Using Digital Cameras on an Unmanned Aerial Vehicle to Derive Optimum Color Vegetation Indices for Leaf Nitrogen Concentration Monitoring in Winter Wheat
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Site and Experimental Design
2.2. Data Acquisition and Processing
2.2.1. Color Images from Unmanned Aerial Vehicle (UAV)
2.2.2. Determination of Leaf N Concentration (LNC)
2.2.3. Derivation of Vegetation Indices (VIs)
2.3. Data Analysis and Evaluation
3. Results
3.1. Changes of Digital Number (DN) Values in Different Channels
3.2. Leaf N Concentration (LNC) Estimation Model Constraction and Validation
3.2.1. Quantitative Relationships between Leaf N Concentration (LNC) and Vegetation Indices (VIs) at Different Growth Stages
3.2.2. Validation of the Leaf N Concentration (LNC) Models for Wheat
3.3. Saturation Sensitivity of Vegetation Indices (VIs) at Different Leaf N Concentrations (LNCs)
3.4. Applicability of the Leaf N Concentration (LNC) Models under Different Treatments
4. Discussion
4.1. Performance of the Vegetation Indices (VIs) Derived from Digital Imagery in Estimating Wheat Leaf N Concentration (LNC)
4.2. Accuracy and Universality of Leaf N Concentration (LNC) Estimation Models in Wheat
4.3. Capability of Commercial Digital Cameras for Wheat Leaf N Concentration (LNC) Estimation
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Experiment | Year | Wheat Varieties | N Application Rates (kg/ha) | Plot Area (m2) | Planting Density (plants/ha) | Sampling Dates |
---|---|---|---|---|---|---|
Exp.1 | 2013–2014 | V1: Yangmai 8 V2: Shengxuan 6 | N0: 0 N1: 150 N2: 300 | 7 × 5 | D1: 3.0 × 106 D2: 1.5 × 106 | 9/15/23 April 6 May |
Exp.2 | 2014–2015 | V1: Yangmai 8 V2: Shengxuan 6 | N0: 0 N1: 150 N2: 300 | 7 × 5 | D1: 2.4 × 106 D2: 1.5 × 106 | 8/17/25 April 6 May |
Parameter | Value |
---|---|
Weight (without batteries) | 2050 g |
Size | 73 (width) × 73 (length) × 36 (height) cm |
Battery Wight (4s/5000) | 520 g |
Maximum payload | 2500 g |
Flight duration | 8~41 min |
Temperature range | −5 °C ~ 35 °C |
Parameter | Value | |
---|---|---|
RGB Camera | CIR Camera | |
Blue Channel | Visible blue light | Visible blue light |
Green Channel | Visible green light | Visible green light |
Red Channel | Visible red light | |
NIR Channel | 670–770 nm | |
Geometric Resolution | 5760 × 3840 pixel | 4000 × 3000 pixel |
Focal Length | 24 mm | 4 mm |
Date | Growth Stage | RGB Imagery | CIR Imagery | |
---|---|---|---|---|
Exp. 1 (2014) | 9 April | Booting | ✘ | ✔ |
15 April | Heading | ✘ | ✔ | |
23 April | Anthesis | ✘ | ✔ | |
6 May | Filling | ✘ | ✔ | |
Exp. 2 (2015) | 8 April | Booting | ✔ | ✔ |
17 April | Heading | ✔ | ✔ | |
25 April | Anthesis | ✔ | ✔ | |
6 May | Filling | ✔ | ✔ |
Camera | VI | Name | Formula |
---|---|---|---|
RGB | NGRDI | Normalized green red difference index | (G−R)/(G+R) |
