Using an unmanned aerial vehicle to evaluate nitrogen variability and height effect with an active crop canopy sensor

Precision Agriculture

Volumn 18, Issue 6, 2017, Pages 900-915

  Krienke, Brian ^a   Ferguson, Richard B ^a   Schlemmer, Michael ^b   Holland, Kyle ^c   Marx, David ^a   Eskridge, Kent ^a  

^a UNIVERSITY OF NEBRASKA LINCOLN   (United States)

^b BAYER CROPSCIENCE   (United States)

^c Electrical Engineer and Proprietor   (United States)

Author keywords

Active sensors; Imagery; Maize; Nitrogen variability; Unmanned aerial vehicle (UAV)

Indexed keywords

CANOPY ARCHITECTURE; COMPARATIVE STUDY; HEIGHT; IMAGERY; MAIZE; NITROGEN; NUTRIENT AVAILABILITY; NUTRITIONAL STATUS; SENSOR; UNMANNED VEHICLE;

POACEAE; ZEA MAYS;

EID: 85028968530     PISSN: 13852256     EISSN: 15731618     Source Type: Journal    
DOI: 10.1007/s11119-017-9534-5     Document Type: Article

References (30)

1. Abendroth, L. J., Elmore, R. W., Boyer, M. J., & Marlay, S. K. (2011). Corn growth and development. PMR 1009. Ames, USA: Iowa State University Extension.
2. Barker, D. W., & Sawyer, J. E. (2010). Using active canopy sensors to quantify corn nitrogen stress and nitrogen application rate. Agronomy Journal, 102(3), 964–971.
3. Berni, J. A. J., Zarco-Tejada, P. J., Suárez, L., & Fereres, E. (2009). Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on Geoscience Remote Sensing, 47(3), 722–738.
4. Birth, G. S., & McVey, G. R. (1968). Measuring the color of growing turf with a reflectance spectrophotometer. Agronomy Journal, 60(6), 640.
5. Buschmann, C., & Nagel, E. (1993). In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation. International Journal of Remote Sensing, 14, 711–722.
6. Ciganda, V. S., Gitelson, A. A., & Schepers, J. S. (2012). How deep does a remote sensor sense? Expression of chlorophyll content in a maize canopy. Remote Sensing of the Environment, 126, 240–247.
7. Colomina, I., & Molina, P. (2014). Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 92, 79–97.
8. Dash, J., & Curran, P. J. (2004). The MERIS terrestrial chlorophyll index. International Journal of Remote Sensing., 25(23), 5403–5413.
9. Datt, B. (1999). Visible/near infrared reflectance and chlorophyll content in eucalyptus leaves. International Journal of Remote Sensing, 20(14), 2741–2759.
10. Dellinger, A. E., Schmidt, J. P., & Beegle, D. B. (2008). Developing nitrogen fertilizer recommendations for corn using an active sensor. Agronomy Journal, 100(6), 1546–1552.
11. Gitelson, A. A. (2003). Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters, 30(5), 4–7.
12. Gitelson, A. A. (2004). Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. Journal of Plant Physiology, 161(2), 165–173.
13. Holland, K. H., Lamb, D. W., & Schepers, J. S. (2012). Radiometry of proximal active optical sensors (AOS) for agricultural sensing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing., 5(6), 1793–1802.
14. Holland, K. H., & Schepers, J. S. (2010). Derivation of a variable rate nitrogen application model for in-season fertilization of corn. Agronomy Journal, 102(5), 1415–1424.
15. Kitchen, N. R., Sudduth, K. A., Drummond, S. T., Scharf, P. C., Palm, H. L., Roberts, D. F., et al. (2010). Ground-based canopy reflectance sensing for variable-rate nitrogen corn fertilization. Agronomy Journal, 102(1), 71–84.
16. Lamb, D. W., Trotter, M. G., & Schneider, D. A. (2009). Ultra low-level airborne (ULLA) sensing of crop canopy reflectance: A case study using a CropCircle™ sensor. Computers and Electronics in Agriculture., 69(1), 86–91.
17. Li, Y., Chen, D., Walker, C. N., & Angus, J. F. (2010). Estimating the nitrogen status of crops using a digital camera. Field Crop Research, 118(3), 221–227.
18. Raun, W. R., Solie, J. B., Taylor, R. K., Arnall, D. B., Mack, C. J., & Edmonds, D. E. (2008). Ramp calibration strip technology for determining midseason nitrogen rates in corn and wheat. Agronomy Journal, 100(4), 1088–1093.
19. Roberts, D. F., Kitchen, N. R., Scharf, P. C., & Sudduth, K. A. (2010). Will variable-rate nitrogen fertilization using corn canopy reflectance sensing deliver environmental benefits? Agronomy Journal, 102(1), 85–95.
20. Rouse Jr., J.W., Haas, R.H., Schell, J.A., & Deering, D.W. (1973). Monitoring vegetation systems in the great plains with ERTS. In Third earth resources technology satellite-1 symposium (Vol. 1, pp. 309–330).
21. Samborski, S. M., Tremblay, N., & Fallon, E. (2009). Strategies to make use of plant sensors-based information for nitrogen recommendations. Agronomy Journal, 101(4), 800–816.
22. Scharf, P. C., Kitchen, N. R., Sudduth, K. A., Davis, J. G., Hubbard, V. C., & Lory, J. A. (2005). Field-scale variability in optimal nitrogen fertilizer rate for corn. Agronomy Journal, 97, 452–461.
23. Scharf, P. C., Shannon, D. K., Palm, H. L., Sudduth, K. A., Drummond, S. T., Kitchen, N. R., et al. (2011). Sensor-based nitrogen applications out-performed producer-chosen rates for corn in on-farm demonstrations. Agronomy Journal, 103(6), 1683–1691.
24. Schmidt, J., Beegle, D., Zhu, Q., & Sripada, R. (2011). Improving in-season nitrogen recommendations for maize using an active sensor. Field Crops Research, 120(1), 94–101.
25. Shanahan, J., Kitchen, N. R., Raun, W., & Schepers, J. (2008). Responsive in-season nitrogen management for cereals. Computers and Electronics in Agriculture, 61(1), 51–62.
26. Shanahan, J. F., Schepers, J. S., Francis, D. D., Varvel, G. E., Wilhelm, W. W., Tringe, J. M., et al. (2001). Use of remote-sensing imagery to estimate corn grain yield. Agronomy Journal, 93, 583–589.
27. Solari, F. (2006). Developing a crop based strategy for on-the-go nitrogen management in irrigated cornfields. AAT 3216347. PhD dissertation, University of Nebraska, Lincoln, USA.
28. Thompson, L. J., Ferguson, R. B., Kitchen, N. R., Frazen, D. W., Mamo, M., Yang, H., et al. (2015). Model and sensor-based recommendation approaches for in-season nitrogen management in corn. Agronomy Journal, 107, 2020–2030.
29. Viña, A., Gitelson, A. A., Nguy-Robertson, A. L., & Peng, Y. (2011). Comparison of different vegetation indices for the remote assessment of green leaf area index of crops. Remote Sensing of the Environment., 115(12), 3468–3478.
30. Zillmann, E., Graeff, S., Link, J., Batchelor, W. D., & Claupein, W. (2006). Assessment of cereal nitrogen requirements derived by optical on-the-go sensors on heterogeneous soils. Agronomy Journal, 98(3), 682–690.