基于空间结构的杉木枝下高可视化模拟研究

doi:10.12302/j.issn.1000-2006.202010037

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南京林业大学学报（自然科学版） ›› 2022, Vol. 46 ›› Issue (1): 51-57.doi: 10.12302/j.issn.1000-2006.202010037

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基于空间结构的杉木枝下高可视化模拟研究

朱念福¹^,²(), 张怀清¹^,²^,^*(), 崔泽宇¹, 杨廷栋¹, 李永亮¹, 刘华¹

1.中国林业科学研究院资源信息研究所,北京 100091
2.国家林业和草原局林业遥感与信息技术重点实验室,北京 100091

收稿日期:2020-10-24 接受日期:2021-03-23 出版日期:2022-01-30 发布日期:2022-02-09
通讯作者: 张怀清
基金资助:
中国林科院资源信息研究所基本科研业务费专项(CAFYBB2019SZ004);国家自然科学基金项目(32071681);国家重点研发计划(2017YFD0600905)

Visual simulation of Chinese fir under branch height in consideration of spatial structure

ZHU Nianfu¹^,²(), ZHANG Huaiqing¹^,²^,^*(), CUI Zeyu¹, YANG Tingdong¹, LI Yongliang¹, LIU Hua¹

1. Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091,China
2. Key Laboratory of Forestry Remote Sensing and Information System, NFGA, Beijing 100091, China

Received:2020-10-24 Accepted:2021-03-23 Online:2022-01-30 Published:2022-02-09
Contact: ZHANG Huaiqing

摘要/Abstract

摘要：

【目的】定量研究林分空间结构对杉木枝下高的影响,构建基于空间结构的枝下高模型,结合杉木生长模型,应用三维可视化技术,实现杉木枝下高可视化模拟。【方法】利用湖南省黄丰桥国有林场6块杉木人工林临时样地的调查数据,选择5个常用枝下高基础模型,分析水平空间结构参数(P_H)、垂直空间结构参数(P_V)和空间结构单元平均距离(d_DIS)及其组合对枝下高的影响,构建综合指标较好且变量少的枝下高模型。基于林分三维模型实时生成方法,建立一种枝干可控的杉木三维模型;结合单木胸径连年生长量模型、树高-曲线模型和冠幅面积估计模型,模拟林木的生长状态。【结果】Logistic模型综合指标较好且模型参数可解释,可选为基础模型;3个空间结构参数中垂直空间结构影响较为显著,将P_V加入到Logistic模型中,改善了枝下高模型的拟合效果,决定系数(R²)从0.717提升到0.741,估计值的标准差从1.407 m减小到1.321 m,并使各项模型检验误差指标有所减小;构建的杉木三维模型可以动态调节枝干,实现了杉木枝下高模拟。【结论】构建的枝下高模型可以应用于林木年龄和部分林分信息未知的杉木林中,体现了林木间的相互竞争影响;结合枝干可控的杉木三维模型,模拟杉木生长过程,形象直观地表现了杉木枝下高的变化,为进一步研究林分生长动态可视化模拟和森林经营可视化模拟提供支持。

关键词: 空间结构参数, 枝下高, 杉木人工林, 可视化模拟

Abstract:

【Objective】 This study quantitatively investigated the effect of spatial structure on the under-branch height of Chinese fir (Cunninghamia lanceolata), to build a model of Chinese fir under-branch height. The spatial structure combined with the fir growth model, three-dimensional (3D) visualization technology was applied to visually simulate the height of fir branches. 【Method】 Using survey data of six temporary sample plots of Chinese fir plantations in the Huangfengqiao State-owned Forest Farm in Hunan Province, China; five commonly used branch height foundation models were selected to analyze horizontal spatial structure parameters (P_H), vertical spatial structure parameters (P_V), and spatial structure unit average distance (d_DIS). The influence of this combination on the height of branches was constructed with better comprehensive indicators and fewer variables. 【Result】 The Logistic model showed better comprehensive indicators and explanatory model parameters; as such, it was selected as the basic model. Among the three spatial structure parameters, the vertical spatial structure (P_V) had a significant impact (R²=0.741). Adding vertical spatial structure parameters to the Logistic model improved the simulation of the sub-branch height model. As a result, the coefficient of determination (R²) increased from 0.717 to 0.741, the standard deviation of the estimate reduced from 1.407 to 1.321 m, and various model inspection error indicators were reduced.【Conclusion】 The under-branch height model constructed in this study may be applied to Chinese fir forests of unknown tree age and partial stand information, reflecting the mutual competition among forest trees and visually and intuitively expresses changes in the height of fir branches, and supports further research on the visual simulation of forest stand growth dynamics and forest management.

