Remote Estimation of Biomass in Winter Oilseed Rape (Brassica napus L.) Using Canopy Hyperspectral Data at Different Growth Stages
<p>Experimental design: (<b>a</b>) Experiment location map; (<b>b</b>) Experiment one; and, (<b>c</b>) Experiment two.</p> "> Figure 2
<p>Canopy spectral reflectance and field pictures at four different stages. (<b>a</b>) Canopy spectral reflectance at seeding, bolting, flowering and pod stages; (<b>b</b>) Field picture at seeding stage; (<b>c</b>) Field picture at bolting stage; (<b>d</b>) Field picture at flowering stage; (<b>e</b>) Field picture at pod stage.</p> "> Figure 3
<p>Correlation coefficient results of AGB and canopy spectral reflectance at four different stages: (<b>a</b>) Seeding stage; (<b>b</b>) Bolting stage; (<b>c</b>) Flowering stage; and, (<b>d</b>) Pod stage.</p> "> Figure 4
<p>Relationship between CIred edge and AGB at four different stages: (<b>a</b>) seeding stage; (<b>b</b>) bolting stage; (<b>c</b>) flowering stage; and, (<b>d</b>) pod stage.</p> "> Figure 5
<p>The coefficient of determination (R<sup>2</sup>) between AGB and NDVI-like indices at four different stages: (<b>a</b>) seeding stage; (<b>b</b>) bolting stage; (<b>c</b>) flowering stage; and, (<b>d</b>) pod stage.</p> "> Figure 6
<p>The partial least squares regression variable importance in projection (PLSR VIP) of each wavelength with the combination of four different grown stages data</p> "> Figure 7
<p>Regression modeling analysis between NDVI (800, 1200), CIred edge, and AGB at different stages: (<b>a</b>) model 33; (<b>b</b>) model 34; (<b>c</b>) model 35; (<b>d</b>) model 36; (<b>e</b>) model 37; and, (<b>f</b>) model 38.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experiment Design
2.2. Experiment Data
2.2.1. Canopy Hyperspectral Data Acquisition
2.2.2. Dry Aboveground Biomass (AGB) Data
2.2.3. Calibration and Validation Dataset
2.3. Research Methods
2.3.1. Vegetation Indices (VIs)
2.3.2. The Process of Modeling and Assessment
3. Results
3.1. Statistical Values of AGB
3.2. Representative Spectral Reflectance
3.3. Correlation Analysis for Hyperspectral Waveband and AGB
3.4. Relationship Between the Seven VIs and AGB at Four Different Stages
3.5. The Coefficient of Determination (R2) Between AGB and Narrow Band Indices
3.6. Extract the Feature Wavelengths by PLSR
3.7. Relationship Between NDVI (800, 1200) and AGB
3.8. Regression Modeling Analysis for AGB of Different Growth Stages Combination
4. Discussion
4.1. Estimating WOR AGB Using the Seven Commonly Used VIs
4.2. Estimating WOR AGB Using the Modified Vegetation indices NDVI (800, 1200)
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Year and Site | Plots | Fertilizer-N level (kg/hm2) | The Major Chemical Properties of Soil Layer (0–20 cm) |
---|---|---|---|
2014–2015 Wuxue city | The 24 individual plot area: 20 m2 (10.0 m × 2.0 m) | 8 fertilizer-N levels: 0, 45, 90, 135, 180, 225, 270, 360 | pH:5.40 Organic matter: 30.08 g/kg Total N: 1.72 g/kg Olsen-P: 13.80 mg/kg NH4OAc-K: 92.10 mg/kg |
2015–2016 Shayang city | The 27 individual plot area: 30 m2 (15.0 m × 2.0 m) | 9 fertilizer-N levels: 0, 45, 90, 135, 180, 225, 270, 315, 360 | pH:5.88 Organic matter: 18.02 g/kg Total N: 0.96 g/kg Olsen-P: 11.79 mg/kg NH4OAc-K: 85.97 mg/kg |
