Remote Sensing Inversion of Leaf and Canopy Water Content in Different Growth Stages of Summer Maize

Liu Erhua; Zhou Guangsheng; Zhou Li; Zhang Feng

doi:10.11898/1001-7313.20200105

Vol.31, NO.1, 2020

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Liu Erhua, Zhou Guangsheng, Zhou Li, et al. Remote sensing inversion of leaf and canopy water content in different growth stages of summer maize. J Appl Meteor Sci, 2020, 31(1): 52-62. DOI: 10.11898/1001-7313.20200105.

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Liu Erhua, Zhou Guangsheng, Zhou Li, et al. Remote sensing inversion of leaf and canopy water content in different growth stages of summer maize. J Appl Meteor Sci, 2020, 31(1): 52-62. DOI: 10.11898/1001-7313.20200105.

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Remote Sensing Inversion of Leaf and Canopy Water Content in Different Growth Stages of Summer Maize

DOI: 10.11898/1001-7313.20200105

1.
Chinese Academy of Meteorological Sciences, Beijing 100081
2.
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044
3.
State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093

Received Date: 2019-03-19
Rev Recd Date: 2019-07-11
Publish Date: 2020-01-31

Abstract

Abstract

Hyperspectral remote sensing technology is an important method for crop water monitoring, aiming to understand crop growth status. In order to achieve rapid, refined and comprehensive monitoring for the leaf and canopy water content of summer maize in different growth stages, controlled experiments are implemented during different growth stages of the summer maize with different irrigation water drought simulation test in North China. The water content of vegetation index (W_I), water stress index (M_SI), global vegetation moisture index (G_VMI), compound ratio index (W_NV and W_CG) and reflectance curve area (D_area) of summer maize are defined for inversion models of equivalent water thickness for canopy (E_WTC) and fuel moisture content for leaf (F_MC). The hyperspectral remote sensing inversion models of moisture content of summer maize in 2014 are verified by using drought simulation data of different irrigation water amount during different growth periods in 2015. Results show that W_I, M_SI, G_VMI, W_NV, W_CG and D_area for inversion E_WTC of summer maize at the three-leaf stage doesn't pass the significance test of 0.05 level, but all the indices estimation E_WTC models after the three-leaf stage pass the significance test of 0.01 level. The model accuracy for different stages from high to low are as follows: Tasseling stage, knotting stage, filling stage, mature stage, and seven-leaf stage. F_MC at the seven-leaf stage and jointing stage is retrieved by 6 special indicators and all of them pass the significance test of 0.01 level. F_MC at the three-leaf stage is retrieved by W_NV index, but 6 spectral indicators after jointing stage cannot retrieve F_MC of summer maize. In summary, the difference of precision of the same spectral indicator to retrieve the water content of summer maize is obvious in different growth stages. The retrieved water content precision is higher for middle summer maize growth period, but relatively lower for early and late remote sensing. Although canopy and leaf scale water content indices can reflect the drought situation of summer maize, considering the precision of spectral indicator retrieval of two scale water content indices of summer maize is closely related to the growth period of summer maize, a retrieval model of water content is proposed for different growth stages of summer maize to provide accurate simulation of water content in summer maiz growth.
- hyperspectral;
- summer maize;
- vegetation water content index;
- complex ratio index;
- different growth stages

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References(34)

Figures and Tables

Fig. 1 Variation characteristics of water content in summer maize growth stages

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Fig. 2 Variation characteristics of spectral reflectance in knotting stage

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Fig. 3 Water content models established on W_I in different summer maize growth stages

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Fig. 4 Water content models established on M_SI in different summer maize growth stages

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Fig. 5 Water content models established on G_VMI in different summer maize growth stages

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Fig. 6 Water content models established on W_NV in different summer maize growth stages

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Fig. 7 Water content models established on W_CG in different summer maize growth stages

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Fig. 8 Water content models established on D_area in different summer maize growth stages