IKaw | Kawashima index | (R−B)/(R+B) | |
RGRI | Red green ratio index | R/G | |
VARI | Visible atmospherically resistance index | (G−R)/(G+R−B) | |
ExG | Excess green vegetation index | (2G−R−B)/(G+R+B) | |
TCVI 1 | True Color Vegetation Index | 1.4*(2R−2B)/(2R−G−2B+255*0.4) | |
CIR | GNDVI | Green normalized difference vegetation index | (NIR−G)/(NIR+G) |
ENDVI | Enhanced normalized difference vegetation index | (NIR+G−2B)/(NIR+G+2B) | |
FCVI 2 | False Color Vegetation Index | 1.5*(2NIR+B−2G)/(2G+2B−2NIR+255*0.5) |
Growth Stage | RGB Camera | CIR Camera | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
Normalized Green-Red Difference Index (NGRDI) | IKaw | Red Green Ratio Index (RGRI) | VARI | Excess Green Vegetation Index (ExG) | True Color Vegetation Index (TCVI) | Green Normalized Difference Vegetation Index (GNDVI) | Enhanced Normalized Difference Vegetation Index (ENDVI) | False Color Vegetation Index (FCVI) | ||
Booting | Function | y = 1.19e8x | y = 4.42e−4.68x | y = 141e−4.84x | y = 1.28e4.57x | y = 1.81e2.58x | y = 4.73e−0.89x | y = 0.99e4.3x | y = 1.36e5.6x | y = 1.5e1.56x |
R2 | 0.752 | 0.880 | 0.743 | 0.818 | 0.032 | 0.854 | 0.853 | 0.664 | 0.866 | |
RRMSE | 11.7 | 8.3 | 11.9 | 10.1 | 22.5 | 9.1 | 9.1 | 13.8 | 9.5 | |
Heading | Function | y = 1.31e6.56x | y = 5.6e−4.79x | y = 64.7e−3.95x | y = 1.35e4.18x | y = 0.79e5.01x | y = 5.62e−1.21x | y = 0.52e6.25x | y = 0.87e6.42x | y = 1.15e1.81x |
R2 | 0.792 | 0.918 | 0.782 | 0.841 | 0.284 | 0.911 | 0.706 | 0.313 | 0.822 | |
RRMSE | 12.9 | 8.6 | 13.1 | 11.2 | 23.8 | 8.9 | 14.1 | 22.9 | 11.5 | |
Anthesis | Function | y = 1.21e9.26x | y = 6.19e−5.95x | y = 237e−5.31x | y = 1.25e5.73x | y = 0.4e9.17x | y = 5.11e−1.04x | y = 0.71e4.63x | y = 0.95e7.67x | y = 1.1e1.79x |
R2 | 0.875 | 0.825 | 0.868 | 0.892 | 0.458 | 0.855 | 0.889 | 0.811 | 0.911 | |
RRMSE | 10.6 | 11.8 | 10.8 | 10.0 | 21.8 | 11.5 | 9.7 | 12.9 | 9.0 | |
Filling | Function | y = 1.79e8.34x | y = 9.21e−6.11x | y = 143e−4.37x | y = 1.78e5.71x | y = 0.66e6.98x | y = 5.56e−1.08x | y = 0.65e5.34x | y = 1.13e7.02x | y = 0.87e2.45x |
R2 | 0.771 | 0.746 | 0.769 | 0.779 | 0.426 | 0.813 | 0.821 | 0.648 | 0.849 | |
RRMSE | 18.5 | 18.6 | 18.4 | 18.1 | 27.5 | 16.3 | 15.2 | 20.0 | 15.1 | |
All | Function | y = 1.74e5.21x | y = 4.61e−3.52x | y = 34.4e−3x | y = 1.76e3.27x | y = 1.1e4.27x | y = 5.09e−1.02x | y = 0.77e4.77x | y = 1.34e5.08x | y = 1.15e1.85x |
R2 | 0.631 | 0.659 | 0.634 | 0.651 | 0.252 | 0.852 | 0.744 | 0.507 | 0.792 | |
RRMSE | 18.7 | 17.7 | 18.6 | 18.1 | 26.4 | 12.1 | 15.8 | 21.7 | 14.0 |
Camera | VI | Cross-Validation | Independent Validation | ||
---|---|---|---|---|---|
R2 | RRMSE (%) | R2 | RRMSE (%) | ||
RGB | Normalized Green Red Difference Vegetation Index (NGRDI) | 0.591 | 18.24 | ||
IKaw | 0.618 | 17.79 | |||
Red green ratio index (RGRI) | 0.608 | 18.66 | |||
