A space optimization model of water resource conservation forest in Dongting Lake based on improved PSO

Jianjun, 李建军 Li; Zhang, Huiru; Shuai, 刘帅 Liu; Zhufang, 邝祝芳 Kuang; Chuanli, 王传立 Wang; Hao, 臧颢 Zang; Xupeng, 曹旭鹏 Cao

doi:10.5846/stxb201207281072

Cited by 6 publications

(1 citation statement)

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“…There are also examples of the application of this algorithm in forest management. For example, Izquierdo uses particle swarm optimization to solve the problem of forest fire-fighting drone assignment [14]; Bui D T uses the GIS neuro-fuzzy inference system to establish a forest fire model and uses particle swarm optimization (PSO) to optimize the model parameters [15]; Li Jianjun solved the spatial optimization problem of water conservation forest in Dongting Lake by particle swarm optimization [16] and Zheng Peng solved the problem of forest harvesting planning by particle swarm optimization [17]. From the research results, the particle swarm optimization algorithm has certain advantages for solving the nonlinear and multi-objective problems existing in forest management.…”

Section: Introductionmentioning

confidence: 99%

Mining and quantifying the optimal DBH range of loblolly pine with improved particle algorithm

Qing¹,

Liu²,

Deng³

et al. 2022

NNW

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In order to fully understand the objective law of height and DBH growth of loblolly pine trees and exploring the best DBH (Diameter at Breast Height) Range for loblolly pine tree height growth, 13 340 loblolly pines with initial DBH between 1 inch and 7 inch were selected from Alabama as research objects, and statistics on its growth from 2000 to 2015. Because particle swarm optimization (PSO) is suitable for solving non-linear problems, the optimal DBH of loblolly pine is transformed into the optimization problem of PSO, which quantifies the optimal DBH range of loblolly pine at different scales by mapping strategy. The experimental results show that the range of the breast diameter suitable for the high growth of the pine tree is concentrated between 3.7 inch and 7.3 inch. The height of the pine tree begins to enter a period of rapid growth from a breast diameter of 3.9 inch (ą0.2 inch ). The tree height growth rate reached a maximum at a breast diameter of 6.4 inch (ą0.6 inch ), and the tree height entered a slow growth period after the breast diameter of 11.92 inch (ą0.3 inch). In general, when the breast diameter exceeds 15.26 inch (ą0.3 inch), the height of the pine tree stops growing.

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Section: Introductionmentioning

confidence: 99%

Mining and quantifying the optimal DBH range of loblolly pine with improved particle algorithm

Qing¹,

Liu²,

Deng³

et al. 2022

NNW

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A novel model to evaluate spatial structure in thinned conifer-broadleaved mixed natural forests

et al. 2023

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In order to ensure the effective analysis and reconstruction of forests, it is key to ensure the quantitative description of their spatial structure. In this paper, a distance model for the optimal stand spatial structure based on weighted Voronoi diagrams is proposed. In particular, we provide a novel methodological model for the comprehensive evaluation of the spatial structure of forest stands in natural mixed conifer-broadleaved forests and the formulation of management decision plans. The applicability of the rank evaluation and the optimal solution distance model are compared and assessed for different standard sample plots of natural mixed conifer-broadleaved forests. The effect of crown width on the spatial structure unit of the trees is observed to be higher than that of the diameter at breast height. Moreover, the influence of crown length is greater than that of tree height. There are nine possible spatial structure units determined by the weighted Voronoi diagram for the number of neighboring trees in the central tree, with an average intersection of neighboring crowns reaching 80%. The rank rating of natural forest sample plots is correlated with the optimal solution distance model, and their results are generally consistent for natural forests. However, the rank rating is not able to provide a quantitative assessment. The optimal solution distance model is observed to be more comprehensive than traditional methods for the evaluation of the spatial structure of forest stands. It can effectively reflect the trends in realistic stand spatial structure factors close to or far from the ideal structure point, and accurately assesses the forest spatial structure. The proposed optimal solution distance model improves the integrated evaluation of the spatial structure of forest stands and provides solid theoretical and technical support for sustainable forest management.

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Extraction of the spatial structure of Chinese fir plantations stands based on unmanned aerial vehicle and its effect on AGB

Huang,

Chen,

Tan

et al. 2024

Forest Ecology and Management

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A space optimization model of water resource conservation forest in Dongting Lake based on improved PSO

Cited by 6 publications

References 0 publications

Mining and quantifying the optimal DBH range of loblolly pine with improved particle algorithm

Mining and quantifying the optimal DBH range of loblolly pine with improved particle algorithm

A novel model to evaluate spatial structure in thinned conifer-broadleaved mixed natural forests

Extraction of the spatial structure of Chinese fir plantations stands based on unmanned aerial vehicle and its effect on AGB

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