Estimation of aboveground biomass of Diarthron tianschanicum based on vegetation index fusion

doi:10.6048/j.issn.1001-4330.2024.11.020

Abstract

Abstract:

【Objective】 In order to explore the ability of multi-source data to estimate aboveground biomass (AGB) of D.tianschanicum.【Methods】 A drone platform equipped with visible light and multispectral sensors was used to collect information on blooming and heading stages and obtain visible light vegetation index, multispectral vegetation index, and a combination of the two vegetation indices.Multiple linear regression (MLR), stepwise linear regression (SMLR) Random Forest Regression (RF) were applied to establish an AGB estimation model for single vegetation index and fused vegetation index by using the determination coefficient (R²), and to valuate the estimation model with the adjusted coefficient of determination ( $R_{a d j}^{2}$ ) and root mean square error (RMSE).【Results】 The vegetation index in the combination of near-infrared and red edge bands was more sensitive to the AGB of D. tianschanicum, so selecting;The peak flowering period had the best estimation effect among different growth stages, and the fitting effect was the best in the multiple linear stepwise regression estimation model based on the fusion vegetation index. The model's R², $R_{a d j}^{2}$ and RMSE were 0.837, 0.831, and 7.357;Compared with vegetation index estimation models based on a single type, estimation models based on fused vegetation indices hadthe best fitting accuracy and better stability. 【Conclusion】 The fusion of vegetation index can effectively increase spectral information and improve model prediction accuracy.

Key words: drones; Diarthron tianschanicum aboveground biomass; vegetation index; visible light; multispectral

摘要：

【目的】研究多源数据估算天山假狼毒地上生物量(AGB)的能力。【方法】采用搭载可见光和多光谱传感器的无人机平台采集盛花期与结实期信息,获取可见光植被指数、多光谱植被指数及两者相融合的植被指数,分别以多元线性回归(MLR)、逐步线性回归(SMLR)、随机森林回归(RF)建立单一植被指数与融合植被指数的AGB估测模型,采用决定系数(R²)、调整后决定系数( $R_{a d j}^{2}$ )和均方根误差(RMSE)评价估算模型。【结果】(1)近红外和红边波段组合的植被指数对天山假狼毒AGB较为敏感,可以较好的估算天山假狼毒的AGB。(2)在不同生育期中,盛花期估算效果最佳;基于融合植被指数的多元线性逐步回归估测模型中拟合效果最佳,模型的R²、 $R_{a d j}^{2}$ 、RMSE为0.837、0.831和7.357。(3)与基于单一类型的植被指数估测模型相比,基于融合植被指数建立的估测模型拟合精度最佳、稳定性更好。【结论】融合植被指数可有效增加光谱信息,提高模型预测精度。

关键词: 无人机, 天山假狼毒地上生物量, 植被指数, 可见光, 多光谱

CLC Number:

S812

HOU Zhengqing, YAN An, XIE Kaiyun, YUAN Yilin, XIA Wenqiu, XIAO Shuting, ZHANG Zhenfei, SUN Zhe. Estimation of aboveground biomass of Diarthron tianschanicum based on vegetation index fusion[J]. Xinjiang Agricultural Sciences, 2024, 61(11): 2787-2796.

侯正清, 颜安, 谢开云, 袁以琳, 夏雯秋, 肖淑婷, 张振飞, 孙哲. 基于植被指数融合天山假狼毒地上生物量的估测[J]. 新疆农业科学, 2024, 61(11): 2787-2796.

