毛竹林竹鞭生长特征和空间结构的探地雷达无损探测

doi:10.11707/j.1001-7488.20201203

摘要/Abstract

摘要：

目的: 发展毛竹林地下竹鞭空间结构的探地雷达无损探测方法，解决因毛竹竹鞭深入地下和观测不便而使空间结构及地下生物量无法准确预测的难题，为毛竹林地下竹鞭研究提供新思路。方法: 设置毛竹林样地并采用探地雷达进行探测，在雷达数据预处理后提取竹鞭信息，同时基于双曲线模型估计竹鞭直径，并利用直径（D）与长度（L）拟合竹鞭生物量，再用实测值进行模型检验，最后分析竹鞭的垂直与水平空间结构。结果: 探地雷达能有效探测毛竹林地下竹鞭的位置信息，双曲线模型对竹鞭直径和长度估计误差分别为-14.45%~20.66%和0.53%~8.51%，对空间位置3个方向（X，Y，Z）的估计误差分别为0.13%~6.65%、1.23%~6.55%和2.42%~7.41%；对于生物量，以DL为变量的多项式模型和以D²L为变量的指数模型拟合结果较好，确定系数R²为0.93~0.95，均方根误差RMSE为18.3~22.4 kg·hm^-2；从模型检验结果来看，以D²L为变量的指数和多项式模型模拟效果显著好于以D、D²和DL为变量的指数和多项式模型；以D²L为变量的指数模型是竹鞭生物量（BR）的最佳拟合模型，具体形式为BR=65.17e^0.002D²L；对竹鞭空间结构分析表明，竹鞭主要垂直分布在0~40 cm土层，该土层竹鞭条数占竹鞭条数总量的91%，竹鞭鞭长和生物量分别占总量的95%和93%，且竹鞭直径在下层（>20 cm）土壤显著大于表层（0~20 cm）土壤；竹鞭在地下的走势较为曲折，空间分布相对均匀，同一竹鞭的直径差异不大，但不同竹鞭的直径差异显著（P < 0.01），样地内单位面积竹鞭的长度和生物量分别为54 080 m·hm^-2和1 001.17 kg·hm^-2。结论: 利用探地雷达能成功探测地下竹鞭的位置信息，可得到竹鞭垂直和水平方向的空间结构，同时竹鞭直径模型与生物量模型的预测结果也较好，表明探地雷达技术可为研究毛竹林竹鞭结构及其动态与地上立竹的相互关系等提供技术支撑。

关键词: 毛竹林, 探地雷达, 竹鞭系统, 空间结构, 无损探测

Abstract:

Objective: A method of non-destructive detection for the spatial structure of underground bamboo rhizomes in moso bamboo forest by using ground penetrating radar(GPR) was developed, in order to solve the problem that the spatial structure and underground biomass could not be accurately predicted due to the deep underground and inconvenient observation of moso bamboo rhizomes, providing a new idea for the study of underground bamboo rhizomes in moso bamboo forest. Method: The GPR was used to detect the bamboo rhizomes in the sample plots of moso bamboo forest. The information of bamboo rhizomes was extracted after radar data pretreatment. At the same time, the diameters of bamboo rhizomes were estimated based on hyperbolic model, and the biomass of bamboo rhizomes was fitted by diameter (D) and length (L). Then the measured values were used to test the model. Finally, the vertical and horizontal spatial structure of bamboo rhizomes was analyzed. Result: The GPR could effectively detect the position of the underground bamboo rhizomes. The error range of the hyperbolic model for the diameter and length of the bamboo rhizomes were -14.45%-20.66% and 0.53%-8.51%. The estimated error range of the space position in X, Y and Z directions were 0.13%-6.65%, 1.23%-6.55%, and 2.42%-7.41%, respectively. The estimated values were close to the measured values. As for biomass, polynomial model and exponential model using DL and D²L as variables had the best fitting results. The coefficient of determination (R²) ranged from 0.93 to 0.95, and the root mean square error (RMSE) was from 18.3 to 22.4 kg·hm^-2. The simulated results of the exponential and polynomial models with D²L as variables were significantly better than that of the exponential and polynomial models with D, D² and DL as variables. Generally, the exponential model with D²L as the variable was the best fitting model of bamboo rhizomes biomass(BR), while the specific expression was BR=65.17e^0.002D²L. Analysis of bamboo rhizomes spatial structure showed that the vertical distribution of bamboo rhizomes was mainly in 0-40 cm soil layer, in which the number of rhizomes accounts for 91% of the total, while the length and biomass of bamboo rhizomes account for 95% and 93% of the total respectively, and the diameter of bamboo rhizomes in the lower soil (>20 cm) was significantly larger than that in the surface soil (0-20 cm). The underground rhizomes were tortuous, and the spatial distribution was relatively uniform. There was little difference in the diameter of the same rhizomes, but there were significantly differences in the diameter of different rhizomes (P < 0.01). The length and biomass of the rhizomes per unit area in the sample plot were 54 080 m·hm^-2 and 1 001.17 kg·hm^-2 respectively. Conclusion: The results showed that GPR could successfully detect the position information of the underground bamboo rhizomes and obtain the vertical and horizontal spatial structure of the bamboo rhizomes. At the same time, the bamboo rhizomes diameter model and the biomass model also produced the good prediction results, indicating that GPR technology could provide technical support for the study of bamboo rhizomes structure and dynamics and the relationship with above-ground standing bamboo.

Key words: moso bamboo forest, ground penetrating radar, rhizomes system, spatial structure, non-destructive detection

中图分类号:

S757.2⁺9

熊雨露,周宇峰,李平衡,童亮,周国模,施拥军,杜华强. 毛竹林竹鞭生长特征和空间结构的探地雷达无损探测[J]. 林业科学, 2020, 56(12): 19-27.

