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Chinese Journal of Applied Ecology ›› 2020, Vol. 31 ›› Issue (10): 3579-3588.doi: 10.13287/j.1001-9332.202010.014

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Representation, analysis and application of landscape graph based on graph theory

SONG Li-li1, QIN Ming-zhou2, ZHANG Peng-yan2*, XIA Yi-fei1, MA Jie1, CAO Wei1   

  1. 1College of Horticulture and Landscape, Henan Institute of Science and Technology, Xinxiang 453003, Henan, China;
    2College of Environment and Planning, Henan University, Kaifeng 475004, Henan, China
  • Received:2020-05-02 Accepted:2020-07-29 Online:2020-10-15 Published:2021-04-15
  • Contact: * E-mail: pengyanzh@henu.edu.cn
  • Supported by:
    National Natural Science Foundation of China (41901237) and the Key Scientific Research Projects of Higher Education Institutions in Henan Province (19B170004).

Abstract: Landscape structure and spatial pattern are the core issues in landscape ecology. The application of graph theory provides a research framework for landscape pattern analysis. Landscape graph based on graph theory is gradually applied to the connectivity modeling of biodiversity conservation and decision support of landscape planning. The representation, analysis and application of landscape graph have become a hot topic in conservation biology and landscape ecology. In this review, we first introduced the graph theory basis of landscape map. Based on the Scopus database, 257 published journal papers with the words “landscape graph”, “connectivity” and “network” in titles, abstracts, and keywords from 1993 to 2019 were retrieved. We analyzed the research progress and development trend of this field from the aspects of annual published papers, journal sources, research areas, research institutions and landscape types involved. The results showed that before 2017, the number of journal papers published showed an overall increasing trend, and after 2017, the annual number of published papers decreased year by year. The main research forces were concentrated in United States, France, Canada, and China, contributing to 86.8% of the total published papers. Most of the research results were published in “Landscape Ecology”, “Landscape and Urban Planning”, and “Biological Conservation”. In the research content, the representation of landscape graph mainly included the definition of nodes, the measurement of edges and the simulation of landscape. The analysis of landscape graph involved analysis index and landscape graph partitioning. This study mainly focused on the application of landscape graph in science and practice, including biodiversity conservation, landscape (ecological network) planning and management, the assessment of landscape impacts. Landscape graph based on graph theory influences conservation science and planning practitioners by helping understand landscape connectivity changes, animal behavior and habitat conservation. The impact of graph theory on conservation science and planning comes from the rich theoretical basis and mature research methods. Landscape graph based on graph theory provides a springboard for ecological understanding of landscape structure and pattern, and is an important tool for global researchers and practitioners.

Key words: graph theory, landscape graph, connectivity, ecological network