Research on Estimation Model of Winter Wheat Leaf Area Index based on Spectral and Texture Features of Sentinel-2A Image

波段	Sentinel⁃2A		分辨率 /m
波段	中心波长/nm	波段宽度/nm	分辨率 /m
1海岸波段	443.9	27	60
2蓝波段	496.6	98	10
3绿波段	560.0	45	10
4红波段	664.5	38	10
5植被红边波段1	703.9	19	20
6植被红边波段2	740.2	18	20
7植被红边波段3	782.5	28	20
8近红外波段（宽）	835.1	145	10
8a近红外波段（窄）	864.8	33	20
9水汽波段	945.0	26	60
10卷云波段	1373.5	75	60
11短波红外1	1613.7	143	20
12短波红外2	2202.4	242	20

Table 1. Appendix Table1　Abbreviation explanation of VI combined variable
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Table 1. Appendix Table1　Abbreviation explanation of VI combined variable
组合 VI₁ VI₂
V1 UNVI RVI
V2 NDVI RVI
V3 UNVI NDVI
V4 EVI SAVI
V5 SAVI RVI
V6 EVI RVI
V7 NDVI NIRv
V8 NDVI SAVI
V9 NIRv RVI
V10 UNVI NIRv
V11 UNVI SAVI
V12 NDVI EVI
V13 NIRv SAVI
V14 UNVI EVI
V15 EVI NIRv

Table 2. Appendix Table2　Abbreviation explanation of Texture combined variable
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Table 2. Appendix Table2　Abbreviation explanation of Texture combined variable
组合 Texture₁ Texture₂
T1 MEA_RE1 ENT_NIR(Z)
T2 MEA_RE1 HOM_NIR(Z)
T3 MEA_Red ENT_NIR(Z)
T4 MEA_Red HOM_NIR(Z)
T5 MEA_SWIR2 HOM_NIR(Z)
T6 MEA_RE1 MEA_NIR(Z)
T7 MEA_RE1 MEA_Red
T8 MEA_SWIR2 ENT_NIR(Z)
T9 MEA_RE1 MEA_RE3
T10 MEA_NIR(Z) MEA_SWIR1

Table 2. LAI statistical data of winter wheat in training set and verification set
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Table 2. LAI statistical data of winter wheat in training set and verification set
数量范围均值标准差变异系数/%
107 1.80~6.68 4.40 1.21 27.50
训练集
74 1.80~6.18 4.28 1.19 27.80
测试集
33 2.24~6.68 4.66 1.22 26.20
全集合

Table 3. Appendix Table3　Abbreviation explanation of NDTI combined variable

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Table 3. Appendix Table3　Abbreviation explanation of NDTI combined variable

组合	NDTI₁		NDTI₂
N1	MEA_RE1	MEA_RE2	MEA_RE2	MEA_NIR(Z)
N2	MEA_RE1	MEA_RE2	MEA_RE2	MEA_SWIR1
N3	MEA_RE1	MEA_RE2	MEA_NIR(Z)	MEA_SWIR1
N4	MEA_RE1	MEA_RE2	MEA_RE3	MEA_SWIR1
N5	MEA_RE1	MEA_RE2	MEA_RE2	MEA_SWIR2
N6	MEA_RE1	MEA_RE2	MEA_NIR(Z)	MEA_SWIR2
N7	MEA_RE1	MEA_RE2	MEA_RE3	MEA_SWIR2
N8	MEA_RE1	MEA_RE3	MEA_RE2	MEA_NIR(Z)
N9	MEA_RE1	MEA_NIR(Z)	MEA_RE2	MEA_NIR(Z)
N10	MEA_RE1	MEA_NIR(Z)	MEA_RE3	MEA_SWIR1

Table 3. Calculation formula of vegetation index

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Table 3. Calculation formula of vegetation index

植被指数	计算公式
通用归一化植被指数UNVI	$U N V I = \frac{C_{v} - 0.1 * C_{s} - C_{4}}{C_{w} + C_{v} + C_{s}}$
归一化植被指数NDVI	$N D V I = \frac{R_{N I R} - R_{R e d}}{R_{N I R} + R_{R e d}}$
增强型植被指数EVI	$E V I = \frac{2.5 * (R_{N I R} - R_{R e d})}{R_{N I R} + 6 * R_{R e d} - 7.5 * R_{B l u e} + 1}$
植被近红外反射率植被指数NIRv	$N I R v = N D V I * N I R$
土壤调整型植被指数SAVI	$S A V I = \frac{(R_{N I R} - R_{R e d}) * (1 + 0.5)}{R_{N I R} + R_{R e d} + 0.5}$
比值植被指数RVI	$R V I = \frac{R_{N I R}}{R_{R e d}}$

