Forest and Grassland Resources Research >
Autocorrelation Analysis of Quantitative Index of Stand Spatial Structure Based on Moran's I
Received date: 2021-12-01
Revised date: 2021-12-29
Online published: 2022-03-31
In order to study the autocorrelation of spatial structure indexes between object trees and adjacent trees in stand spatial unit,the spatial logical relationship between object trees and adjacent trees was analyzed.Twenty five 20m×20m sample plots were set up in Daweishan Nature Reserve,Wuyunjie Nature Reserve and Lutou Forest Farm,the forest spatial unit based on Voronoi diagram was constructed,the adjacent trees of each object forest were determined,and the mixing degree,open ratio,DBH size ratio and competition index were selected as the quantitative indexes of forest spatial structure,and the values of each index were calculated. Finally,combined with the basic principle of global Moran's I index,the autocorrelation analysis scheme of stand spatial structure unit index was constructed to analyze the stand in the study sample plot.The results showed that the stand in the study area was a medium mixed forest,and the trees in this area were in a medium crowded state. There were great differences in DBH distribution between the object trees in the study area and the adjacent trees in its spatial unit,and the competition between trees was relatively obvious.From the perspective of spatial relationship,the mixing degree and open ratio of trees in the study area were positively correlated with their adjacent trees in space,and logically showed aggregation;The DBH size ratio and competition index of trees were negatively correlated with their adjacent trees in space,which was logically discrete. In addition,the spatial relationship between the trees in the survey area and their adjacent trees was mainly competition. The mixing degree and competition index of the trees in the stand may be the main spatial indicators leading to the heterogeneity between them and the surrounding adjacent trees.
Dongsheng QING , Jinxiang PENG , Jianjun LI , Qiaoling DENG , Shuai LIU . Autocorrelation Analysis of Quantitative Index of Stand Spatial Structure Based on Moran's I[J]. Forest and Grassland Resources Research, 2022 , 0(1) : 8 -17 . DOI: 10.13466/j.cnki.lyzygl.2022.01.002
| [1] | Pretzsch H. Analysis and modeling of spatial stand structures.Methodological considerations based on mixed beech-larch stands in Lower Saxony[J]. Forest ecology and Management, 1997,97(3):237-253. |
| [2] | 惠刚盈. 基于相邻木关系的林分空间结构参数应用研究[J]. 北京林业大学学报, 2013,35(4):1-8. |
| [3] | 汤孟平. 森林空间结构研究现状与发展趋势[J]. 林业科学, 2010,46(1):117-122. |
| [4] | Pommerening A. Approaches to quantifying forest structures[J]. Forestry:An International Journal of Forest Research, 2002,75(3):305-324. |
