for multi-objective forest planning," Forest Policy and Economics, Elsevier, vol. 21(C), pages 12-19.
    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. Ziyan Wang & Cheng Wang & Zehui Jiang & Tao Hu & Wenjing Han & Chang Zhang & Jiali Jin & Kaiyue Wei & Jiao Zhao & Xinyu Wang, 2020. "Relationship between Rural Settlements’ Plant Communities and Environmental Factors in Hilly Area of Southeast China," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    2. Liu, Lun & Gao, Xuesong & Zhuang, Jiexin & Wu, Wen & Yang, Bo & Cheng, Wei & Xiao, Pengfei & Yao, Xingzhu & Deng, Ouping, 2020. "Evaluating the lifestyle impact of China’s rural housing land consolidation with locational big data: A study of Chengdu," Land Use Policy, Elsevier, vol. 96(C).
    3. Yue Peng & Hui Qiu & Xinlu Wang, 2023. "The Influence of Spatial Functions on the Public Space System of Traditional Settlements," Sustainability, MDPI, vol. 15(11), pages 1-26, May.
    4. Sungsoo Yoon & Youngjoo Moon & Jinah Jeong & Chan-Ryul Park & Wanmo Kang, 2021. "A Network-Based Approach for Reducing Pedestrian Exposure to PM 2.5 Induced by Road Traffic in Seoul," Land, MDPI, vol. 10(10), pages 1-14, October.
    5. Bon-Gang Hwang & Ming Shan, 2018. "Management Strategies and Innovations: Important Roles to Sustainable Construction," Sustainability, MDPI, vol. 10(3), pages 1-3, February.
    6. Vasco Barbosa & Inés Santé-Riveira & Rafael Crecente-Maseda & Carlos Díaz Redondo & Juan Porta Trinidad & Jorge Parapar López & Ramón Doallo Biempica & José Ambrósio Ferreira Neto, 2022. "A New Spatial Criteria Method to Delimit Rural Settlements towards Boundaries Equity: Land Use Optimization for Decision Making in Galicia, NW Spain," Land, MDPI, vol. 11(6), pages 1-19, May.
    7. Tian Tian & Stijn Speelman, 2021. "Pursuing Development behind Heterogeneous Ideologies: Review of Six Evolving Themes and Narratives of Rural Planning in China," Sustainability, MDPI, vol. 13(17), pages 1-16, September.
    8. Libang Ma & Xiaodong Guo & Yaya Tian & Yongli Wang & Meimei Chen, 2017. "Micro-Study of the Evolution of Rural Settlement Patterns and Their Spatial Association with Water and Land Resources: A Case Study of Shandan County, China," Sustainability, MDPI, vol. 9(12), pages 1-18, December.
    9. Su, Kangchuan & Hu, Baoqing & Shi, Kaifang & Zhang, Zhongxun & Yang, Qingyuan, 2019. "The structural and functional evolution of rural homesteads in mountainous areas: A case study of Sujiaying village in Yunnan province, China," Land Use Policy, Elsevier, vol. 88(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. Sanjeev Goyal & Fernando Vega-Redondo, 2000. "Learning, Network Formation and Coordination," Econometric Society World Congress 2000 Contributed Papers 0113, Econometric Society.
    2. Quayle, A.P. & Siddiqui, A.S. & Jones, S.J.M., 2006. "Preferential network perturbation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 823-840.
    3. Chen, Lei & Yue, Dong & Dou, Chunxia, 2019. "Optimization on vulnerability analysis and redundancy protection in interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1216-1226.
    4. Bálint Mészáros & István Simon & Zsuzsanna Dosztányi, 2009. "Prediction of Protein Binding Regions in Disordered Proteins," PLOS Computational Biology, Public Library of Science, vol. 5(5), pages 1-18, May.
    5. Irina Rish & Guillermo Cecchi & Benjamin Thyreau & Bertrand Thirion & Marion Plaze & Marie Laure Paillere-Martinot & Catherine Martelli & Jean-Luc Martinot & Jean-Baptiste Poline, 2013. "Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-15, January.
    6. Wang, Zhuoyang & Chen, Guo & Hill, David J. & Dong, Zhao Yang, 2016. "A power flow based model for the analysis of vulnerability in power networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 105-115.
    7. Bellingeri, Michele & Cassi, Davide & Vincenzi, Simone, 2014. "Efficiency of attack strategies on complex model and real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 174-180.
    8. Bech, Morten L. & Atalay, Enghin, 2010. "The topology of the federal funds market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5223-5246.
    9. Valentini, Luca & Perugini, Diego & Poli, Giampiero, 2007. "The “small-world” topology of rock fracture networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 323-328.
    10. Enrico Zio & Giovanni Sansavini, 2011. "Component Criticality in Failure Cascade Processes of Network Systems," Risk Analysis, John Wiley & Sons, vol. 31(8), pages 1196-1210, August.
    11. Ryan M. Hynes & Bernardo S. Buarque & Ronald B. Davies & Dieter F. Kogler, 2020. "Hops, Skip & a Jump - The Regional Uniqueness of Beer Styles," Working Papers 202013, Geary Institute, University College Dublin.
    12. Pi, Xiaochen & Tang, Longkun & Chen, Xiangzhong, 2021. "A directed weighted scale-free network model with an adaptive evolution mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    13. Lenore Newman & Ann Dale, 2007. "Homophily and Agency: Creating Effective Sustainable Development Networks," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 9(1), pages 79-90, February.
    14. Aybike Ulusan & Ozlem Ergun, 2018. "Restoration of services in disrupted infrastructure systems: A network science approach," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-28, February.
    15. Yang, Hyeonchae & Jung, Woo-Sung, 2016. "Structural efficiency to manipulate public research institution networks," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 21-32.
    16. Deng, Ye & Wu, Jun & Tan, Yue-jin, 2016. "Optimal attack strategy of complex networks based on tabu search," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 74-81.
    17. Blagus, Neli & Šubelj, Lovro & Bajec, Marko, 2012. "Self-similar scaling of density in complex real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2794-2802.
    18. Alexander Shiroky & Andrey Kalashnikov, 2021. "Mathematical Problems of Managing the Risks of Complex Systems under Targeted Attacks with Known Structures," Mathematics, MDPI, vol. 9(19), pages 1-11, October.
    19. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    20. Zhao, Jiuhua & Liu, Qipeng & Wang, Lin & Wang, Xiaofan, 2017. "Competitive seeds-selection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 240-248.

    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:gam:jsusta:v:9:y:2017:i:8:p:1370-:d:106832. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.