A New Copper Stress Vegetation Index NCSVI Explores the Sensitive Range of Corn Leaves Spectral Under Copper Pollution

Tian XIA; Ke-ming YANG; Fei-sheng FENG; Hui GUO; Chao ZHANG

doi:10.3964/j.issn.1000-0593(2021)08-2604-07

Journals >Spectroscopy and Spectral Analysis >Volume 41 >Issue 8 >Page 2604 > Article

Spectroscopy and Spectral Analysis
Vol. 41, Issue 8, 2604 (2021)

A New Copper Stress Vegetation Index NCSVI Explores the Sensitive Range of Corn Leaves Spectral Under Copper Pollution

Tian XIA^{1、1; *;}, Ke-ming YANG^2、2;, Fei-sheng FENG^3、3;, Hui GUO^4、4;, and Chao ZHANG^2、2;

Author Affiliations

¹1. China Centre for Resources Satellite Data and Application, Beijing 100094, China

²2. College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China

³3. State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mine, Anhui University of Science and Technology, Huainan 232001, China

⁴4. School of Surveying and Mapping, Anhui University of Science and Technology, Huainan 232001, China

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DOI: 10.3964/j.issn.1000-0593(2021)08-2604-07 Cite this Article

Tian XIA, Ke-ming YANG, Fei-sheng FENG, Hui GUO, Chao ZHANG. A New Copper Stress Vegetation Index NCSVI Explores the Sensitive Range of Corn Leaves Spectral Under Copper Pollution[J]. Spectroscopy and Spectral Analysis, 2021, 41(8): 2604 Copy Citation Text

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Fig. 1. The growth process of corn

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Fig. 2. The Spectral of corn leaves in 2016

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Fig. 3. The Spectral of corn leaves in 2014

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Fig. 4. Schematic diagram of the spectral subintervals in corn leaves

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Fig. 5. Correlation between VIs and Cu²⁺ contents in corn leaves by experiment in 2016

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Fig. 6. Correlation between VIs and Cu²⁺ contents in corn leaves by experiment in 2014

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样品年份	样品编号	胁迫浓度/ (μg·g^-1)	Cu²⁺含量/ (μg·g^-1)
2016	Cu(0)	0	9.77
	Cu(200)	200	31.29
	Cu(300)	300	75.78
	Cu(500)	500	54.51
	Cu(700)	700	114.79
2014	Cu(0)	0	1.08
	Cu(250)	250	4.96
	Cu(500)	500	9.46

Table 1. Cu²⁺ contents in corn leaves

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植被指数	名称	计算公式
WBI	水波段指数	R₉₀₀/R₉₇₀
MCARI	改进的叶绿素吸收率指数	((R₇₀₀-R₆₇₀)-0.2(R₇₀₀-R₅₅₀))(R₇₀₀/R₆₇₀)
NDWI	归一化水指数	(R₈₆₀-R_{1 240})/(R₈₆₀+R_{1 240})

Table 2. Computing formula of vegetation indexes

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指数	子区间	Cu(0)	Cu(200)	Cu(300)	Cu(500)	Cu(700)	R	RMSE
NCSVI	350~430 nm(紫谷)	0.33	0.37	0.27	0.34	0.16	-0.88	17.09
	430~530 nm(蓝边)	0.29	0.33	0.23	0.32	0.12	-0.85	19.22
	530~580 nm(绿峰)	0.12	0.12	0.04	0.10	-0.09	-0.94^*	12.57
	580~650 nm(黄边)	0.16	0.26	0.06	0.15	-0.06	-0.88	17.47
	650~690 nm(红谷)	0.21	0.27	0.15	0.25	0.03	-0.84	19.64
	690~750 nm(红边)	-0.05	-0.07	-0.12	-0.07	-0.17	-0.97^*	8.71
	750~1 301 nm(近红外平台)	-0.13	-0.12	-0.15	-0.13	-0.19	-0.87	17.97
	1 301~1 500 nm(近谷)	0.11	0.11	0.07	0.11	0.01	-0.94^*	12.71
	1 500~1 590 nm(近边)	0.09	0.18	0.03	0.08	-0.02	-0.82	20.68
	1 590~1 919 nm(近峰 A)	0.06	0.05	0.01	0.04	-0.05	-0.96^*	10.06
	1 919~2 500 nm(近峰 B)	0.18	0.28	0.12	0.17	0.06	-0.79	22.09
WBI	-	1.05	1.03	1.03	1.04	1.03	-0.68	26.63
MCARI	-	16.95	28.03	33.49	29.71	30.57	0.75	24.21
NDWI	-	0.06	0.04	0.04	0.05	0.04	-0.65	27.48

Table 3. Statistics and correlation calculation results of NCSVI and conventional VIs by experiment in 2016

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指数	子区间	Cu(0)	Cu(250)	Cu(500)	r	RMSE
NCSVI	350~430 nm(紫谷)	0.40	0.39	0.39	-0.75	2.25
	430~530 nm(蓝边)	0.36	0.35	0.36	0.61	2.71
	530~580 nm(绿峰)	0.21	0.19	0.18	-0.90^*	1.50
	580~650 nm(黄边)	0.32	0.30	0.30	-0.79	2.08
	650~690 nm(红谷)	0.37	0.36	0.37	0.19	3.36
	690~750 nm(红边)	0.04	0.02	0.01	-0.97^*	0.85
	750~1 301 nm(近红外平台)	-0.10	-0.10	-0.10	-0.27	3.30
	1 301~1 500 nm(近谷)	0.16	0.15	0.14	-0.97^*	0.78
	1 500~1 590 nm(近边)	0.13	0.12	0.11	-0.89	1.58
	1 590~1 919 nm(近峰 A)	0.09	0.08	0.08	-0.93^*	1.29
	1 919~2 500 nm(近峰 B)	0.23	0.21	0.21	-0.80	2.04
WBI	-	0.99	1.03	1.03	0.81	2.02
MCARI	-	14.43	12.75	16.00	0.52	2.92
NDWI	-	0.07	0.05	0.05	-0.85	1.78

Table 4. Statistics and correlation calculation results of NCSVI and conventional VIs by experiment in 2014

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