Comparison of Spaceborne and UAV-Borne Remote Sensing Spectral Data for Estimating Monsoon Crop Vegetation Parameters
Abstract
:1. Introduction
- To build crop-specific parametric and non-parametric models to estimate crop vegetation parameters
- To evaluate the developed vegetation parameter estimation models against (a) the spectral sensitivity of the RS data (multispectral vs hyperspectral), (b) modelling method (parametric and non-parametric), and (c) crop type (finger millet, maize, and lablab)
- To explore how crop-wise vegetation parameter estimation is affected by agricultural treatment (irrigation and fertiliser)
2. Materials and Methods
2.1. Study Site and Experimental Design
2.2. In-Situ Field Data
2.3. Remote Sensing Data
2.3.1. WorldView 3 Data
2.3.2. Cubert Hyperspectral Data
2.4. Model-Building Workflow for Crop Vegetation Parameter Estimation
3. Results
3.1. Crop Vegetation Parameter Data
3.2. Spectral and Vegetation Index Data
3.3. Crop Vegetation Parameter Estimation with Linear Regression
3.4. Crop Vegetation Parameter Estimation with Random Forest Regression
3.4.1. Key Wavebands
3.4.2. Model Performance
3.5. Best Models and Distribution of Residuals
4. Discussion
4.1. Finger Millet Vegetation Parameter Estimation
4.2. Lablab Vegetation Parameter Estimation
4.3. Maize Crop Vegetation Parameter Estimation
4.4. Overall Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Crop | Water | Min | Mean | SD | Max | CV |
---|---|---|---|---|---|---|
LAI (m2/m2) | ||||||
Finger millet | Irrigated | 1.4 | 2.6 | 0.5 | 3.2 | 19.2% |
Rainfed | 0.4 | 1.0 | 0.4 | 1.6 | 40.0% | |
Lablab | Irrigated | 1.7 | 2.5 | 0.6 | 3.5 | 24.0% |
Rainfed | 0.2 | 0.5 | 0.2 | 0.7 | 40.0% | |
Maize | Irrigated | 2.1 | 2.7 | 0.2 | 3.0 | 7.4% |
Rainfed | 1.0 | 1.6 | 0.4 | 2.2 | 25.0% | |
LCC (µg/cm2) | ||||||
Finger millet | Irrigated | 19.3 | 39.7 | 13.6 | 65.6 | 34.3% |
Rainfed | 10.2 | 12.8 | 3.4 | 21.4 | 26.6% | |
Lablab | Irrigated | 17.5 | 36.3 | 7.8 | 43.0 | 21.5% |
Rainfed | 20.1 | 27.5 | 4.3 | 33.3 | 15.6% | |
Maize | Irrigated | 15.7 | 42.1 | 19.6 | 76.4 | 46.6% |
Rainfed | 11.9 | 20.3 | 5.3 | 30.6 | 26.1% | |
CWC (kg/m2) | ||||||
Finger millet | Irrigated | 0.4 | 1.4 | 0.7 | 2.7 | 46.5% |
Rainfed | 0.1 | 0.5 | 0.2 | 1.0 | 52.1% | |
Lablab | Irrigated | 0.4 | 0.7 | 0.3 | 1.6 | 48.5% |
Rainfed | 0.03 | 0.08 | 0.04 | 0.1 | 50.0% | |
Maize | Irrigated | 0.8 | 1.5 | 0.4 | 2.3 | 26.6% |
Rainfed | 0.2 | 0.9 | 0.4 | 1.5 | 45.5% |
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Crop | Phenological Stage (Days after Sowing) | |
---|---|---|
Irrigated Experiment | Rainfed Experiment | |
Finger millet | Inflorescence emergence (87) | Inflorescence emergence (79) |
Lablab | Ripening (83) | Development of fruit (78) |
Maize | Development of fruit (87) | Development of fruit (79) |
Band Name | Centre Wavelength (nm) | Effective Bandwidth (nm) |
---|---|---|
Coastal blue (CB) | 427.4 | 40.5 |
Blue (BL) | 481.9 | 54.0 |
Green (GR) | 547.1 | 61.8 |
Yellow (YE) | 604.3 | 38.1 |
Red (RD) | 660.1 | 58.5 |
Red-edge (RE) | 722.7 | 38.7 |
Near-infrared 1 (N1) | 824.0 | 100.4 |
Near-infrared 2 (N2) | 913.6 | 88.9 |
VI | Formula for WV3 Bands | Formula for CUB Bands | Reference |
---|---|---|---|
NDVI800,670 | [37] | ||
NDVI750,550 | [38] | ||
DATT4 | [36] | ||
MTVI | [39] | ||
REIP | [40] | ||
WI | [23] |
Parameter | Crop | RS Data | LR Model with VIs | |||
---|---|---|---|---|---|---|
Best Vegetation Index | r | R2cv | nRMSEcv (%) | |||
LAI (m2/m2) | Finger millet | CUB | NDVI800_670 | 0.88 | 0.74 | 15.7 |
WV3 | REIP | 0.88 | 0.74 | 16.1 | ||
Lablab | CUB | NDVI800_670 | 0.90 | 0.77 | 15.6 | |
WV3 | REIP | 0.90 | 0.77 | 15.9 | ||
