IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i5p2572-d756637.html
   My bibliography  Save this article

Influence of Environmental Factors on the Site Selection and Layout of Ancient Military Towns (Zhejiang Region)

Author

Listed:
  • Lifeng Tan

    (School of Architecture and Urban Planning, Tianjin Chengjian University, Tianjin 300072, China
    These authors contributed equally to this work.)

  • Huanjie Liu

    (School of Architecture, Tianjin University, Tianjin 300072, China
    These authors contributed equally to this work.)

  • Jiayi Liu

    (School of Architecture, Tianjin University, Tianjin 300072, China
    School of Marine Science and Technology, Tianjin University, Tianjin 300072, China)

  • Jiayin Zhou

    (School of Architecture, Tianjin University, Tianjin 300072, China)

  • Pengfei Zhao

    (School of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, China)

  • Yukun Zhang

    (School of Architecture, Tianjin University, Tianjin 300072, China)

  • Shuaishuai Zhao

    (School of Architecture, Tianjin University, Tianjin 300072, China)

  • Shenge Shen

    (School of Architecture, Tianjin University, Tianjin 300072, China)

  • Tong Li

    (School of Architecture, Tianjin University, Tianjin 300072, China)

  • Yinggang Wang

    (School of Architecture, Tianjin University, Tianjin 300072, China)

  • Linping Yang

    (School of Architecture, Tianjin University, Tianjin 300072, China)

Abstract

There are many subjective inferences regarding environment-related studies in modern studies of ancient military defense heritage, and the objective quantitative analysis of citadel site selection and layout has become the key to interpreting the environmental adaptability of citadels under defense strategies. Based on this, it has been proposed in this research that the site selection of ancient military citadels in a specific region (Zhejiang) has environmental adaptability characteristics. Firstly, an elevated hydrological overlay model was established by predicting and graphically verifying the ancient hydrological thresholds through geospatial analysis strategies. Secondly, the hydrological and topographical indicators of the regional environment where the military citadel is located were digitally extracted. Finally, correlation and weight influence calculations were performed for different environmental data. The environmental adaptability characteristics of the site layout of the Ming dynasty-era Zhejiang coastal defense military citadel, based on military defense needs, were obtained. In this way, we promote digital technology for the excavation, conservation and sustainable use of heritage resources.

Suggested Citation

  • Lifeng Tan & Huanjie Liu & Jiayi Liu & Jiayin Zhou & Pengfei Zhao & Yukun Zhang & Shuaishuai Zhao & Shenge Shen & Tong Li & Yinggang Wang & Linping Yang, 2022. "Influence of Environmental Factors on the Site Selection and Layout of Ancient Military Towns (Zhejiang Region)," Sustainability, MDPI, vol. 14(5), pages 1-20, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2572-:d:756637
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/5/2572/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/5/2572/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lifeng Tan & Huanjie Liu & Jiayin Zhou & Yukun Zhang & Jiayi Liu & Shenge Shen & Tong Li & Chaonan Wang & Wanjing Lin & Daqing Gong, 2021. "A GIS-Based Modeling Approach for Determining the Efficiency of the Traffic System between Ancient Military Castles," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-13, October.
    2. José Balsa-Barreiro & Alfredo J. Morales & Rubén C. Lois-González & Ãtila Bueno, 2021. "Mapping Population Dynamics at Local Scales Using Spatial Networks," Complexity, Hindawi, vol. 2021, pages 1-14, May.
    3. Albert-László Barabási, 2005. "The origin of bursts and heavy tails in human dynamics," Nature, Nature, vol. 435(7039), pages 207-211, May.
    Full references (including those not matched with items on IDEAS)

    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. Jingya Tang & Lichun Sui, 2022. "Geodetector-Based Livability Analysis of Potential Resettlement Locations for Villages in Coal Mining Areas on the Loess Plateau of China," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    2. Anzhi Sheng & Qi Su & Aming Li & Long Wang & Joshua B. Plotkin, 2023. "Constructing temporal networks with bursty activity patterns," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. He, Yifan & Zhao, Chen & Zeng, An, 2022. "Ranking locations in a city via the collective home-work relations in human mobility data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    4. Lu, Xi & Mo, Hongming & Deng, Yong, 2015. "An evidential opinion dynamics model based on heterogeneous social influential power," Chaos, Solitons & Fractals, Elsevier, vol. 73(C), pages 98-107.
    5. Wang, Cheng-Jun & Wu, Lingfei, 2016. "The scaling of attention networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 196-204.
    6. Simon DeDeo, 2016. "Conflict and Computation on Wikipedia: A Finite-State Machine Analysis of Editor Interactions," Future Internet, MDPI, vol. 8(3), pages 1-23, July.
    7. Jing Yang & Yingwu Chen, 2011. "Fast Computing Betweenness Centrality with Virtual Nodes on Large Sparse Networks," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-5, July.
    8. Baltakys, Kęstutis & Kanniainen, Juho & Saramäki, Jari & Kivelä, Mikko, 2023. "Investor trade allocation patterns in stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 210(C), pages 191-209.
    9. Diao, Su-Meng & Liu, Yun & Zeng, Qing-An & Luo, Gui-Xun & Xiong, Fei, 2014. "A novel opinion dynamics model based on expanded observation ranges and individuals’ social influences in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 220-228.
    10. Zhou, Bin & Xie, Jia-Rong & Yan, Xiao-Yong & Wang, Nianxin & Wang, Bing-Hong, 2017. "A model of task-deletion mechanism based on the priority queueing system of Barabási," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 415-421.
    11. Chen, Ning & Zhu, Xuzhen & Chen, Yanyan, 2019. "Information spreading on complex networks with general group distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 671-676.
    12. Zhenpeng Li & Xijin Tang & Zhenjie Hong, 2022. "Collective attention dynamic induced by novelty decay," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(8), pages 1-11, August.
    13. C Ben Gibson & Norbou Buchler & Blaine Hoffman & Claire-Genevieve La Fleur, 2019. "Participation shifts explain degree distributions in a human communications network," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-13, May.
    14. Vladimir Shepelev & Aleksandr Glushkov & Ivan Slobodin & Yuri Cherkassov, 2023. "Measuring and Modelling the Concentration of Vehicle-Related PM2.5 and PM10 Emissions Based on Neural Networks," Mathematics, MDPI, vol. 11(5), pages 1-23, February.
    15. Koen Zwet & Ana I. Barros & Tom M. Engers & Peter M. A. Sloot, 2022. "Emergence of protests during the COVID-19 pandemic: quantitative models to explore the contributions of societal conditions," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    16. Huan-Kai Peng & Hao-Chih Lee & Jia-Yu Pan & Radu Marculescu, 2016. "Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-21, January.
    17. Qianqian Liu & Qun Wang, 2017. "A comparative study on uncooperative search models in survivor search and rescue," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(2), pages 843-857, November.
    18. Sur, Souvik & Ganguly, Niloy & Mukherjee, Animesh, 2015. "Attack tolerance of correlated time-varying social networks with well-defined communities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 98-107.
    19. Kota Yamada & Atsunori Kanemura, 2020. "Simulating bout-and-pause patterns with reinforcement learning," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-21, November.
    20. Muaz Niazi & Amir Hussain, 2011. "Agent-based computing from multi-agent systems to agent-based models: a visual survey," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 479-499, 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:gam:jsusta:v:14:y:2022:i:5:p:2572-:d:756637. 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.