Yulu Xiong,Yufeng Zhou,Pingheng Li,Liang Tong,Guomo Zhou,Yongjun Shi,Huaqiang Du. Non-Destructive Detection by Ground Penetrating Radar of Growth Characteristics and Spatial Structure of Rhizomes in Moso Bamboo Forest[J]. Scientia Silvae Sinicae, 2020, 56(12): 19-27.

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竹鞭编号 Rhizome No.	样本点 Sample points	双曲线拟合的4个参数				实测直径 Measured diameter/cm	相对误差 Relative error(%)
竹鞭编号 Rhizome No.	样本点 Sample points	t₀/s x₀/cm		v/(cm·s^-1)	估计直径 Estimated diameter/cm	实测直径 Measured diameter/cm	相对误差 Relative error(%)
1	16	1.50	1.19	1.02×10⁸	1.61	1.71	-5.82
2	39	0.31	1.22	1.37×10⁸	1.93	1.71	12.87
3	39	-0.16	1.24	1.55×10⁸	1.50	1.71	-12.28
4	18	-0.99	1.87	1.10×10⁸	1.95	1.73	12.72
5	26	-1.40	1.81	1.51×10⁸	2.64	2.28	15.79
6	30	0.31	1.52	1.39×10⁸	2.04	2.23	-8.52
7	21	1.50	1.19	1.53×10⁸	2.25	2.13	5.63
8	39	0.31	1.22	1.38×10⁸	2.57	2.13	20.66
9	25	0.75	1.58	1.43×10⁸	1.48	1.73	-14.45
10	27	0.92	1.34	1.45×10⁸	1.85	1.73	6.94

土层 Soil layer/cm	竹鞭数量 Number of bamboo rhizomes	平均直径 Average diameter/cm	鞭长 Rhizomes length/(m·hm^-2)	生物量 Biomass/(kg·hm^-2)
0~5	5 (22%)	2.02	11 700 (22%)	225.03 (23%)
5~20	9 (39%)	2.01	22 292 (41%)	323.89 (32%)
20~40	7 (30%)	2.36	17 224 (32%)	382.43 (38%)
>40	2 (9%)	2.42	2 864 (5%)	69.82 (7%)
合计Total	23 (100%)	2.15	54 080 (100%)	1 001.17 (100%)

竹鞭号 Rhizome No.	竹鞭长度 Rhizome length/m			空间位置相对误差 Location relative error (%)
竹鞭号 Rhizome No.	估计值 Simulated value/m	实测值 Actual value/m	相对误差 Relative error (%)	X	Y	Z
1	1.22	1.25	2.40	6.65	4.31	7.41
2	1.53	1.56	1.92	1.62	5.54	2.47
3	1.81	1.79	1.12	4.25	6.45	5.69
4	1.02	0.94	8.51	3.40	5.17	7.07
5	1.88	1.87	0.53	6.24	1.23	5.97
6	2.05	2.03	0.99	5.33	2.84	2.42
7	1.18	1.16	1.72	3.20	6.55	3.39
8	1.03	1.05	1.90	0.13	6.42	4.23
9	0.98	0.93	5.38	5.75	2.87	3.91
10	2.54	2.52	0.79	3.11	6.26	4.39

模型 Model	参数估计值 Estimated parameter values			模型建立精度 Model establishment accuracy		模型检验精度 Model validation accuracy
模型 Model	a	b	c	R²	RMSE/g	R²	RMSE/g
BR=aD^b	16.77	2.84		0.61	51.6	0.55	48.0
BR=a(DL)^b	0.11	1.46		0.90	26.3	0.70	21.0
BR=a(D²L)^b	0.41	1.03		0.88	29.5	0.65	38.9
BR=a+bD+cD²	963.70	-962.50	266.20	0.69	48.0	0.73	47.2
BR=a+bDL+c(DL)²	80.41	-0.94	0.006 3	0.94	20.6	0.69	27.1
BR=a+bD²L+c(D²L)	64.27	0.10	0.000 5	0.93	22.4	0.83	20.3
BR=ae^bD	7.84	1.35		0.67	48.1	0.61	35.9
BR=ae^bD²	33.13	0.31		0.72	44.6	0.75	29.2
BR=ae^bDL	43.37	0.01		0.95	18.3	0.68	19.7
BR=ae^bD²L	65.17	0.002		0.94	21.4	0.83	17.3

竹鞭号 Rhizome No.	估计直径 Simulated diameter/cm	实测直径 Actual diameter/ cm	实测生物量 Actual biomass/ (kg·hm^-2)	估计直径模拟生物量 Calculated biomass using estimated diameter		实测直径模拟生物量 Calculated biomass using actual diameter
竹鞭号 Rhizome No.	估计直径 Simulated diameter/cm	实测直径 Actual diameter/ cm	实测生物量 Actual biomass/ (kg·hm^-2)	生物量 Biomass/(kg·hm^-2)	RMSE/g	生物量 Biomass/(kg·hm^-2)	RMSE/g
1	1.61	1.71	86.94	90.86	3.92	94.81	7.87
2	1.93	1.71	86.94	105.06	18.12	94.81	7.87
3	1.50	1.71	86.94	86.96	0.02	94.81	7.87
4	1.95	1.73	86.94	106.11	19.17	95.65	8.71
5	2.64	2.28	167.91	198.77	30.86	149.72	18.19
6	2.04	2.23	167.91	126.83	41.08	144.41	23.50
7	2.25	2.13	167.91	146.50	21.41	134.68	33.23
8	2.57	2.13	167.91	187.50	19.59	134.68	33.23
9	1.48	1.73	93.87	92.56	1.31	105.26	11.39
10	1.85	1.73	93.87	112.76	18.89	105.26	11.39