Figures/Tables 10

Tab.1 Visible light and multispectral vegetation index and calculation formula

植被指数 Vegetation Indexes	计算公式 Formula	参考文献 References
红绿比值指数(RGRI)	r/g	[13]
红蓝比值指数RBRI	r/b	[13]
红绿植被指数(GRVI)	(g-r)/(g+r)	[13]
绿叶指数(GLA)	(2g-r-b)/(2*g+r+b)	[13]
改进型绿红植被指数(MGRVI)	(g²-r²)/(g²+r²)	[13]
地平面影像指数(GLI)	(2g-r-b)/(2g+r+b)	[13]
过绿指数减过红指数(EXGR)	2g-r-b-(1.4r-g)	[13]
彩色植被指数(CIVE)	0.441r-0.881g+0.385 6b+18.787 45	[13]
过红指数(ExR)	1.4r-g	[13]
大气阻抗植被指数VARI	(g-r)/(g+r-b)	[13]
重归一化植被指数(GRDVI)	(m₅-m₂)/(m₅+m₂)1/2	[13]
改进的非线性植被指数(MNLI)	(1.5 $m_{5}^{2}$ -1.5m₂)/( $m_{5}^{2}$ +m₁+0.5)	[13]
非线性植被指数(NLI)	( $m_{5}^{2}$ -m₁)/( $m_{5}^{2}$ +m₁)	[13]
归一化植被指数(NDVI)	(m₅-m₁)/(m₅+m₁)	[13]
绿色归一化植被指数(GNDVI)	(m₅-m₂)/(m₅+m₂)	[13]
非线性植被指数1(2NLI)	( $m_{5}^{2}$ -m₂)/( $m_{5}^{2}$ +m₂)	[13]
改进的非线性植被指数(GMNLI)	1.5( $m_{5}^{2}$ -m₂)/( $m_{5}^{2}$ +m₂+0.5)	[13]
绿色叶绿素指数(GCI)	(m₅/m₂)-1	[13]
红边叶绿素指数(RECI)	(m₅/m₄)-1	[13]
改进简单比值植被指数(MSR)	(m₅/m₁-1)/[(m₅/m₁)¹^/²+1]	[13]

Tab.1 Visible light and multispectral vegetation index and calculation formula

植被指数 Vegetation Indexes	计算公式 Formula	参考文献 References
红绿比值指数(RGRI)	r/g	[13]
红蓝比值指数RBRI	r/b	[13]
红绿植被指数(GRVI)	(g-r)/(g+r)	[13]
绿叶指数(GLA)	(2g-r-b)/(2*g+r+b)	[13]
改进型绿红植被指数(MGRVI)	(g²-r²)/(g²+r²)	[13]
地平面影像指数(GLI)	(2g-r-b)/(2g+r+b)	[13]
过绿指数减过红指数(EXGR)	2g-r-b-(1.4r-g)	[13]
彩色植被指数(CIVE)	0.441r-0.881g+0.385 6b+18.787 45	[13]
过红指数(ExR)	1.4r-g	[13]
大气阻抗植被指数VARI	(g-r)/(g+r-b)	[13]
重归一化植被指数(GRDVI)	(m₅-m₂)/(m₅+m₂)1/2	[13]
改进的非线性植被指数(MNLI)	(1.5 $m_{5}^{2}$ -1.5m₂)/( $m_{5}^{2}$ +m₁+0.5)	[13]
非线性植被指数(NLI)	( $m_{5}^{2}$ -m₁)/( $m_{5}^{2}$ +m₁)	[13]
归一化植被指数(NDVI)	(m₅-m₁)/(m₅+m₁)	[13]
绿色归一化植被指数(GNDVI)	(m₅-m₂)/(m₅+m₂)	[13]
非线性植被指数1(2NLI)	( $m_{5}^{2}$ -m₂)/( $m_{5}^{2}$ +m₂)	[13]
改进的非线性植被指数(GMNLI)	1.5( $m_{5}^{2}$ -m₂)/( $m_{5}^{2}$ +m₂+0.5)	[13]
绿色叶绿素指数(GCI)	(m₅/m₂)-1	[13]
红边叶绿素指数(RECI)	(m₅/m₄)-1	[13]
改进简单比值植被指数(MSR)	(m₅/m₁-1)/[(m₅/m₁)¹^/²+1]	[13]

Tab.2 Correlation between visible light vegetation index and Diarthron tianschanicum AGB

