Classification of Vertical Forest Structure of Overstory in Subtropical Forests Using Airborne Lidar Data

doi:10.13466/j.cnki.lyzygl.2022.01.013

Abstract

Abstract:

The vertical structure classification of forest plays an important role in ecology and forestry. A vertical canopy profile (pseudo-wave) was obtained by fitting the frequency distribution of height and coverage of discrete laser point cloud in Guangxi by using the tenth order polynomial method,which reflected the vertical distribution of canopy material. Canopy structure parameters such as effective peak,stand surface height,sub-storey height,and crown ratio were extracted by pseudo-wave and classification rules were established to divide the vertical structure of stands into six types.Confusion matrix was used to evaluate the classification accuracy,and an area of 1369km² was selected for mapping to test the generalization of classification rules. The results showed that: 1) In the classification results of 1 147 sample plots,the overall classification accuracy was 93.9%,and the Kappa coefficient was 0.913;2) The error rates of single-peak,double-peak and triple-peak were 6.2%,7.4% and 9.1% respectively,while the error rates of Chinese fir forest,pine forest,eucalyptus forest and broadleaved forest were 9%,6.4%,2.4% and 6.9%,respectively,indicating that the more complex the vertical structure of the stand,the lower the accuracy of classification;3) The accuracy of each forest layer was higher than 96%,the omission errors were less than 4%,and the commission errors were less than 10%,indicating that each forest layer can be accurately detected;4) The coverage of classification rules in mapping areas reached 99.8%. In this study,vertical forest classification method with high accuracy,good generalization and rich spatial information is suitable for overstory vertical structure classification mapping of large regional subtropical forest.

Key words: canopy vertical profile, pseudo-wave, canopy structure parameters, confusion matrix

CLC Number:

S771.8

ZHOU Xiangbei, LI Chungan, YU Zhu, CHEN Zhongchao, SU Kai. Classification of Vertical Forest Structure of Overstory in Subtropical Forests Using Airborne Lidar Data[J]. FOREST RESOURCES WANAGEMENT, 2022, (1): 106-113.

Figures/Tables 7

Tab.1

Fig.1

Fig.2

Fig.3

Tab.2

Classification rules of vertical structure of overstory based on continuous vertical canopy profile