Maize | CUB | NDVI800_670 | 0.90 | 0.77 | 14.9 | |
WV3 | NDVI800_670 | 0.89 | 0.73 | 16.0 | ||
LCC (µg/cm2) | Finger millet | CUB | DATT4 | 0.83 | 0.63 | 18.0 |
WV3 | NDVI750_550 | 0.76 | 0.50 | 21.0 | ||
Lablab | CUB | NDVI750_550 | 0.67 | 0.37 | 23.3 | |
WV3 | NDVI750_550 | 0.66 | 0.36 | 23.4 | ||
Maize | CUB | NDVI800_670 | 0.59 | 0.21 | 24.1 | |
WV3 | DATT4 | 0.61 | 0.26 | 23.3 | ||
CWC (kg/m2) | Finger millet | CUB | NDVI750_550 | 0.73 | 0.44 | 19.5 |
WV3 | NDVI750_550 | 0.73 | 0.43 | 19.9 | ||
Lablab | CUB | NDVI800_670 | 0.77 | 0.53 | 16.3 | |
WV3 | REIP | 0.81 | 0.58 | 15.6 | ||
Maize | CUB | NDVI800_670 | 0.68 | 0.36 | 19.9 | |
WV3 | DATT4 | 0.76 | 0.51 | 17.0 |
Parameter | Crop | Selected Wavebands from Cubert Data | Selected Wavebands from WorldView3 Data |
---|---|---|---|
LAI (m2/m2) | Finger Millet | ρ522, ρ526, ρ582, ρ642, ρ694, ρ702, ρ706, ρ722, ρ730, ρ738, ρ750, ρ762, ρ946 | Blue, Green, Yellow, Red, Red-edge, Near-infrared 2 |
Lablab | ρ690, ρ698, ρ706, ρ722, ρ726, ρ734, ρ750, ρ826, ρ918, ρ930, ρ946, ρ950, ρ954, ρ958 | Blue, Green, Yellow, Red, Red edge | |
Maize | ρ474, ρ478, ρ674, ρ682, ρ690, ρ694, ρ794, ρ802, ρ806, ρ822, ρ870, ρ874, ρ890, ρ898, ρ906, ρ930, ρ954 | Blue, Green, Yellow, Red, Red edge, Near-infrared 2 | |
LCC (µg/cm2) | Finger Millet | ρ746, ρ750, ρ754, ρ758, ρ762, ρ766 | Blue, Green, Yellow, Red, Red edge, Near-infrared 1, Near-infrared 2 |
Lablab | ρ574, ρ638, ρ718, ρ742, ρ750 | Blue, Green, Yellow, Red, Red edge | |
Maize | ρ682, ρ690, ρ698, ρ702 | Blue, Green, Yellow, Red, Red edge | |
CWC (kg/m2) | Finger Millet | ρ470, ρ478, ρ522, ρ526, ρ694, ρ706, ρ710, ρ722, ρ742, ρ746 | Blue, Green, Yellow, Red, Red edge, Near-infrared 2 |
Lablab | ρ502, ρ606, ρ614, ρ618, ρ630, ρ666, ρ678, ρ682, ρ742, ρ802, ρ834 | Blue, Green, Yellow, Red, Red edge | |
Maize | ρ866, ρ878, ρ886, ρ918, ρ966, ρ970 | Blue, Green, Yellow, Red, Red edge |
Parameter | Crop | RS Data | RFR Model with Selected Wavebands | ||
---|---|---|---|---|---|
No. of Wavebands | R2cv | nRMSEcv (%) | |||
LAI (m2/m2) | Finger millet | CUB | 13 | 0.74 | 16.1 |
WV3 | 6 | 0.70 | 17.1 | ||
Lablab | CUB | 14 | 0.84 | 12.9 | |
WV3 | 5 | 0.87 | 12.0 | ||
Maize | CUB | 18 | 0.79 | 13.9 | |
WV3 | 6 | 0.80 | 13.9 | ||
LCC (µg/cm2) | Finger millet | CUB | 6 | 0.45 | 22.1 |
WV3 | 7 | 0.51 | 20.8 | ||
Lablab | CUB | 5 | 0.23 | 25.8 | |
WV3 | 5 | 0.13 | 27.4 | ||
Maize | CUB | 4 | 0.16 | 24.9 | |
WV3 | 5 | 0.01 | 31.5 | ||
CWC (kg/m2) | Finger millet | CUB | 10 | 0.43 | 19.9 |
WV3 | 6 | 0.23 | 22.9 | ||
Lablab | CUB | 11 | 0.51 | 16.9 | |
WV3 | 5 | 0.42 | 18.2 | ||
Maize | CUB | 4 | 0.24 | 21.4 | |
WV3 | 5 | 0.26 | 21.4 |
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Wijesingha, J.; Dayananda, S.; Wachendorf, M.; Astor, T. Comparison of Spaceborne and UAV-Borne Remote Sensing Spectral Data for Estimating Monsoon Crop Vegetation Parameters. Sensors 2021, 21, 2886. https://doi.org/10.3390/s21082886
Wijesingha J, Dayananda S, Wachendorf M, Astor T. Comparison of Spaceborne and UAV-Borne Remote Sensing Spectral Data for Estimating Monsoon Crop Vegetation Parameters. Sensors. 2021; 21(8):2886. https://doi.org/10.3390/s21082886
Chicago/Turabian StyleWijesingha, Jayan, Supriya Dayananda, Michael Wachendorf, and Thomas Astor. 2021. "Comparison of Spaceborne and UAV-Borne Remote Sensing Spectral Data for Estimating Monsoon Crop Vegetation Parameters" Sensors 21, no. 8: 2886. https://doi.org/10.3390/s21082886
APA StyleWijesingha, J., Dayananda, S., Wachendorf, M., & Astor, T. (2021). Comparison of Spaceborne and UAV-Borne Remote Sensing Spectral Data for Estimating Monsoon Crop Vegetation Parameters. Sensors, 21(8), 2886. https://doi.org/10.3390/s21082886