Table 4. Appendix Table4　Abbreviation explanation of RTI combined variable

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Table 4. Appendix Table4　Abbreviation explanation of RTI combined variable

组合	RTI₁		RTI₂
R1	MEA_NIR(Z)	MEA_SWIR1	MEA_RE2	MEA_SWIR1
R2	MEA_NIR(Z)	MEA_SWIR1	MEA_RE3	MEA_SWIR1
R3	MEA_RE3	MEA_SWIR1	MEA_RE2	MEA_SWIR1
R4	MEA_NIR(Z)	MEA_SWIR1	MEA_RE3	MEA_SWIR2
R5	MEA_NIR(Z)	MEA_SWIR1	MEA_NIR(Z)	MEA_SWIR2
R6	MEA_RE3	MEA_SWIR1	MEA_NIR(Z)	MEA_SWIR2
R7	MEA_RE3	MEA_SWIR1	MEA_RE3	MEA_SWIR2
R8	MEA_NIR(Z)	MEA_SWIR1	MEA_RE1	MEA_RE2
R9	MEA_RE3	MEA_SWIR1	MEA_RE1	MEA_RE2
R10	MEA_NIR(Z)	MEA_SWIR1	MEA_RE1	MEA_NIR(Z)

Table 4. Correlation coefficient between LAI and texture features （top ten）
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Table 4. Correlation coefficient between LAI and texture features （top ten）
纹理特征 r
MEA_NIR(Z) 0.842
MEA_Blue 0.840
MEA_RE3 0.839
MEA_RE1 0.827
MEA_Red 0.810
MEA_SWIR2 0.805
MEA_SWIR1 0.761
MEA_Green 0.735
MEA_RE2 0.671
ENT_NIR(Z) 0.416

Table 5. Correlation coefficient between LAI and NDTI （top ten）

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Table 5. Correlation coefficient between LAI and NDTI （top ten）

纹理指数	纹理特征		r
纹理指数	T₁	T₂	r
NDTI	MEA_RE1	MEA_RE3	0.859
	MEA_RE1	MEA_NIR(Z)	0.858
	MEA_RE1	MEA_RE2	0.857
	MEA_RE3	MEA_SWIR1	0.846
	MEA_RE2	MEA_RE3	0.845
	MEA_NIR(Z)	MEA_SWIR1	0.845
	MEA_RE2	MEA_NIR(Z)	0.843
	MEA_Blue	MEA_RE2	0.842
	MEA_Blue	MEA_RE3	0.842
	MEA_Blue	MEA_NIR(Z)	0.841

Table 5. Appendix Table5　Abbreviation explanation of DTI combined variable

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Table 5. Appendix Table5　Abbreviation explanation of DTI combined variable

组合	DTI₁		DTI₂
D1	MEA_RE1	VAR_RE2	MEA_Red	ENT_NIR(Z)
D2	MEA_RE1	ENT_NIR(Z)	VAR_RE2	MEA_SWIR2
D3	MEA_RE1	ENT_NIR(Z)	MEA_RE1	CON_RE2
D4	MEA_RE1	ENT_NIR(Z)	MEA_RE1	VAR_RE2
D5	MEA_Red	ENT_NIR(Z)	MEA_RE1	CON_RE2
D6	VAR_Red	MEA_RE1	MEA_Red	ENT_NIR(Z)
D7	MEA_RE1	DIS_RE2	MEA_Red	ENT_NIR(Z)
D8	MEA_RE1	ENT_NIR(Z)	MEA_RE1	DIS_RE2
D9	MEA_RE1	ENT_NIR(Z)	MEA_Red	ENT_NIR(Z)
D10	MEA_RE1	ENT_NIR(Z)	VAR_Red	MEA_RE1

Table 6. Appendix Table6　Abbreviation explanation of VI and Texture combined variable
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Table 6. Appendix Table6　Abbreviation explanation of VI and Texture combined variable
组合 VI Texture
VT1 UNVI ENT_NIR(Z)
VT2 UNVI HOM_NIR(Z)
VT3 RVI ENT_NIR(Z)
VT4 RVI MEA_SWIR2
VT5 RVI MEA_SWIR1
VT6 RVI MEA_RE1
VT7 RVI HOM_NIR(Z)
VT8 UNVI MEA_Green
VT9 UNVI MEA_Red
VT10 RVI MEA_Blue

