Monitoring of Wheat Growth Status and Mapping of Wheat Yield’s within-Field Spatial Variations Using Color Images Acquired from UAV-camera System
Abstract
:1. Introduction
2. Materials and Methods
2.1. Field Site and Acquisition of UAV Images
2.2. Radiometric Normalization of Multi-Temporal UAV Images
2.3. Field Sampling of Wheat Yield
2.4. Generating CVI Maps Based on UAV Images
3. Result and Discussion
3.1. Monitoring of Wheat Growth Status
3.2. Evaluation of Radiometric Normalization of Multi-Temporal Orthomosaic Images
3.3. Mapping of Wheat Yield’s within-Field Spatial Variations
4. Uncertainties, Errors, and Accuracies
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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UAV Specification | Camera Specification | ||
---|---|---|---|
Overall diameter × height (mm) | φ1009 × 254 | Weight (gram) | 345 |
Rated operation weight (kg) | 3.2 | Camera resolution | 4000 × 6000 pixels |
Endurance (min) | 15–20 | Focal length (mm) | 16 |
Range (km) | 10 | Sensor size(mm) | 23.5 × 15.6 |
Maximus flying altitude (m) | 250 |
Wheat Variety | Sample ID. | Sample Position | Sampled Grain Weight (kg, Converted to 12.5% Moisture) | |
---|---|---|---|---|
Latitude | Longitude | |||
Kitahonami | 1 | 42.901657 | 142.978642 | 1.01 |
2 | 42.901097 | 142.979570 | 0.86 | |
3 | 42.900532 | 142.980497 | 0.84 | |
4 | 42.900180 | 142.981070 | 0.91 | |
5 | 42.900360 | 142.981302 | 0.85 | |
6 | 42.900694 | 142.980759 | 0.79 | |
7 | 42.900972 | 142.980286 | 0.82 | |
8 | 42.901202 | 142.979924 | 0.80 | |
9 | 42.901476 | 142.979472 | 0.83 |
Image Date | Band | Slope | Intercept | R-Squared |
---|---|---|---|---|
2 June | Blue | 1.01 | 6.55 | 0.83 |
Green | 0.77 | 45.38 | 0.96 | |
Red | 0.74 | 52.52 | 0.94 | |
10 June | Blue | 0.86 | 15.43 | 0.73 |
Green | 0.87 | 7.96 | 0.91 | |
Red | 0.85 | 11.55 | 0.91 | |
19 June | Blue | 0.77 | 42.65 | 0.91 |
Green | 1.09 | −15.09 | 0.94 | |
Red | 1.10 | −17.33 | 0.93 | |
25 June | Blue | 0.99 | 4.14 | 0.97 |
Green | 0.95 | 9.623 | 0.99 | |
Red | 0.92 | 12.56 | 0.99 | |
2 July | Blue | 0.82 | 28.49 | 0.94 |
Green | 1.03 | −13.48 | 0.98 | |
Red | 1.03 | −12.15 | 0.98 | |
10 July | Blue | 0.88 | 22.77 | 0.81 |
Green | 1.01 | −2.42 | 0.94 | |
Red | 1.06 | −10.30 | 0.93 | |
16 July | Blue | 0.79 | 47.09 | 0.97 |
Green | 1.16 | −15.27 | 0.98 | |
Red | 1.16 | −16.84 | 0.97 | |
24 July | Blue | 0.94 | 12.01 | 0.80 |
Green | 0.89 | 17.61 | 0.97 | |
Red | 0.9031 | 16.2754 | 0.97 |
Sample ID | VDVI | NGRDI | NGBDI | GRRI | ExG |
---|---|---|---|---|---|
1 | 0.71 | 1.00 | 0.50 | 10.40 | 333.17 |
2 | 0.65 | 1.16 | 0.29 | 10.86 | 264.30 |
3 | 0.62 | 1.04 | 0.29 | 10.49 | 286.08 |
4 | 0.64 | 1.11 | 0.27 | 10.70 | 296.75 |
5 | 0.67 | 1.10 | 0.33 | 10.65 | 301.90 |
6 | 0.62 | 1.12 | 0.24 | 10.70 | 276.56 |
7 | 0.62 | 1.19 | 0.18 | 11.00 | 259.11 |
8 | 0.63 | 1.16 | 0.25 | 10.81 | 244.95 |
9 | 0.62 | 1.19 | 0.18 | 10.96 | 259.36 |
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Du, M.; Noguchi, N. Monitoring of Wheat Growth Status and Mapping of Wheat Yield’s within-Field Spatial Variations Using Color Images Acquired from UAV-camera System. Remote Sens. 2017, 9, 289. https://doi.org/10.3390/rs9030289
Du M, Noguchi N. Monitoring of Wheat Growth Status and Mapping of Wheat Yield’s within-Field Spatial Variations Using Color Images Acquired from UAV-camera System. Remote Sensing. 2017; 9(3):289. https://doi.org/10.3390/rs9030289
Chicago/Turabian StyleDu, Mengmeng, and Noboru Noguchi. 2017. "Monitoring of Wheat Growth Status and Mapping of Wheat Yield’s within-Field Spatial Variations Using Color Images Acquired from UAV-camera System" Remote Sensing 9, no. 3: 289. https://doi.org/10.3390/rs9030289
APA StyleDu, M., & Noguchi, N. (2017). Monitoring of Wheat Growth Status and Mapping of Wheat Yield’s within-Field Spatial Variations Using Color Images Acquired from UAV-camera System. Remote Sensing, 9(3), 289. https://doi.org/10.3390/rs9030289