Key words: spatial structure parameters, under branch height, Chinese fir plantation, visual simulation

中图分类号:

S791.27

朱念福,张怀清,崔泽宇,等. 基于空间结构的杉木枝下高可视化模拟研究[J]. 南京林业大学学报（自然科学版）, 2022, 46(1): 51-57.

ZHU Nianfu, ZHANG Huaiqing, CUI Zeyu, YANG Tingdong, LI Yongliang, LIU Hua. Visual simulation of Chinese fir under branch height in consideration of spatial structure[J].Journal of Nanjing Forestry University (Natural Science Edition), 2022, 46(1): 51-57.DOI: 10.12302/j.issn.1000-2006.202010037.

图/表 7

表1

图1

表2

枝下高模型"

模型 model	表达式 expression	参考文献 reference
A	H_CB=H/(1+e^X)	[13]
B	H_CB=H/(1+e^X)¹^/⁶	[15]
C	H_CB=H/(1+e^X)¹^/²	[17]
D	H_CB=H(1+e^X)	[19]
E	H_CB=H(1+ $e X 2$ )	[19]

表2

表3

表4

图2

表5

参考文献 35

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样地序号 plot No.	面积/ m² area	样木数 steam numbers	平均胸径/ cm mean DBH	平均树高/m mean height	平均冠幅/m mean CW	平均枝下高/m mean HCB
1	60×60	525	16.2	10.6	2.7	4.7
2	50×80	359	22.6	15.7	2.9	7.9
3	50×80	309	14.2	9.5	2.7	4.2
4	50×50	955	11.6	8.4	2.2	4.4
5	40×40	230	20.0	12.7	2.9	6.6
6	30×30	120	15.5	11.0	3.1	5.3

模型 model	标准误 standard error		拟合优度 goodness of fitting		检验结果 validation result
模型 model	a	b	R²	σ(SEE)/m	σ(ME)/m	σ(MAE)/m	σ(TRE)/%	σ(MSE)/%
A	0.020	0.001	0.717	1.407	-0.293	1.018	-2.906	-2.931
B	0.057	0.003	0.716	1.409	-0.297	1.018	-2.986	-3.108
C	0.026	0.001	0.717	1.409	-0.297	1.018	-2.936	-3.044
D	0.011	0.001	0.717	1.409	-0.293	1.018	-2.929	-2.939
E	0.006	0.000	0.716	1.409	-0.297	1.018	-2.927	-3.021

因子 factor	拟合优度 goodness of fitting		检验结果 validation result
因子 factor	R²	σ(SEE)/ m	σ(ME)/ m	σ(MAE)/ m	σ(TRE)/ %	σ(MSE)/ %
—	0.717	1.407	-0.293	1.018	-2.906	-2.931
P_H	0.731	1.325	-0.238	0.998	-2.844	-2.863
P_V	0.741	1.321	-0.234	0.989	-2.842	-2.843
d_DIS	0.729	1.375	-0.242	1.011	-2.916	-3.005
P_H, P_V	0.745	1.317	-0.239	0.989	-2.875	-2.940
P_H, d_DIS	0.738	1.316	-0.237	0.998	-2.845	-2.883
P_V, d_DIS	0.743	1.314	-0.235	0.993	-2.854	-2.917
P_H, P_V, d_DIS	0.748	1.312	-0.231	0.989	-2.849	-2.884