Table 6. Correlation coefficient between LAI and RTI （top ten）

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Table 6. Correlation coefficient between LAI and RTI （top ten）

纹理指数	纹理特征		r
纹理指数	T₁	T₂	r
RTI	MEA_RE1	MEA_RE3	0.854
	MEA_RE1	MEA_RE2	0.854
	MEA_RE1	MEA_NIR(Z)	0.853
	MEA_NIR(Z)	MEA_SWIR1	0.850
	MEA_RE3	MEA_SWIR1	0.849
	MEA_RE2	MEA_RE3	0.846
	MEA_RE2	MEA_NIR(Z)	0.842
	MEA_Blue	MEA_RE2	0.842
	MEA_Blue	MEA_RE3	0.841
	MEA_Blue	MEA_SWIR1	0.840

Table 7. Appendix Table7　Abbreviation explanation of VI and NDTI combined variable

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Table 7. Appendix Table7　Abbreviation explanation of VI and NDTI combined variable

组合	VI	NDTI
VN1	RVI	MEA_RE2	MEA_SWIR1
VN2	RVI	MEA_NIR(Z)	MEA_SWIR1
VN3	RVI	MEA_RE3	MEA_SWIR1
VN4	RVI	MEA_RE2	MEA_SWIR2
VN5	RVI	MEA_NIR(Z)	MEA_SWIR2
VN6	RVI	MEA_RE3	MEA_SWIR2
VN7	RVI	MEA_RE1	MEA_RE2
VN8	RVI	MEA_RE1	MEA_NIR(Z)
VN9	RVI	MEA_RE1	MEA_RE3
VN10	UNVI	MEA_RE2	MEA_NIR(Z)

Table 7. Correlation coefficient between LAI and DTI （top ten）

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Table 7. Correlation coefficient between LAI and DTI （top ten）

纹理指数	纹理特征		r
纹理指数	T₁	T₂	r
DTI	MEA_Blue	VAR_Green	0.867
	MEA_RE1	MEA_NIR(Z)	0.861
	MEA_RE1	MEA_RE3	0.859
	MEA_NIR(Z)	MEA_SWIR1	0.859
	MEA_RE2	MEA_NIR(Z)	0.859
	MEA_RE1	ENT_NIR(Z)	0.858
	MEA_RE3	MEA_SWIR1	0.857
	MEA_RE2	MEA_RE3	0.856
	MEA_NIR(Z)	MEA_SWIR2	0.854
	MEA_RE3	MEA_SWIR2	0.852

Table 8. Appendix Table8　Abbreviation explanation of VI and RTI combined variable

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Table 8. Appendix Table8　Abbreviation explanation of VI and RTI combined variable

组合	VI	RTI
VR1	RVI	MEA_RE2	MEA_SWIR1
VR2	RVI	MEA_NIR(Z)	MEA_SWIR1
VR3	RVI	MEA_RE3	MEA_SWIR1
VR4	RVI	MEA_RE1	MEA_RE2
VR5	RVI	MEA_RE1	MEA_RE3
VR6	RVI	MEA_RE1	MEA_NIR(Z)
VR7	UNVI	MEA_RE1	MEA_NIR(Z)
VR8	UNVI	MEA_RE1	MEA_RE3
VR9	UNVI	MEA_RE2	MEA_NIR(Z)
VR10	UNVI	MEA_RE1	MEA_RE2

Table 8. Determination coefficient of LAI inversion by SR-NDTIs （top ten）

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Table 8. Determination coefficient of LAI inversion by SR-NDTIs （top ten）

回归方法	纹理特征NDTI		R²	RMSE	rRMSE/%
回归方法	T₁	T₂	R²	RMSE	rRMSE/%
SR	MEA_RE1	MEA_NIR(Z)	0.732	0.631	13.53
	MEA_RE1	MEA_RE3	0.732	0.632	13.55
	MEA_RE1	MEA_RE2	0.726	0.639	13.70
	MEA_NIR(Z)	MEA_SWIR1	0.723	0.642	13.77
	MEA_RE3	MEA_SWIR1	0.722	0.644	13.81
	MEA_RE2	MEA_SWIR1	0.710	0.658	14.10
	MEA_NIR(Z)	MEA_SWIR2	0.702	0.666	14.28
	MEA_RE3	MEA_SWIR2	0.701	0.668	14.31
	MEA_RE2	MEA_SWIR2	0.691	0.679	14.55
	MEA_RE2	MEA_NIR(Z)	0.688	0.682	14.62