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Table 1 Irrigation treatments of summer maize growth in 2014

处理	占7月降水量的百分比/%	灌水量/mm
A	20	30
B	40	60
C	60	90
D	80	120
E	100	150

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Table 2 Irrigation treatments of summer maize growth in 2015

处理	土壤相对湿度
A1	全生育期55%±5%
B1	全生育期35%±5%
C1	拔节前保持75%±5%, 拔节后加灌16 mm
D1	拔节前保持75%±5%, 拔节后不再灌水
E1	全生育期75%±5%

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Table 3 The model precision of canopy and leaf level water content of summer maize using different spectral indices (R²)

光谱指数	尺度	三叶期	七叶期	拔节期	抽雄期	灌浆期	成熟期
W_I	冠层	0.02	0.50^*	0.80^*	0.95^*	0.71^*	0.72^*
W_I	叶片		0.67^*	0.59^*	0.02	0.06	0.06
M_SI	冠层	0.10	0.56^*	0.82^*	0.91^*	0.80^*	0.64^*
M_SI	叶片	0.08	0.58^*	0.59^*	0.02	0.06	0.04
G_VMI	冠层	0.31	0.51^*	0.83^*	0.91^*	0.77^*	0.67^*
G_VMI	叶片	0.32	0.58^*	0.58^*	0.03	0.05	0.02
W_NV	冠层	0.36	0.67^*	0.91^*	0.89^*	0.87^*	0.75^*
W_NV	叶片	0.54^*	0.58^*	0.53^*	0.009	0.05	0.01
W_CG	冠层	0.28	0.61^*	0.92^*	0.88^*	0.82^*	0.71^*
W_CG	叶片	0.45	0.59^*	0.55^*	0.001	0.05	0.06
D_area	冠层	0.35	0.59^*	0.87^*	0.91^*	0.78^*	0.72^*
D_area	叶片	0.41	0.61^*	0.59^*	0.02	0.06	0.07
注:*表示达到0.01显著性水平。

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Table 4 Model verification in summer maize growth stages

生育期	光谱指数	模拟值(x)与观测值(y)拟合方程	R²	均方根误差
拔节期	W_I	y=1.12x-0.0018	0.65^*	0.0054
	M_SI	y=1.37x-0.0021	0.66^*	0.0059
	G_VMI	y=1.30x-0.0015	0.66^*	0.0058
	W_NV	y=1.06x+0.002	0.65^*	0.0062
	W_CG	y=1.15x+0.0024	0.63^*	0.0067
	D_area	y=1.2388x-0.002	0.64^*	0.0056
抽雄期	W_I	y=0.73x+0.0016	0.63^*	0.0057
	M_SI	y=1.01x-0.0016	0.72^*	0.0041
	G_VMI	y=0.87x+0.003	0.67^*	0.0045
	W_NV	y=0.78x+0.0005	0.67^*	0.0041
	W_CG	y=1.09x-0.0033	0.72^*	0.0042
	D_area	y=0.858x-0.0012	0.69^*	0.0057
灌浆期	W_I	y=0.74x-0.0025	0.69^*	0.0084
	M_SI	y=1.19x-0.0064	0.74^*	0.0058
	G_VMI	y=1.46x-0.0079	0.72^*	0.0056
	W_NV	y=0.93x+0.0010	0.71^*	0.0054
	W_CG	y=0.92x+0.0013	0.74^*	0.0050
	D_area	y=1.11x+0.0014	0.68^*	0.0050
成熟期	W_I	y=1.25x-0.0014	0.54^*	0.0051
	M_SI	y=1.60x-0.0032	0.55^*	0.0059
	G_VMI	y=1.57x-0.0071	0.55^*	0.0060
	W_NV	y=1.28x+0.0011	0.56^*	0.0059
	W_CG	y=1.16x+0.0013	0.55^*	0.0056
	D_area	y=1.02x+0.0053	0.55^*	0.0072
注:*表示达到0.01显著性水平。

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