Early-Season Stand Count Determination in Corn via Integration of Imagery from Unmanned Aerial Systems (UAS) and Supervised Learning Techniques
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Sites
2.2. Platform, Sensor, and Field Data Collection
2.3. Data Processing
2.4. Vegetation Detection
2.5. Row Detection
2.6. Feature Descriptors
2.7. Classifier Training
2.8. Classifier Performance Evaluation
3. Results and Discussion
3.1. Evaluation Metrics: Training Modes
3.2. Evaluation Metrics: Spatial Resolution
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Fields | Previous Crop | Planting Date (DOY) | Growth Stage | Flight Day (DOY) | Flight Altitude (m) |
---|---|---|---|---|---|
Site 1 | Soybean | 116 | v2 | 135 | 10 |
Site 2 | Soybean | 130 | v2–v3 | 153 | 10 |
Site 1 | Site 2 | |||
---|---|---|---|---|
Data Set | Training | Testing | Training | Testing |
Images | 94 | 75 | 87 | 75 |
Contours | 17,608 | 15,378 | 16,855 | 15,246 |
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Varela, S.; Dhodda, P.R.; Hsu, W.H.; Prasad, P.V.V.; Assefa, Y.; Peralta, N.R.; Griffin, T.; Sharda, A.; Ferguson, A.; Ciampitti, I.A. Early-Season Stand Count Determination in Corn via Integration of Imagery from Unmanned Aerial Systems (UAS) and Supervised Learning Techniques. Remote Sens. 2018, 10, 343. https://doi.org/10.3390/rs10020343
Varela S, Dhodda PR, Hsu WH, Prasad PVV, Assefa Y, Peralta NR, Griffin T, Sharda A, Ferguson A, Ciampitti IA. Early-Season Stand Count Determination in Corn via Integration of Imagery from Unmanned Aerial Systems (UAS) and Supervised Learning Techniques. Remote Sensing. 2018; 10(2):343. https://doi.org/10.3390/rs10020343
Chicago/Turabian StyleVarela, Sebastian, Pruthvidhar Reddy Dhodda, William H. Hsu, P. V. Vara Prasad, Yared Assefa, Nahuel R. Peralta, Terry Griffin, Ajay Sharda, Allison Ferguson, and Ignacio A. Ciampitti. 2018. "Early-Season Stand Count Determination in Corn via Integration of Imagery from Unmanned Aerial Systems (UAS) and Supervised Learning Techniques" Remote Sensing 10, no. 2: 343. https://doi.org/10.3390/rs10020343