Table 9. Determination coefficient of LAI inversion by SR-RTIs （top ten）

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Table 9. Determination coefficient of LAI inversion by SR-RTIs （top ten）

回归方法	纹理特征RTI		R²	RMSE	rRMSE/%
回归方法	T₁	T₂	R²	RMSE	rRMSE/%
SR	MEA_NIR(Z)	MEA_SWIR1	0.745	0.617	13.22
	MEA_RE3	MEA_SWIR1	0.740	0.622	13.34
	MEA_RE1	MEA_NIR(Z)	0.726	0.639	13.69
	MEA_RE1	MEA_RE2	0.726	0.639	13.70
	MEA_RE1	MEA_RE3	0.726	0.639	13.70
	MEA_RE2	MEA_SWIR1	0.720	0.646	13.85
	MEA_NIR(Z)	MEA_SWIR2	0.692	0.678	14.53
	MEA_RE2	MEA_NIR(Z)	0.687	0.683	14.63
	MEA_RE3	MEA_SWIR2	0.684	0.686	14.71
	MEA_RE2	MEA_RE3	0.683	0.687	14.74

Table 9. Appendix Table9　Abbreviation explanation of VI and DTI combined variable

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Table 9. Appendix Table9　Abbreviation explanation of VI and DTI combined variable

组合	VI	DTI
VD1	RVI	MEA_RE1	ENT_NIR(Z)
VD2	RVI	ENT_NIR(Z)	MEA_SWIR2
VD3	UNVI	MEA_RE1	ENT_NIR(Z)
VD4	UNVI	MEA_Red	ENT_NIR(Z)
VD5	RVI	VAR_RE2	MEA_SWIR2
VD6	RVI	MEA_Red	ENT_NIR(Z)
VD7	RVI	MEA_RE1	DIS_NIR(Z)
VD8	RVI	MEA_RE1	VAR_RE2
VD9	RVI	MEA_RE1	CON_RE2
VD10	RVI	MEA_RE1	DIS_RE2

Table 10. Determination coefficient of LAI inversion by SR-DTIs （top ten）

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Table 10. Determination coefficient of LAI inversion by SR-DTIs （top ten）

回归方法	纹理特征DTI		R²	RMSE	rRMSE/%
回归方法	T₁	T₂	R²	RMSE	rRMSE/%
SR	MEA_RE1	MEA_NIR(Z)	0.775	0.579	12.41
	ENT_NIR(Z)	MEA_SWIR2	0.735	0.629	13.48
	MEA_RE1	VAR_RE2	0.730	0.634	13.60
	VAR_Red	MEA_RE1	0.721	0.645	13.82
	MEA_RE1	DIS_RE2	0.719	0.647	13.87
	MEA_Red	ENT_NIR(Z)	0.716	0.651	13.95
	MEA_RE1	DIS_NIR(Z)	0.713	0.653	14.01
	VAR_RE2	MEA_SWIR2	0.713	0.654	14.02
	MEA_RE1	CON_RE2	0.706	0.661	14.18
	MEA_Blue	VAR_Green	0.706	0.661	14.18

Table 11. Results of MLR and RFR LAI inversion based on multivariate combination

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Table 11. Results of MLR and RFR LAI inversion based on multivariate combination

回归方法	V			V+T			V+N
回归方法	R²	RMSE	rRMSE(%)	R²	RMSE	rRMSE(%)	R²	RMSE	rRMSE(%)
RFR	0.709	0.659	14.13	0.717	0.649	13.91	0.716	0.651	13.95
MLR	0.682	0.688	14.75	0.712	0.655	14.05	0.765	0.591	12.67
回归方法	V+R			V+D			V+T+TI
回归方法	R²	RMSE	rRMSE(%)	R²	RMSE	rRMSE(%)	R²	RMSE	rRMSE(%)
RFR	0.724	0.641	13.74	0.761	0.597	12.80	0.763	0.594	12.73
MLR	0.702	0.667	14.29	0.761	0.597	12.80	0.556	0.814	17.44

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Jiahua CHEN, Lifu ZHANG, Changping HUANG, Ping LANG, Xiaoyan KANG. Research on Estimation Model of Winter Wheat Leaf Area Index based on Spectral and Texture Features of Sentinel-2A Image[J]. Remote Sensing Technology and Application, 2024, 39(2): 290

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Paper Information

Category: Research Articles

Received: Dec. 28, 2022

Accepted: --

Published Online: Aug. 13, 2024

The Author Email: CHEN Jiahua (chenjiahua20@mails.ucas.ac.cn)

