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FOREST RESOURCES WANAGEMENT ›› 2023, Vol. 0 ›› Issue (4): 27-35.doi: 10.13466/j.cnki.lyzygl.2023.04.004

• Scientific Research • Previous Articles     Next Articles

A Study on Forest Stand Spatial Structure Intelligent Optimization Based on Voronoi Spatial Unit

LIU Xin1(), HUANG Lang2, QING Dongsheng1,2, LI Jianjun2()   

  1. 1. Hunan Applied Technology University,Changde,Hunan 415100,China
    2. Central South University of Forestry and Technology,Changsha 410004,China
  • Received:2023-06-12 Revised:2023-07-08 Online:2023-08-28 Published:2023-10-16

Abstract:

Using the Voronoi method to determine the target tree and neighbourhood tree has the problems of inaccurate edge correction and uncertainty of threshold size,which are not conducive to the quantitative description of the spatial structure of forest stand.To address these problems,this study set all the forest trees in Voronoi units that are less than 0.5 m from the sample plot boundary line and incomplete as non-objective trees,and introduced a regulation threshold Rmax for the distance between the target tree and neighbourhood tree to correct the problem of unreasonable selection of target tree and neighbourhood tree in the processing of edge effects in Voronoi spatial units.Based on the modified Voronoi spatial unit,a multi-objective ecological harvesting scheme was constructed and intelligently optimized by an ant colony algorithm.The results showed that the fitness functions of the four sample plots,M4,M8,M14 and M17,which had relatively poor stand spatial structure conditions among the 20 sample plots before regulation,were improved by 0.72,0.92,0.93 and 0.86,respectively,after regulation by simulated harvesting,which proved that the scheme has a better effect on optimizing the spatial structure of forest stand,and can provide a supportive tool for forest management decisions.

Key words: Voronoi, forest stand spatial unit, ant colony algorithm, intelligent optimization

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