Growth Stages | Number of Calibration Dataset | Number of Validation Dataset | Study Site | Sampling Dates (month/day/year) | Number of Samples |
---|---|---|---|---|---|
Seeding stage (n = 156) | n = 104 | n = 52 | Wuxue city | 12/8/2014 | 24 |
Wuxue city | 1/15/2015 | 24 | |||
Shayang city | 11/26/2015 | 27 | |||
Shayang city | 12/14/2015 | 27 | |||
Shayang city | 1/7/2016 | 27 | |||
Shayang city | 1/24/2016 | 27 | |||
Bolting stage (n = 27) | n = 18 | n = 9 | Shayang city | 2/18/2016 | 27 |
Flowering stage (n = 51) | n = 34 | n = 17 | Wuxue city | 3/12/2015 | 24 |
Shayang city | 3/18/2016 | 27 | |||
Pod stage (n = 51) | n = 34 | n = 17 | Wuxue city | 4/14/2015 | 24 |
Shayang city | 4/18/2016 | 27 |
Vegetation Indices | Formulas | References |
---|---|---|
Red edge chlorophyll index (CIred edge) | (R800/R725) − 1 | [30] |
Green chlorophyll index (CIgreen) | (R800/R550) − 1 | [41] |
Normalized Difference Vegetation Index (NDVI) | (R800 − R670)/(R800 + R670) | [42] |
Green normalized difference vegetation index (GNDVI) | (R780 − R550)/(R780 + R550) | [43] |
Ratio vegetation index (RVI) | R750/R550 | [44] |
Difference Vegetation Index (DVI) | R800 − R670 | [45] |
Soil-Adjusted Vegetation Index (SAVI) | (1 + L)(R890 − R670)/(R890 + R670 + L), L = 0.5 | [46] |
Growth Stages | Minimum (kg/hm2) | Maximum (kg/hm2) | Mean (kg/hm2) | Standard Deviation | Variance | Coef. of Variation |
---|---|---|---|---|---|---|
Seeding stage (n = 156) | 179.00 | 3982.00 | 1444.00 | 1026.08 | 1052847.38 | 71.05 |
Bolting stage (n = 27) | 527.00 | 5428.00 | 3052.85 | 1798.74 | 3235464.82 | 58.92 |
Flowering stage (n = 51) | 674.00 | 10286.00 | 4589.64 | 2743.17 | 7524995.81 | 59.77 |
Pod stage (n = 51) | 1445.63 | 17402.00 | 8700.45 | 4480.54 | 20075254.99 | 51.50 |
Growth Period | Model Number | Vegetation Index | Model | Rcal2 | RMSEC | Rval2 | RMSEV | RPD |
---|---|---|---|---|---|---|---|---|
Seeding stage | 1 | CIred edge | Y = 102.97e5.47X | 0.75 | 516.02 | 0.60 | 667.45 | 1.49 |
2 | CIgreen | Y = 23.79X1.75 | 0.46 | 765.90 | 0.43 | 754.32 | 1.32 | |
3 | NDVI | Y = 0.15e10.86X | 0.44 | 782.97 | 0.35 | 808.95 | 1.23 | |
4 | GNDVI | Y = 66244.38X2 − 71070.06X + 19149.09 | 0.70 | 567.58 | 0.62 | 634.92 | 1.57 | |
5 | RVI | Y = 140.90X2 − 532.25X + 468.94 | 0.66 | 603.71 | 0.60 | 645.25 | 1.54 | |
6 | DVI | Y = 1030.32X2 + 3315.29X − 430.26 | 0.38 | 820.85 | 0.48 | 719.00 | 1.38 | |
7 | SAVI | Y = 9193.38X2 − 6090.45X + 1306.71 | 0.42 | 794.13 | 0.51 | 698.61 | 1.42 | |
Bolting stage | 8 | CIred edge | Y = 9197.71X2.35 | 0.90 | 548.12 | 0.95 | 563.53 | 3.36 |
9 | CIgreen | Y = 28.60X2 − 144.13X + 510.72 | 0.60 | 1116.29 | 0.68 | 1200.59 | 1.58 | |
10 | NDVI | Y = 0.01e14.69X | 0.74 | 909.41 | 0.83 | 931.60 | 2.03 | |
11 | GNDVI | Y = 0.002e19.10X | 0.76 | 860.64 | 0.85 | 917.05 | 2.06 | |
12 | RVI | Y = 414.29X2 − 3126.00X + 6200.30 | 0.75 | 880.71 | 0.84 | 935.99 | 2.02 | |
13 | DVI | Y = −544.29X2 + 10100.64X − 1593.67 | 0.65 | 1045.51 | 0.64 | 1116.31 | 1.70 | |
14 | SAVI | Y = 19512.53X2 − 12498.74X + 2389.74 | 0.68 | 1000.69 | 0.71 | 1039.45 | 1.82 | |
Flowering stage | 15 | CIred edge | Y = 15030.54X2 + 4155.57X + 617.51 | 0.51 | 1930.70 | 0.73 | 1383.12 | 1.94 |
16 | CIgreen | Y = −40.19X2 + 1635.22X − 5133.96 | 0.46 | 2035.52 | 0.69 | 1506.24 | 1.78 | |