DOI:10.11873/j.issn.1004-0323.2024.2.0290

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Band information of S2A

Table 1. Band information of S2A

Table 1. Appendix Table1 Abbreviation explanation of VI combined variable

Table 1. Appendix Table1 Abbreviation explanation of VI combined variable

Table 2. Appendix Table2 Abbreviation explanation of Texture combined variable

Table 2. Appendix Table2 Abbreviation explanation of Texture combined variable

Table 2. LAI statistical data of winter wheat in training set and verification set

Table 2. LAI statistical data of winter wheat in training set and verification set

Table 3. Appendix Table3 Abbreviation explanation of NDTI combined variable

Table 3. Appendix Table3 Abbreviation explanation of NDTI combined variable

Table 3. Calculation formula of vegetation index

Table 3. Calculation formula of vegetation index

Table 4. Appendix Table4 Abbreviation explanation of RTI combined variable

Table 4. Appendix Table4 Abbreviation explanation of RTI combined variable

Table 4. Correlation coefficient between LAI and texture features （top ten）

Table 4. Correlation coefficient between LAI and texture features （top ten）

Table 5. Correlation coefficient between LAI and NDTI （top ten）

Table 5. Correlation coefficient between LAI and NDTI （top ten）

Table 5. Appendix Table5 Abbreviation explanation of DTI combined variable

Table 5. Appendix Table5 Abbreviation explanation of DTI combined variable

Table 6. Appendix Table6 Abbreviation explanation of VI and Texture combined variable

Table 6. Appendix Table6 Abbreviation explanation of VI and Texture combined variable

Table 6. Correlation coefficient between LAI and RTI （top ten）

Table 6. Correlation coefficient between LAI and RTI （top ten）

Table 7. Appendix Table7 Abbreviation explanation of VI and NDTI combined variable

Table 7. Appendix Table7 Abbreviation explanation of VI and NDTI combined variable

Table 7. Correlation coefficient between LAI and DTI （top ten）

Table 7. Correlation coefficient between LAI and DTI （top ten）

Table 8. Appendix Table8 Abbreviation explanation of VI and RTI combined variable

Table 8. Appendix Table8 Abbreviation explanation of VI and RTI combined variable

Table 8. Determination coefficient of LAI inversion by SR-NDTIs （top ten）

Table 8. Determination coefficient of LAI inversion by SR-NDTIs （top ten）

Table 9. Determination coefficient of LAI inversion by SR-RTIs （top ten）

Table 9. Determination coefficient of LAI inversion by SR-RTIs （top ten）

Table 9. Appendix Table9 Abbreviation explanation of VI and DTI combined variable

Table 9. Appendix Table9 Abbreviation explanation of VI and DTI combined variable

Table 10. Determination coefficient of LAI inversion by SR-DTIs （top ten）

Table 10. Determination coefficient of LAI inversion by SR-DTIs （top ten）

Table 11. Results of MLR and RFR LAI inversion based on multivariate combination

Table 11. Results of MLR and RFR LAI inversion based on multivariate combination

Table 1. Appendix Table1　Abbreviation explanation of VI combined variable

Table 1. Appendix Table1　Abbreviation explanation of VI combined variable

Table 2. Appendix Table2　Abbreviation explanation of Texture combined variable

Table 2. Appendix Table2　Abbreviation explanation of Texture combined variable

Table 3. Appendix Table3　Abbreviation explanation of NDTI combined variable

Table 3. Appendix Table3　Abbreviation explanation of NDTI combined variable

Table 4. Appendix Table4　Abbreviation explanation of RTI combined variable

Table 4. Appendix Table4　Abbreviation explanation of RTI combined variable

Table 5. Appendix Table5　Abbreviation explanation of DTI combined variable

Table 5. Appendix Table5　Abbreviation explanation of DTI combined variable

Table 6. Appendix Table6　Abbreviation explanation of VI and Texture combined variable

Table 6. Appendix Table6　Abbreviation explanation of VI and Texture combined variable

Table 7. Appendix Table7　Abbreviation explanation of VI and NDTI combined variable

Table 7. Appendix Table7　Abbreviation explanation of VI and NDTI combined variable

Table 8. Appendix Table8　Abbreviation explanation of VI and RTI combined variable

Table 8. Appendix Table8　Abbreviation explanation of VI and RTI combined variable

Table 9. Appendix Table9　Abbreviation explanation of VI and DTI combined variable

Table 9. Appendix Table9　Abbreviation explanation of VI and DTI combined variable