林木编号 tree No.	树高/ m tree height	枝下高/m under branch height
林木编号 tree No.	树高/ m tree height	当前状态 now	10年后 10 years later	20年后 20 years later
1	6.3	2.4	7.1	8.9
2	7.9	2.9	7.8	9.2
3	6.7	2.6	7.3	9.1
4	10.4	3.3	7.8	9.3
5	9.9	2.8	7.1	9.0

基于空间结构的杉木枝下高可视化模拟研究

Visual simulation of Chinese fir under branch height in consideration of spatial structure

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[1]	鲁旭东, 董禹然, 李垚, 毛岭峰. 中国亚热带杉木人工林不同林分发育阶段的群落构建机制[J]. 南京林业大学学报（自然科学版）, 2024, 48(1): 67-73.
[2]	王有良, 林开敏, 宋重升, 崔朝伟, 彭丽鸿, 郑宏, 郑鸣鸣, 任正标, 邱明镜. 间伐对杉木人工林生态系统碳储量的短期影响[J]. 南京林业大学学报（自然科学版）, 2022, 46(3): 65-73.
[3]	薛蓓蓓, 田国双. 不同碳补贴机制下杉木人工林最优轮伐期和碳汇成本分析[J]. 南京林业大学学报（自然科学版）, 2022, 46(2): 27-34.
[4]	崔泽宇, 张怀清, 左袁青, 杨廷栋, 刘洋, 张京, 王林龙. 杉木三维模型各方向枝下高分布研究[J]. 南京林业大学学报（自然科学版）, 2022, 46(1): 81-87.
[5]	郭传阳, 林开敏, 郑鸣鸣, 任正标, 李茂, 郑宏, 游云飞, 陈志云. 间伐对杉木人工林土壤微生物生物量碳氮的短期影响[J]. 南京林业大学学报（自然科学版）, 2020, 44(5): 125-131.
[6]	段光爽,李学东,冯岩,符利勇. 基于广义非线性混合效应的华北落叶松天然次生林枝下高模型[J]. 南京林业大学学报（自然科学版）, 2018, 42(02): 170-176.
[7]	曹元帅，孙玉军. 基于广义代数差分法的杉木人工林地位指数模型[J]. 南京林业大学学报（自然科学版）, 2017, 41(05): 79-84.
[8]	李静,王玲红,程栋梁,徐朝斌,张中瑞,吴永宏,钟全林. 不同龄组天然常绿阔叶林与杉木人工林林下草本层生物量分配特征[J]. 南京林业大学学报（自然科学版）, 2016, 40(05): 170-176.
[9]	曾伟,江斌,余林,肖复明,徐海宁. 江西杉木人工林生物量分配格局及其模型构建[J]. 南京林业大学学报（自然科学版）, 2016, 40(03): 177-182.
[10]	涂宏涛,万杰,孙玉军,梅光义,刘素真. 不同林龄杉木人工林根生物量及其相容性模型[J]. 南京林业大学学报（自然科学版）, 2015, 39(06): 81-86.
[11]	王东,李瑞霞,陈信力,关庆伟. 杉木人工林不同根序的一级根形态差异及其对间伐的响应[J]. 南京林业大学学报（自然科学版）, 2014, 38(04): 69-74.
[12]	刘应安;洪岩;叶金山. 皖东南山区杉木人工林立地质量数量化评定与产量预测[J]. 南京林业大学学报（自然科学版）, 1998, 22(03): 51-55.
[13]	孙多. 残留物管理育林法对杉木人工林物种多样性的恢复作用[J]. 南京林业大学学报（自然科学版）, 1996, 20(01): 29-32.
[14]	李耀芬;李大纲;宋均庭;黎源忠. 宜春杉木人工林管胞形态变异及其对材性的影响[J]. 南京林业大学学报（自然科学版）, 1988, 12(02): 115-121.