植被指数 Vegetation indexes	盛花期 Blooming stage	结实期 Fruiting stage
RGRI	0.633^**	-0.360^**
VARI	-0.599^**	0.345^**
EXR	0.482^**	-0.360^*
GRVI	0.381^**	0.362^**
GLA	0.374^**	0.333^**
MGRVI	-0.360^*	0.361^**
GLI	0.318^*	0.371^**
EXGR	0.384^**	0.368^**
CIVE	0.313^*	0.371^*
RBRI	0.321^*	-0.086

Tab.3 Correlation between multispectral vegetationindex and Diarthron tianschanicum AGB

植被指数 Vegetation indexes	盛花期 Blooming stage	结实期 Fruiting stage
GRDVI	0.660^**	0.483^**
MNLI	0.550^**	-0.352^**
NLI	0.471^**	-0.342^**
NDVI	0.458^**	0.438^**
GNDVI	0.457^**	0.463^**
2NLI	0.453^**	-0.431^**
GMNLI	0.446^**	-0.434^**
GCI	-0.439^**	0.560^**
MSR	-0.424^**	0.405^**
RECI	-0.407^**	0.473^**

Tab.4 Correlation between integrated vegetation index and Diarthron tianschanicum AGB

植被指数 Vegetation index	盛花期 Blooming stage	结实期 Fruiting stage
RGRI×GRDVI	0.768^**	0.415^**
RGRI×MNLI	0.538^**	-0.513^**
RGRI×NLI	0.534^**	-0.513^**
VARI×GRDVI	0.517^**	0.582^**
VARI×MNLI	0.535^**	0.370^**
VARI×NLI	0.535^**	0.348^**
EXR×GRDVI	0.520^**	-0.454^**
EXR×MNLI	0.537^**	-0.452^**
EXR×NLI	0.533^**	-0.452^**

Tab.5 Estimating the fitting accuracy of Diarthron tianschanicum AGB model based on visible light vegetation index

生育期 Growth stage	方法 Method	自变量 Independent variable	R²	${R^{2}}_{a d j}$	RMSE
盛花期 Blooming stage	SMLR	VARI、EXR、MGRVI	0.697	0.678	10.591
	MLR	RBRI、VARI、EXR、GLI、RGRI、MGRVI、 GRVI、GLA、EXGR、CIVE	0.711	0.645	10.587
	RF		0.720	0.685	8.263
结实期 Fruiting stage	SMLR	GLI	0.278	0.138	13.123
	MLR	RBRI、VARI、EXR、GLI、RGRI、MGRVI、 GRVI、GLA、EXGR、CIVE	0.344	0.3	12.852
	RF		0.483	0.465	9.776

Tab.5 Estimating the fitting accuracy of Diarthron tianschanicum AGB model based on visible light vegetation index

生育期 Growth stage	方法 Method	自变量 Independent variable	R²	${R^{2}}_{a d j}$	RMSE
盛花期 Blooming stage	SMLR	VARI、EXR、MGRVI	0.697	0.678	10.591
	MLR	RBRI、VARI、EXR、GLI、RGRI、MGRVI、 GRVI、GLA、EXGR、CIVE	0.711	0.645	10.587
	RF		0.720	0.685	8.263
结实期 Fruiting stage	SMLR	GLI	0.278	0.138	13.123
	MLR	RBRI、VARI、EXR、GLI、RGRI、MGRVI、 GRVI、GLA、EXGR、CIVE	0.344	0.3	12.852
	RF		0.483	0.465	9.776

Tab.6 Estimating the fitting accuracy of Diarthron tianschanicum AGB model based on multispectral vegetation index

生育期 Growth stage	方法 Method	自变量 Independent variable	R²	${R^{2}}_{a d j}$	RMSE
盛花期 Blooming stage	SMLR	MNLI、GRDVI、NDVI	0.763	0.747	8.988
	MLR	GMNLI、GRDVI、NDVI、RECI、MNLI、MSR、 GCI、NLI、GNDVI、2NLI	0.804	0.753	8.876
	RF		0.794	0.779	7.318
结实期 Fruiting stage	SMLR	MSR	0.349	0.355	10.877
	MLR	GMNLI、GRDVI、NDVI、RECI、MNLI、MSR、 GCI、NLI、GNDVI、2NLI	0.620	0.613	8.301
	RF		0.681	0.562	9.693

