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Landscape Pattern Optimization of Qionghai City Based on GIS

  • Xiangyang LI ,
  • Jiang WU ,
  • Zhaobai WU
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  • Central South Inventory and Planning Institute of National Forestry and Grassland Administation,Changsha 410014,Hunan,China

Received date: 2019-02-14

  Revised date: 2019-03-26

  Online published: 2020-09-22

Abstract

Landscape pattern optimization is an effective method to promote the regional sustainable development.This paper,taking Qionghai city as an example,uses spatial analysis model of GIS and cluster analysis and accumulative cost distance model for carrying out the analysis of landscape pattern optimization so as to provide reference for the local ecological construction.The results show that:(1) Using cluster analysis to choose a suitable reference for the selection of ecological sources in Qionghai city,and the landscape component construction is the most suitable one when its scale of grid is 800m.There are 65 ecological sources in Qionghai city,and the main influencing factors of space distribution of ecological sources are man-made jamming and landform.(2) Ecological resistance surface is clustered into 5 regions,which include low resistance region,light low resistance region,moderate resistance region,light high resistance region and high resistance region.Suitable measures are taken to construct each region.(3) There are 136 ecological corridors and 136 ecological nodes in Qionghai city,and they are combined with ecological sources to form a ecological network.With Wanquan River as the frontier,ecological corridors and ecological nodes are distributed in northeast,middle part and south of Qionghai city.Their stroma is farm land,forest land or garden plot.According to their stroma and surrounding environment we should take different construction and regulatory motheds.

Cite this article

Xiangyang LI , Jiang WU , Zhaobai WU . Landscape Pattern Optimization of Qionghai City Based on GIS[J]. Forest and Grassland Resources Research, 2019 , 0(2) : 147 -151 . DOI: 10.13466/j.cnki.lyzygl.2019.02.022

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