VARI | 0.603 | 18.37 | |||
Excess green vegetation index (ExG) | 0.150 | 27.23 | |||
True color vegetation index (TCVI) | 0.848 | 11.47 | |||
CIR | Green normalized difference vegetation index (GNDVI) | 0.720 | 16.13 | 0.523 | 23.66 |
Enhanced normalized difference vegetation index (ENDVI) | 0.492 | 20.62 | 0.207 | 37.99 | |
False color vegetation index (FCVI) | 0.756 | 14.18 | 0.627 | 13.61 |
Treatment | RGB Imagery | CIR Imagery | |
---|---|---|---|
Variety | Yangmai 8 | 13.95 | 14.69 |
Shengxuan 6 | 9.88 | 13.34 | |
N rates (kg/ha) | 0 | 13.01 | 16.41 |
150 | 11.23 | 12.61 | |
300 | 11.64 | 13.35 | |
Planting Density (plants/ha) | 3.0 × 106 | 9.01 | 14.17 |
1.5 × 106 | 14.49 | 13.87 |
VI | Coefficients for Different Channels | Channels | L | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
a1 | a2 | a3 | a4 | a5 | a6 | R | G | B | |||
Normal color (RGB) | Normalized green red difference vegetation index (NGRDI) | −1 | 1 | 0 | 1 | 1 | 0 | DNred | DNgreen | 0 | |
IKaw | 1 | 0 | −1 | 1 | 0 | 1 | DNred | DNblue | 0 | ||
Red green ratio index (RGRI) | 1 | 0 | 0 | 0 | 1 | 0 | DNred | DNgreen | 0 | ||
VARI | −1 | 1 | 0 | 1 | 1 | −1 | DNred | DNgreen | DNblue | 0 | |
Excess green vegetation index (ExG) | −1 | 2 | −1 | 1 | 1 | 1 | DNred | DNgreen | DNblue | 0 | |
True color vegetation index (TCVI) | 2 | 0 | −2 | 2 | −1 | −2 | DNred | DNgreen | DNblue | 0.4 | |
Color near-infrared (CIR) | Green normalized difference vegetation index (GNDVI) | 1 | −1 | 0 | 1 | 1 | 0 | DNnir | DNgreen | 0 | |
Enhanced normalized difference vegetation index (ENDVI) | 1 | 1 | −2 | 1 | 1 | 2 | DNnir | DNgreen | DNblue | 0 | |
False color vegetation index (FCVI) | 1 | −2 | 1 | −2 | 2 | 2 | DNnir | DNgreen | DNblue | 0.5 |
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Jiang, J.; Cai, W.; Zheng, H.; Cheng, T.; Tian, Y.; Zhu, Y.; Ehsani, R.; Hu, Y.; Niu, Q.; Gui, L.; et al. Using Digital Cameras on an Unmanned Aerial Vehicle to Derive Optimum Color Vegetation Indices for Leaf Nitrogen Concentration Monitoring in Winter Wheat. Remote Sens. 2019, 11, 2667. https://doi.org/10.3390/rs11222667
Jiang J, Cai W, Zheng H, Cheng T, Tian Y, Zhu Y, Ehsani R, Hu Y, Niu Q, Gui L, et al. Using Digital Cameras on an Unmanned Aerial Vehicle to Derive Optimum Color Vegetation Indices for Leaf Nitrogen Concentration Monitoring in Winter Wheat. Remote Sensing. 2019; 11(22):2667. https://doi.org/10.3390/rs11222667
Chicago/Turabian StyleJiang, Jiale, Weidi Cai, Hengbiao Zheng, Tao Cheng, Yongchao Tian, Yan Zhu, Reza Ehsani, Yongqiang Hu, Qingsong Niu, Lijuan Gui, and et al. 2019. "Using Digital Cameras on an Unmanned Aerial Vehicle to Derive Optimum Color Vegetation Indices for Leaf Nitrogen Concentration Monitoring in Winter Wheat" Remote Sensing 11, no. 22: 2667. https://doi.org/10.3390/rs11222667