IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i13p5777-d1430246.html
   My bibliography  Save this article

Landscape Ecological Security of the Lijiang River Basin in China: Spatiotemporal Evolution and Pattern Optimization

Author

Listed:
  • Jinlong Hu

    (College of Tourism & Landscape Architecture, Guilin University of Technology, Guilin 541004, China
    Institute of Guangxi Tourism Industry, Guilin University of Technology, Guilin 541004, China)

  • Guo Qing

    (College of Tourism & Landscape Architecture, Guilin University of Technology, Guilin 541004, China)

  • Yingxue Wang

    (College of Tourism & Landscape Architecture, Guilin University of Technology, Guilin 541004, China
    Institute of Guangxi Tourism Industry, Guilin University of Technology, Guilin 541004, China)

  • Sicheng Qiu

    (College of Tourism & Landscape Architecture, Guilin University of Technology, Guilin 541004, China)

  • Nan Luo

    (College of Tourism & Landscape Architecture, Guilin University of Technology, Guilin 541004, China
    Institute of Guangxi Tourism Industry, Guilin University of Technology, Guilin 541004, China)

Abstract

The ecological security of karst basins is receiving increased attention as a result of intense human activity and climate change. However, how ecological security evolves in spacetime and the optimization of ecological security patterns still remain unclear. This study developed a methodological framework for evaluating ecological security and optimizing ecological security patterns of the Lijiang River Basin (LRB). The 3S technology was used to analyze the current status and evolution characteristics of landscape ecological security in the LRB from 1990 to 2020. This study identified and optimized ecological security patterns by adhering to the basic paradigm of “source identification–resistance surface construction–corridor extraction–node determination”. The results showed that the overall ecological security of the LRB was at a medium to high level, with an index showing an initial increase followed by a decrease. The LRB exhibited 24 ecological pinch points, 74 ecological corridors, 30 ecological sources, and 6 ecological barrier points. The predominant landscape types found within these pinch points and barrier points encompass forests, cultivated land, and urban areas. A scheme of “three cores, two belts, and six zones” was proposed to optimize the ecological security pattern of the LRB. This study provides a theoretical basis and technical references for the integrated management of the rivers, grasslands, farmlands, mountains, lakes, forests, and sands in the LRB, as well as for the ecological restoration of other regions.

Suggested Citation

  • Jinlong Hu & Guo Qing & Yingxue Wang & Sicheng Qiu & Nan Luo, 2024. "Landscape Ecological Security of the Lijiang River Basin in China: Spatiotemporal Evolution and Pattern Optimization," Sustainability, MDPI, vol. 16(13), pages 1-22, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:13:p:5777-:d:1430246
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/13/5777/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/13/5777/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rachel Guillain & Julie Le Gallo, 2010. "Agglomeration and Dispersion of Economic Activities in and around Paris: An Exploratory Spatial Data Analysis," Environment and Planning B, , vol. 37(6), pages 961-981, December.
    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. Jae Ik Kim & Chang Hwan Yeo & Jin-Hwi Kwon, 2014. "Spatial change in urban employment distribution in Seoul metropolitan city: clustering, dispersion and general dispersion," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 18(3), pages 355-372, November.
    2. Koech Cheruiyot, 2022. "Detecting spatial economic clusters using kernel density and global and local Moran's I analysis in Ekurhuleni metropolitan municipality, South Africa," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(2), pages 307-327, April.
    3. Arauzo-Carod, Josep-Maria & Manjón-Antolín, Miguel & Martínez , Óscar, 2015. "The Relocation of R&D Establishments in France: An Empirical Analysis," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 33, pages 97-119.
    4. Marcon, Eric & Puech, Florence, 2017. "A typology of distance-based measures of spatial concentration," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 56-67.
    5. Sugam Agarwal & Smruti Ranjan Behera, 2022. "Geographical concentration of knowledge and technology-intensive industries in India: empirical evidence from establishment-level analysis," Indian Economic Review, Springer, vol. 57(2), pages 513-552, December.
    6. Boubaker, Sabri & Derouiche, Imen & Lasfer, Meziane, 2015. "Geographic location, excess control rights, and cash holdings," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 24-37.
    7. Domenica Panzera & Alfredo Cartone & Paolo Postiglione, 2022. "New evidence on measuring the geographical concentration of economic activities," Papers in Regional Science, Wiley Blackwell, vol. 101(1), pages 59-79, February.
    8. Pontarollo, Nicola & Serpieri, Carolina, 2020. "A composite policy tool to measure territorial resilience capacity," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    9. Frank P. van den Heuvel & Peter W. de Langen & Karel H. van Donselaar & Jan C. Fransoo, 2014. "Identification of Employment Concentration Areas," European Planning Studies, Taylor & Francis Journals, vol. 22(1), pages 204-226, January.
    10. Reinhold Kosfeld & Mirko Titze, 2014. "Benchmark Value Added Chains and Regional Clusters in German R&D Intensive Industries," MAGKS Papers on Economics 201437, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    11. Mirko Titze & Matthias Brachert & Alexander Kubis, 2014. "Actors and Interactions—Identifying the Role of Industrial Clusters for Regional Production and Knowledge Generation Activities," Growth and Change, Wiley Blackwell, vol. 45(2), pages 163-190, June.
    12. Mariateresa Ciommi & Francesco M. Chelli & Luca Salvati, 2019. "Integrating parametric and non-parametric multivariate analysis of urban growth and commuting patterns in a European metropolitan area," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(2), pages 957-979, March.
    13. Luca Salvati & Giuseppe Venanzoni & Pere Serra & Margherita Carlucci, 2016. "Scattered or polycentric? Untangling urban growth in three southern European metropolitan regions through exploratory spatial data analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(1), pages 1-29, July.
    14. Xiaoxiang Zhang & Jing Yao & Katarzyna Sila-Nowicka & Chonghui Song, 2021. "Geographic concentration of industries in Jiangsu, China: a spatial point pattern analysis using micro-geographic data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 66(2), pages 439-461, April.
    15. Vassilis Tselios & Demetris Stathakis, 2020. "Exploring regional and urban clusters and patterns in Europe using satellite observed lighting," Environment and Planning B, , vol. 47(4), pages 553-568, May.
    16. Mounir Amdaoud & Giuseppe Arcuri & Nadine Levratto, 2021. "Are regions equal in adversity? A spatial analysis of spread and dynamics of COVID-19 in Europe," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(4), pages 629-642, June.
    17. Min-Yang Lee & Cameron Spier & Andrew Carr-Harris & Sharon Benjamin, 2017. "Geographic Concentration of the Atlantic Sea Scallop Fishery," The Review of Regional Studies, Southern Regional Science Association, vol. 47(1), pages 25-46, Winter.
    18. Eri Yamada & Tetsu Kawakami, 2015. "Assessing dynamic externalities from a cluster perspective: the case of the motor metropolis in Japan," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(1), pages 269-298, January.
    19. Kossowski Tomasz & Hauke Jan, 2018. "SPAG: A New Measure of Spatial Agglomeration. Theoretical Background and Empirical Examples," Quaestiones Geographicae, Sciendo, vol. 37(4), pages 33-42, December.
    20. Yu, Haitao & Jiao, Junfeng & Houston, Eric & Peng, Zhong-Ren, 2018. "Evaluating the relationship between rail transit and industrial agglomeration: An observation from the Dallas-fort worth region, TX," Journal of Transport Geography, Elsevier, vol. 67(C), pages 33-52.

    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:16:y:2024:i:13:p:5777-:d:1430246. 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.