编号	分类规则
A(1)	Null	UT₁
B(1a)	$H UL 1$ ≥hp99/2 and C_INF<0.1	OT₁
B(1b)	$H UL 1$ ≥hp99/2 and C_INF≥0.1	T₁T₃
B(2a)	(hp99/3< $H UL 1$ ≤hp99/2)and C_INF<0.1 and H_LA1/H_CS≥0.65	OT₁T₂
B(2b)	(hp99/3< $H UL 1$ ≤hp99/2)and C_INF<0.1 and H_LA1/H_CS<0.65	OT₁
B(2c)	(hp99/3< $H UL 1$ ≤hp99/2)and C_INF≥0.1 and hp99≥15.0	T₁T₂T₃
B(2d)	(hp99/3< $H UL 1$ ≤hp99/2)and C_INF≥0.1 and hp99<15.0	UT₁T₂
B(3a)	(3.0< $H UL 1$ ≤hp99/3)and hp99≥15.0 and H_LA1/H_CS≥0.80	T₁T₂T₃
B(3b)	(3.0< $H UL 1$ ≤hp99/3)and hp99≥15.0 and(0.65≤H_LA1/H_CS<0.80)and C_INF<0.1	OT₁T₂
B(3c)	(3.0< $H UL 1$ ≤hp99/3)and hp99≥15.0 and(0.65≤H_LA1/H_CS<0.80)and C_INF≥0.1	UT₁T₂
B(3d)	(3.0< $H UL 1$ ≤hp99/3)and hp99≥15.0 and H_LA1/H_CS<0.65	OT₁
B(3e)	(3.0< $H UL 1$ ≤hp99/3)and hp99<15.0 and H_LA1/H_CS≥0.65	OT₁T₂
B(3f)	(3.0< $H UL 1$ ≤hp99/3)and hp99<15.0 and H_LA1/H_CS<0.65 and C_INF<0.1	OT₁
B(3g)	(3.0< $H UL 1$ ≤hp99/3)and hp99<15.0 and H_LA1/H_CS<0.65 and C_INF≥0.1	UT₁
B(4a)	(1.0< $H UL 1$ ≤3.0)and hp99≥15.0 and H_LA1/H_CS≥0.80	T₁T₂T₃
B(4b)	(1.0< $H UL 1$ ≤3.0)and hp99≥15.0 and H_LA1/H_CS<0.80	UT₁T₂
B(4c)	(1.0< $H UL 1$ ≤3.0)and(10.0≤Hp99<15.0)and H_LA1/H_CS≥0.8	UT₁T₂
B(4d)	(1.0< $H UL 1$ ≤3.0)and(10.0≤hp99<15.0)and H_LA1/H_CS<0.8	UT₁
B(4e)	(1.0≤ $H UL 1$ <3.0)and hp99<10.0	UT₁
B(5a)	$H UL 1$ <1.0 and H_CS<10.0	UT₁
B(5b)	$H UL 1$ <1.0 and H_CS≥10.0	UT₁T₂
C(1a)	H_PEAK1≥2/3 hp99 and H_PEAK2≥hp99/3 and H_UL2≥3.0 and(H_LA1+H_LA2)/H_CS<0.65	OT₁
C(1b)	H_PEAK1≥2/3hp99 and H_PEAK2≥hp99/3 and H_UL2≥3.0 and(H_LA1+H_LA2)/H_CS≥0.65	OT₁T₂
C(1c)	H_PEAK1≥2/3hp99 and H_PEAK2≥hp99/3 and H_UL2<3.0 and hp99≥15.0	T₁T₂T₃
C(1d)	H_PEAK1≥2/3hp99 and H_PEAK2≥hp99/3 and H_UL2<3.0 and hp99<15.0	UT₁T₂
C(2a)	H_PEAK1≥2/3hp99 and(3.0<H_PEAK2≤hp99/3)and hp99≥15.0 and C_MID<0.1	T₁T₃
C(2b)	H_PEAK1≥2/3hp99 and(3.0<H_PEAK2≤hp99/3)and hp99≥15.0 and C_MID≥0.1	T₁T₂T₃
C(2c)	H_PEAK1≥2/3hp99 and(3.0<H_PEAK2≤hp99/3)and hp99<15.0	UT₁T₂
C(3a)	H_PEAK1≥2/3hp99 and(1.0≤H_PEAK2<3.0)and hp99≥15.0 and H_LA1/H_CS<0.65 and H_LA2/H_CS<0.35	OT₁
C(3b)	H_PEAK1≥2/3hp99 and(1.0≤H_PEAK2<3.0)and hp99≥15.0 and H_LA1/H_CS≥0.65 and H_LA2/H_CS<0.35	OT₁T₂
C(3c)	H_PEAK1≥2/3hp99 and(1.0≤H_PEAK2<3.0)and hp99≥15.0 and H_LA1/H_CS<0.65 and H_LA2/H_CS≥0.35 and(H_LA1+H_LA2)/H_CS≥0.80	T₁T₂T₃
C(3d)	H_PEAK1≥2/3hp99 and(1.0≤H_PEAK2<3.0)and hp99≥15.0 and H_LA1/H_CS<0.65 and H_LA2/H_CS≥0.35 and(H_LA1+H_LA2)/H_CS<0.80	T₁T₃
C(3e)	H_PEAK1≥2/3hp99 and(1.0≤H_PEAK2<3.0)and hp99<15.0 and H_LA1/H_CS≥0.65	UT₁T₂
C(3f)	H_PEAK1≥2/3hp99 and(1.0≤H_PEAK2<3.0)and hp99<15.0 and H_LA1/H_CS<0.65 and H_UL2<hp99/3	UT₁
C(3g)	H_PEAK1≥2/3hp99 and(1.0≤H_PEAK2<3.0)and hp99<15.0 and H_LA1/H_CS<0.65 and H_UL2≥hp99/3	OT₁
C(4a)	(hp99/3≤H_PEAK1<2/3hp99)and hp99≥15.0 and(H_LA1+H_LA2)/H_CS≥0.8	T₁T₂T₃
C(4b)	(hp99/3≤H_PEAK1<2/3hp99)and hp99≥15.0 and(H_LA1+H_LA2)/H_CS<0.8 and H_UL2<hp99/3	UT₁T₂
C(4c)	(hp99/3≤H_PEAK1<2/3hp99)and hp99≥15.0 and(H_LA1+H_LA2)/H_CS<0.8 and H_UL2≥hp99/3	OT₁T₂
C(4d)	(hp99/3≤H_PEAK1<2/3hp99)and hp99<15.0 and(H_LA1+H_LA2)/H_CS<0.65 and H_UL2<hp99/3	UT₁
C(4e)	(hp99/3≤H_PEAK1<2/3hp99)and hp99<15.0 and(H_LA1+H_LA2)/H_CS<0.65 and H_UL2≥hp99/3	OT₁
C(4f)	(hp99/3≤H_PEAK1<2/3hp99)and hp99<15.0 and(H_LA1+H_LA2)/H_CS≥0.65 and H_UL2<hp99/3	UT₁T₂
C(4g)	(hp99/3≤H_PEAK1<2/3hp99)and hp99<15.0 and(H_LA1+H_LA2)/H_CS≥0.65 and H_UL2≥hp99/3	OT₁T₂
D(1a)	H_PEAK3≥3.0 and(H_LA1+H_LA2+H_LA3)/H_CS≥0.80	T₁T₂T₃
D(1b)	H_PEAK3≥3.0 and(H_LA1+H_LA2+H_LA3)/H_CS<0.80	OT₁T₂
D(2a)	H_PEAK3<3.0 and(H_LA1+H_LA2+H_LA3)/H_CS≥0.80	T₁T₂T₃
D(2b)	H_PEAK3<3.0 and(H_LA1+H_LA2+H_LA3)/H_CS<0.80	OT₁T₂

Tab.2

Tab.3

Fig.4

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森林类型	样地数/个	林分高		林分直径		林分蓄积量
森林类型	样地数/个	均值/m	变动系数/%	均值/cm	变动系数/%	均值/(m³/hm²)	变动系数/%
松树林	265	13.77	27.32	19.04	28.71	190.35	47.76
杉木林	233	10.80	28.51	12.17	28.90	191.57	47.77
桉树林	289	15.94	21.73	11.16	22.82	138.27	47.28
阔叶林	360	8.79	45.71	11.41	52.53	81.94	89.07

类型	真实值						总数	用户精度/%
类型	(1)UT₁	(2)OT₁	(3)UT₁T₂	(4)OT₁T₂	(5)T₁T₃	(6)T₁T₂ T₃	总数	用户精度/%
(1)UT₁	190	0	1	0	0	0	191	99.5
(2)OT₁	5	534	0	2	0	2	543	98.3
(3)UT₁T₂	9	0	67	6	1	1	84	79.8
(4)OT₁T₂	17	5	6	164	1	0	193	85.0
(5)T₁T₃	0	3	0	0	21	1	25	84.0
(6)T₁T₂ T₃	1	1	5	1	2	101	111	91.0
总数	222	543	79	173	25	105	1147
生产者精度/%	85.6	98.3	84.8	94.8	84.0	96.2