Structural Characteristics of Coupling Network of Grassland Landscape Patches in Baotou City
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    Abstract:

    Baotou City of Inner Mongolia was selected as the study area. The Landsat OLI image of Baotou City in summer of 2016 was selected as the research data for interpretation. Totally 28009 grassland landscape patches were extracted. The normalized difference vegetation index (NDVI) was calculated from the original image. According to the NDVI of the study area, the grassland landscape was divided into 12 levels. Based on 12 levels of grassland landscape, a network of grassland landscapes was constructed. At the landscape level, totally 25 indices were selected, and at the type level, 24 indices were selected. Using these indices, the spatial pattern, shape characteristics and degree of aggregation of the grassland landscape were analyzed. The results showed that the landscape similarity percentage index and the distribution and the sidebyside index were higher on the landscape scale, and the landscape segmentation index was lower in the whole territory of Baotou City. The proportion of grades 1~7 was high, the density of landscape patches was low, and the aggregation index was high. The proportion of grades 8~12 was low, the landscape segmentation index was high, the landscape was broken and the connectivity was poor on the type scale. The degree of utilization and degree distribution, average path length and clustering coefficient were used to analyze the characteristics of grassland landscape network. Five nodes with a degree of 6 were found in the grassland landscape network. The maximum value was 8, with 2 nodes, and the average path length was 1.6061. The results showed that the grassland landscape network had obvious nonuniformity. The research results had practical significance for the structural optimization of the grassland landscape in Baotou City and the stable development of the structure.

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History
  • Received:January 04,2019
  • Revised:
  • Adopted:
  • Online: March 10,2019
  • Published: March 10,2019
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