17 | NDVI | Y = 38617.39X2 − 32985.07X + 10536.23 | 0.07 | 2670.14 | 0.22 | 2313.93 | 1.16 | |
18 | GNDVI | Y = 80802.89X2 − 62164.29X + 15637.80 | 0.09 | 2647.08 | 0.21 | 2331.43 | 1.15 | |
19 | RVI | Y = 665.18X2 − 2035.16X + 5086.06 | 0.06 | 2689.12 | 0.20 | 2359.91 | 1.14 | |
20 | DVI | Y = −32022.02X2 + 49340.35X − 8223.08 | 0.61 | 1725.98 | 0.65 | 1562.56 | 1.72 | |
21 | SAVI | Y =-82431.02X2 + 104058.89X − 25617.79 | 0.44 | 2080.93 | 0.54 | 1794.47 | 1.50 | |
Pod stage | 22 | CIred edge | Y = 19903.34X2 + 12952.22X + 30.53 | 0.60 | 2885.85 | 0.57 | 2789.80 | 1.55 |
23 | CIgreen | Y = 369.40X2 − 3109.09X + 9343.05 | 0.63 | 2757.06 | 0.46 | 3128.60 | 1.39 | |
24 | NDVI | Y = 0.15e13.40X | 0.67 | 2627.16 | 0.52 | 2969.42 | 1.46 | |
25 | GNDVI | Y = 300474.05X2 − 255779.54X + 54925.75 | 0.68 | 2577.58 | 0.61 | 2768.50 | 1.57 | |
26 | RVI | Y = 9229.40X − 25666.00 | 0.68 | 2570.50 | 0.61 | 2826.18 | 1.53 | |
27 | DVI | Y = −263029.22X2 + 210863.21X − 31888.76 | 0.25 | 3927.09 | 0.20 | 3959.06 | 1.10 | |
28 | SAVI | Y = −229623.73X2 + 281044.12X − 76153.15 | 0.22 | 4003.84 | 0.37 | 3498.71 | 1.24 |
Growth Period | Model Number | Vegetation Index | Model | Rcal2 | RMSEC | Rval2 | RMSEV | RPD |
---|---|---|---|---|---|---|---|---|
Seeding stage | 29 | NDVI (800, 1200) | Y = 136.47e19.92X | 0.64 | 622.82 | 0.61 | 650.03 | 1.45 |
Bolting stage | 30 | NDVI (800, 1200) | Y = 293314.87X2 − 38660.43X + 1223.73 | 0.70 | 964.67 | 0.80 | 963.94 | 1.96 |
Flowering stage | 31 | NDVI (800, 1200) | Y = 83018.78X2 + 3179.73X + 867.19 | 0.67 | 1588.22 | 0.74 | 1351.36 | 1.99 |
Pod stage | 32 | NDVI (800, 1200) | Y = 464172.09X2 − 115386.42X + 8971.06 | 0.77 | 2200.45 | 0.62 | 2944.28 | 1.47 |
Growth Period | Model Number | Vegetation Index | Model | Rcal2 | RMSEC | Rval2 | RMSEV | RPD |
---|---|---|---|---|---|---|---|---|
Vegetative stage | 33 | NDVI (800, 1200) | Y = 165728.69X2 − 10401.76X + 391.91 | 0.71 | 702.88 | 0.52 | 889.44 | 1.45 |
34 | CIred edge | Y = 15403.76X2 −6617.28X + 1101.59 | 0.84 | 525.35 | 0.75 | 643.48 | 2.01 | |
Reproductive stage | 35 | NDVI (800, 1200) | Y = 467.84e11.51X | 0.73 | 2226.83 | 0.72 | 2231.90 | 1.85 |
36 | CIred edge | Y = 20042.96X2 + 7467.16X + 377.43 | 0.46 | 3159.01 | 0.48 | 2938.05 | 1.41 | |
Total for four stages | 37 | NDVI (800, 1200) | Y = 197455.98X2 −17815.49X + 779.08 | 0.83 | 1521.84 | 0.82 | 1501.34 | 2.37 |
38 | CIrededge | Y = −5472.86X2 + 12188.17X − 717.08 | 0.08 | 3507.79 | 0.06 | 3447.41 | 1.03 |
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Ma, Y.; Fang, S.; Peng, Y.; Gong, Y.; Wang, D. Remote Estimation of Biomass in Winter Oilseed Rape (Brassica napus L.) Using Canopy Hyperspectral Data at Different Growth Stages. Appl. Sci. 2019, 9, 545. https://doi.org/10.3390/app9030545
Ma Y, Fang S, Peng Y, Gong Y, Wang D. Remote Estimation of Biomass in Winter Oilseed Rape (Brassica napus L.) Using Canopy Hyperspectral Data at Different Growth Stages. Applied Sciences. 2019; 9(3):545. https://doi.org/10.3390/app9030545
Chicago/Turabian StyleMa, Yi, Shenghui Fang, Yi Peng, Yan Gong, and Dong Wang. 2019. "Remote Estimation of Biomass in Winter Oilseed Rape (Brassica napus L.) Using Canopy Hyperspectral Data at Different Growth Stages" Applied Sciences 9, no. 3: 545. https://doi.org/10.3390/app9030545