| [5] | 张向龙, 王冰, 张秋良. 内蒙古大兴安岭白桦次生林空间结构特征[J]. 林业资源管理, 2021(5):80-86. |
| [6] | 魏红洋, 董灵波, 刘兆刚. 大兴安岭主要森林类型林分空间结构优化模拟[J]. 应用生态学报, 2019,30(11):3824-3832. |
| [7] | 林富成, 王维芳, 门秀莉, 等. 兴安落叶松人工林空间结构优化[J]. 北京林业大学学报, 2021,43(4):68-76. |
| [8] | 汤孟平. 森林空间结构分析与优化经营模型研究[D]. 北京:北京林业大学, 2003. |
| [9] | 万盼, 刘文桢, 刘瑞红, 等. 结构化经营对栎松混交林林分空间结构及稳定性的影响[J]. 林业科学, 2020,56(4):35-45. |
| [10] | Lee J, Li S. Extending moran's index for measuring spatiotemporal clustering of geographic events[J]. Geographical Analysis, 2017,49(1):36-57. |
| [11] | Tepanosyan G, Sahakyan L, Zhang Chaosheng, et al. The application of Local Moran's I to identify spatial clusters and hot spots of Pb,Mo and Ti in urban soils of Yerevan[J]. Applied Geochemistry, 2019,104:116-123. |
| [12] | Xiong Y, Bingham D, Braun W J, et al. Moran's I statistic-based nonparametric test with spatio-temporal observations[J]. Journal of Nonparametric Statistics, 2019,31(1):244-267. |
| [13] | Assuncao R M, Reis E A. A new proposal to adjust Moran's I for population density[J]. Statistics in medicine, 1999,18(16):2147-2162. |
| [14] | 赵静漪, 魏江生, 周梅, 等. 大兴安岭中段针阔混交林林分空间结构研究[J]. 林业资源管理, 2016(4):59-64. |
| [15] | 曹小玉, 李际平, 封尧, 等. 杉木生态公益林林分空间结构分析及评价[J]. 林业科学, 2015,51(7):37-48. |
| [16] | 秦舟, 韩有志, 张梦弢, 等. 华北落叶松林分空间格局及种间关联性研究[J]. 林业资源管理, 2019(4):80-85. |
| [17] | 张江. 森林健康经营空间途径与评价系统研究[D]. 长沙:中南林业科技大学, 2014. |
| [18] | 李建军, 李际平, 刘素青, 等. 基于Hegyi改进模型的红树林空间结构竞争分析[J]. 中南林业科技大学学报, 2010,30(12):23-27. |
| [19] | 曹小玉, 李际平, 封尧, 等. 杉木生态公益林林分空间结构分析及评价[J]. 林业科学, 2015,51(7):37-48. |
| [20] | 李建军, 李际平, 刘素青, 等. 红树林空间结构均质性指数[J]. 林业科学, 2010,46(6):6-14. |
| [21] | 张会儒, 武纪成, 杨洪波, 等. 长白落叶松-云杉-冷杉混交林林分空间结构分析[J]. 浙江林学院学报, 2009,26(3):319-325. |
| [22] | 汤孟平, 唐守正, 雷相东, 等. 林分择伐空间结构优化模型研究[J]. 林业科学, 2004(5):25-31. |
| [23] | 方景, 孙玉军, 郭孝玉, 等. 基于Voronoi图和Delaunay三角网的杉木游憩林空间结构[J]. 林业科学, 2014,50(12):1-6. |
| [24] | 赵春燕, 李际平, 李建军. 基于Voronoi图和Delaunay三角网的林分空间结构量化分析[J]. 林业科学, 2010,46(6):78-84. |
| [25] | 刘志川, 王建国, 梁书维, 等. 吉林省1990—2018年土地利用空间分布及其变化[J]. 水土保持通报, 2020,40(6):288-296. |
| [26] | 李颉, 郑步云, 王劲峰. 2008—2018年中国手足口病时空分异特征[J]. 地球信息科学学报, 2021,23(3):419-430. |
| [27] | 刘益凡, 李蕊超, 林慧龙. 基于空间自相关性探究我国各省食物需求时空差异[J]. 草地学报, 2016,24(6):1176-1183. |
| [28] | 杨永侠, 王旭, 孟丹, 等. 基于空间自相关的耕地等别指数检验方法研究[J]. 农业机械学报, 2016,47(5):328-335. |
| [29] | 孙一可, 宫辉力, 陈蓓蓓, 等. 综合莫兰指数和交叉小波的不均匀沉降量化分析[J]. 国土资源遥感, 2020,32(2):186-195. |
| [30] | 刘昭玥, 费杨, 师华定, 等. 基于UNMIX模型和莫兰指数的湖南省汝城县土壤重金属源解析[J]. 环境科学研究, 2021,34(10):2446-2458. |
| [31] | 委霞, 曹小玉, 李际平, 等. 福寿林场天然次生林空间结构分析与评价[J]. 西北林学院学报, 2021,36(5):146-151. |
| [32] | 薛卫星, 郭秋菊, 艾训儒, 等. 鄂西南天然林主要乔木树种物种组成及林分空间结构动态变化研究[J]. 西北植物学报, 2021,41(6):1051-1061. |
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