Estimation of Potato Above Ground Biomass Based on UAV Multispectral Images

doi:10.3964/j.issn.1000-0593(2021)08-2549-07

Spectroscopy and Spectral Analysis, Volume. 41, Issue 8, 2549(2021)

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Table 1. Band parameters of multispectral sensor
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Table 1. Band parameters of multispectral sensor
波段中心波长/nm 带宽/nm
绿 550 40
红 660 40
红边 735 10
近红外 790 40

Table 2. Model parameters

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Table 2. Model parameters

光谱变量	计算公式	参考文献
GREVI	GREVI=GRE	本工作
REDVI	REDVI=RED	本工作
REGVI	REGVI=REG	本工作
NIRVI	NIRVI=NIR	本工作
RVI	RVI=NIR/RED	[10]
MSR	MSR=(NIR/RED-1)/(NIR/RED+1)^1/2	[11]
GNDVI	GNDVI=(NIR-GRE)/(NIR+GRE)	[11]
NLI	NLI=(NIR²-RED)/(NIR²+RED)	[7]
SAVI	SAVI=1.5×(NIR-RED)/(NIR+RED+0.5)	[10]
RDVI	RDVI=(NIR-RED)/(NIR+RED)^1/2	[7]
OSAVI	OSAVI=1.16×(NIR-RED)/(NIR+RED+0.16)	[11]
DVI	DVI=NIR-RED	[7]
NDVI	NDVI=(NIR-RED)/(NIR+RED)	[11]

Table 3. The correlation coefficients of vegetation indices and Hdsm with potato AGB

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Table 3. The correlation coefficients of vegetation indices and Hdsm with potato AGB

模型参数	块茎形成期	块茎增长期	淀粉积累期
GREVI	0.686	0.659	0.672
REDVI	0.421	0.621	0.494
REGVI	0.703	0.721	0.727
NIRVI	0.684	0.731	0.724
RVI	0.750	0.727	0.744
MSR	0.739	0.741	0.746
GNDVI	0.718	0.762	0.759
NLI	0.716	0.748	0.747
SAVI	0.712	0.748	0.747
RDVI	0.712	0.749	0.747
OSAVI	0.711	0.747	0.747
DVI	0.710	0.750	0.746
NDVI	0.711	0.745	0.747
REGHL	0.709	0.711	0.700
REGLH	0.695	0.734	0.678
REGLL	0.721	0.744	0.732
Hdsm	0.606	0.682	0.564

Table 4. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices

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Table 4. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices

生育期	模型参数	PLSR				RR
		建模		验证		建模		验证
		R²	NRMSE/%	R²	NRMSE/%	R²	NRMSE/%	R²	NRMSE/%
块茎形成期	SVIs	0.48	20.12	0.59	19.21	0.46	21.61	0.55	20.14
块茎形成期	MVIs	0.61	18.34	0.64	17.37	0.59	19.58	0.62	18.83
块茎增长期	SVIs	0.58	18.26	0.61	17.18	0.53	19.58	0.58	18.78
块茎增长期	MVIs	0.65	17.48	0.68	16.71	0.62	18.42	0.65	17.75
淀粉积累期	SVIs	0.46	23.68	0.54	22.84	0.42	24.09	0.49	23.87
淀粉积累期	MVIs	0.59	21.45	0.62	20.96	0.56	23.34	0.60	22.85

Table 5. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices combined with HFI or Hdsm

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Table 5. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices combined with HFI or Hdsm

生育期	模型参数	PLSR				RR
		建模		验证		建模		验证
		R²	NRMSE/%	R²	NRMSE/%	R²	NRMSE/%	R²	NRMSE/%
块茎形成期	VIs+Hdsm	0.65	17.42	0.67	16.16	0.60	18.86	0.65	17.19
块茎形成期	VIs+HFI	0.68	16.56	0.70	15.46	0.62	17.61	0.68	16.74
块茎增长期	VIs+Hdsm	0.68	16.07	0.71	15.84	0.65	17.58	0.69	16.95
块茎增长期	VIs+HFI	0.72	15.44	0.74	15.33	0.67	16.34	0.70	15.62
淀粉积累期	VIs+Hdsm	0.62	20.34	0.64	19.53	0.58	21.03	0.63	20.72
淀粉积累期	VIs+HFI	0.63	19.36	0.66	18.85	0.61	20.17	0.65	19.98

Table 6. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices combined with HFI and Hdsm

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Table 6. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices combined with HFI and Hdsm

生育期	模型参数	PLSR				RR
		建模		验证		建模		验证
		R²	NRMSE/%	R²	NRMSE/%	R²	NRMSE/%	R²	NRMSE/%
块茎形成期	VIs+Hdsm+HFI	0.70	16.46	0.71	15.08	0.66	16.98	0.68	16.33
块茎增长期	VIs+Hdsm+HFI	0.73	15.22	0.75	14.62	0.69	15.56	0.71	15.47
淀粉积累期	VIs+Hdsm+HFI	0.65	18.83	0.68	17.62	0.64	19.17	0.67	18.26

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. Estimation of Potato Above Ground Biomass Based on UAV Multispectral Images[J]. Spectroscopy and Spectral Analysis, 2021, 41(8): 2549

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Paper Information

Category: Research Articles

Received: Mar. 11, 2021

Accepted: --

Published Online: Sep. 8, 2021

The Author Email:

DOI:10.3964/j.issn.1000-0593(2021)08-2549-07

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Band parameters of multispectral sensor

Table 1. Band parameters of multispectral sensor

Table 2. Model parameters

Table 2. Model parameters

Table 3. The correlation coefficients of vegetation indices and Hdsm with potato AGB

Table 3. The correlation coefficients of vegetation indices and Hdsm with potato AGB

Table 4. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices

Table 4. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices

Table 5. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices combined with HFI or Hdsm

Table 5. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices combined with HFI or Hdsm

Table 6. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices combined with HFI and Hdsm

Table 6. Estimation of potato AGB using partial least squares regression and ridge regression based on vegetation indices combined with HFI and Hdsm