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Article

Measures of Canopy Structure from Low-Cost UAS for Monitoring Crop Nutrient Status

1
Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA
2
Crop and Soil Sciences, North Carolina State University, Raleigh, NC 27695, USA
3
Horticultural Science, North Carolina State University, Raleigh, NC 27695, USA
4
Entomology and Plant Pathology, North Carolina State University, Raleigh, NC 27695, USA
5
Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA
*
Author to whom correspondence should be addressed.
Current address: The Scotts Miracle-Gro Company, Marysville, OH 43040, USA.
Drones 2020, 4(3), 36; https://doi.org/10.3390/drones4030036
Received: 6 June 2020 / Revised: 16 July 2020 / Accepted: 17 July 2020 / Published: 22 July 2020
Deriving crop information from remotely sensed data is an important strategy for precision agriculture. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool that can provide precisely-timed, fine-grained data for informing management responses to intra-field crop variability (e.g., nutrient status and pest damage). UAS sensors with high spectral resolution used to compute informative vegetation indices, however, are practically limited by high cost and data dimensionality. This research extends spectral analysis for remote crop monitoring to investigate the relationship between crop health and 3D canopy structure using low-cost UAS equipped with consumer-grade RGB cameras. We used flue-cured tobacco as a case study due to its known sensitivity to fertility variation and nutrient-specific symptomology. Fertilizer treatments were applied to induce plant health variability in a 0.5 ha field of flue-cured tobacco. Multi-view stereo images from three UAS surveys collected during crop development were processed into orthoimages used to compute a visible band spectral index and photogrammetric point clouds using Structure from Motion (SfM). Plant structural metrics were then computed from detailed high resolution canopy surface models (0.05 m resolution) interpolated from the photogrammetric point clouds. The UAS surveys were complimented by nutrient status measurements obtained from plant tissues. The relationships between foliar nitrogen (N), phosphorus (P), potassium (K), and boron (B) concentrations and the UAS-derived metrics were assessed using multiple linear regression. Symptoms of N and K deficiencies were well captured and differentiated by the structural metrics. The strongest relationship observed was between canopy shape and N foliar concentration (adj. r2 = 0.59, increasing to adj. r2 = 0.81 when combined with the spectral index). B foliar concentration was consistently better predicted by canopy structure with a maximum adj. r2 = 0.41 observed at the latest growth stage surveyed. Overall, combining information about canopy structure and spectral reflectance increased model fit for all measured nutrients compared to spectral alone. These results suggest that an important relationship exists between relative canopy shape and crop health that can be leveraged to improve the usefulness of low cost UAS for precision agriculture. View Full-Text
Keywords: unmanned aerial systems; precision agriculture; canopy structure; crop surface model; visible band index; flue-cured tobacco unmanned aerial systems; precision agriculture; canopy structure; crop surface model; visible band index; flue-cured tobacco
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MDPI and ACS Style

Montgomery, K.; Henry, J.B.; Vann, M.C.; Whipker, B.E.; Huseth, A.S.; Mitasova, H. Measures of Canopy Structure from Low-Cost UAS for Monitoring Crop Nutrient Status. Drones 2020, 4, 36. https://doi.org/10.3390/drones4030036

AMA Style

Montgomery K, Henry JB, Vann MC, Whipker BE, Huseth AS, Mitasova H. Measures of Canopy Structure from Low-Cost UAS for Monitoring Crop Nutrient Status. Drones. 2020; 4(3):36. https://doi.org/10.3390/drones4030036

Chicago/Turabian Style

Montgomery, Kellyn; Henry, Josh B.; Vann, Matthew C.; Whipker, Brian E.; Huseth, Anders S.; Mitasova, Helena. 2020. "Measures of Canopy Structure from Low-Cost UAS for Monitoring Crop Nutrient Status" Drones 4, no. 3: 36. https://doi.org/10.3390/drones4030036

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