Tab.6 Estimating the fitting accuracy of Diarthron tianschanicum AGB model based on multispectral vegetation index

生育期 Growth stage	方法 Method	自变量 Independent variable	R²	${R^{2}}_{a d j}$	RMSE
盛花期 Blooming stage	SMLR	MNLI、GRDVI、NDVI	0.763	0.747	8.988
	MLR	GMNLI、GRDVI、NDVI、RECI、MNLI、MSR、 GCI、NLI、GNDVI、2NLI	0.804	0.753	8.876
	RF		0.794	0.779	7.318
结实期 Fruiting stage	SMLR	MSR	0.349	0.355	10.877
	MLR	GMNLI、GRDVI、NDVI、RECI、MNLI、MSR、 GCI、NLI、GNDVI、2NLI	0.620	0.613	8.301
	RF		0.681	0.562	9.693

Tab.7 Estimating the fitting accuracy of Diarthron tianschanicum AGB model based on fusion vegetation index

生育期 Growth stage	方法 Method	自变量 Independent variable	R²	${R^{2}}_{a d j}$	RMSE
盛花期 Blooming stage	SMLR	RGRI×GRDVI、VARI×GRDVI	0.837	0.831	7.357
	MLR	VARI×GRDVI、VARI×MNLI、RGRI×MNLI、 RGRI×NLI、EXR×GRDVI、EXR×MNLI、EXR×NLI、 VARI×NLI、RGRI×GRDVI	0.844	0.809	7.821
	RF		0.831	0.820	8.054
结实期 Fruiting stage	SMLR	VARI×GRDVI、VARI×NLI	0.603	0.586	9.057
	SMLR	VARI×GRDVI、VARI×NLI	0.627	0.573	9.194
	MLR	VARI×GRDVI、VARI×MNLI、RGRI×MNLI、 RGRI×NLI、EXR×GRDVI、EXR×MNLI、EXR×NLI、 VARI×NLI、RGRI×GRDVI	0.627	0.573	9.194
	MLR		0.719	0.627	7.249
	RF		0.719	0.627	7.249

Tab.7 Estimating the fitting accuracy of Diarthron tianschanicum AGB model based on fusion vegetation index

生育期 Growth stage	方法 Method	自变量 Independent variable	R²	${R^{2}}_{a d j}$	RMSE
盛花期 Blooming stage	SMLR	RGRI×GRDVI、VARI×GRDVI	0.837	0.831	7.357
	MLR	VARI×GRDVI、VARI×MNLI、RGRI×MNLI、 RGRI×NLI、EXR×GRDVI、EXR×MNLI、EXR×NLI、 VARI×NLI、RGRI×GRDVI	0.844	0.809	7.821
	RF		0.831	0.820	8.054
结实期 Fruiting stage	SMLR	VARI×GRDVI、VARI×NLI	0.603	0.586	9.057
	SMLR	VARI×GRDVI、VARI×NLI	0.627	0.573	9.194
	MLR	VARI×GRDVI、VARI×MNLI、RGRI×MNLI、 RGRI×NLI、EXR×GRDVI、EXR×MNLI、EXR×NLI、 VARI×NLI、RGRI×GRDVI	0.627	0.573	9.194
	MLR		0.719	0.627	7.249
	RF		0.719	0.627	7.249

Fig.1 Accuracy verification of estimating models for different growth stages of Diarthron tianschanicum based on visible light vegetation index

Fig.2 Validation of the precision of the estimating model for different growth stages of Diarthron tianschanicum based on multispectral vegetation index construction

Fig.3 Accuracy verification of estimating models for different growth stages of Diarthron tianschanicum based on fusion vegetation index construction

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