Determination and Estimation of Pinus massoniana Stand Volume and Saturation Point Based on Landsat-8 OLI Data

doi:10.13466/j.cnki.lyzygl.2020.06.022

Abstract

Abstract:

This paper takes 72 Pinus massoniana forest plots (25 m × 25 m) in Hunan Province as the research object based on the method of estimating the forest biomass saturation point proposed in previous studies (Scheme 1) and propose a simpler binomial saturation point estimation method (Scheme 2).According to the saturation point estimation method,the study proposes a new stock volume estimation model for a comparative analysis with multiple stepwise regressions.It finds that the maximum saturation point estimation results of Scheme 1 and Scheme 2 were 217.05 m³/hm² and 206.86 m³/hm²,respectively.Based on the vegetation index information,the maximum saturation point estimation results of Scheme 1 and Scheme 2 were 196.95 m³/hm² and 183.06 m³/hm²,respectively.In the modeling test phase,based on the newly-proposed binomial model and the multiple stepwise regression mode,R² was 0.49 and 0.29,MAE was 53.76 m³/hm² and 63.35 m³/hm²,and RMSE was 58.71 m³/hm² and 69.53 m³/hm²,respectively.Compared with Scheme 1,the method for estimating the saturation point of forest stock volume (FSV) in Scheme 2 was more scientific and reasonable,and it was a simple method for determining the saturation point of the FSV by remote sensing data.In addition,compared with the multiple stepwise regression model,the binomial model proposed in this study had a better effect in estimating FSV.

Key words: remote sensing image, forest stock volume, saturation point, binomial estimation model, Pinus massoniana

CLC Number:

S758.51

SUN Zhongqiu, WU Fayun, HU Yang, GAO Xianlian, Gao Jingping. Determination and Estimation of Pinus massoniana Stand Volume and Saturation Point Based on Landsat-8 OLI Data[J]. FOREST RESOURCES WANAGEMENT, 2020, 0(6): 135-142.

Figures/Tables 12

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类别	最小值/(m³/hm²)	最大值/(m³/hm²)	平均/(m³/hm²)	标准误差/(m³/hm²)	方差/(m³/hm²)	观测数/个
总样本	4.25	318.47	125.36	9.31	6234.29	72
建模样本	5.66	318.47	117.01	10.73	5871.01	51
验证样本	4.25	309.98	145.65	18.05	6843.92	21

波段	波段名称	波长范围/μm	空间分辨率/m
B2	Blue	0.452~0.512	30
B3	Green	0.533~0.590	30
B4	Red	0.636~0.673	30
B5	NIR	0.851~0.879	30
B6	SWIR1	1.566~1.651	30
B7	SWIR2	2.107~2.294	30

	FSV	B2	B3	B4	B5	B6	B7
FSV	1
B2	-0.515^**	1
B3	-0.625^**	0.919^**	1
B4	-0.559^**	0.939^**	0.948^**	1
B5	-0.388^**	0.511^**	0.685^**	0.501^**	1
B6	-0.545^**	0.835^**	0.914^**	0.839^**	0.835^**	1
B7	-0.567^**	0.924^**	0.937^**	0.956^**	0.621^**	0.934^**	1

参数	球状模型		二项式模型
参数	估计	标准误	估计	标准误
a₀	723.105	25.051	756.247	27.216
a₁	-2.085	0.278	-3.149	0.430
a₂	1.475E-05	0.000	0.008	0.001

	FSV	DVI	RDVI	EVI	NDVI	GNDVI	LAI	RVI
FSV	1
DVI	-0.279^*	1
RDVI	-0.110	0.944^**	1
EVI	-0.224	0.984^**	0.966^**	1
NDVI	0.408^**	0.261^*	0.560^**	0.360^**	1
GNDVI	0.451^**	0.306^**	0.583^**	0.389^**	0.952^**	1
LAI	-0.224	0.984^**	0.966^**	1.000^**	0.360^**	0.389^**	1
RVI	0.365^**	0.290^*	0.577^**	0.382^**	0.974^**	0.946^**	0.382^**	1