Articles | Volume 13, issue 24
https://doi.org/10.5194/bg-13-6545-2016
https://doi.org/10.5194/bg-13-6545-2016
Research article
 | 
15 Dec 2016
Research article |  | 15 Dec 2016

Crop water stress maps for an entire growing season from visible and thermal UAV imagery

Helene Hoffmann, Rasmus Jensen, Anton Thomsen, Hector Nieto, Jesper Rasmussen, and Thomas Friborg

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Revised manuscript accepted for BG
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Cited articles

Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration – Guidelines for computing crop water requirements – FAO Irrigation and drainage paper 56, FAO Rome, 300, D05109, 1998.
Anderson, M. C., Norman, J. M., Diak, G. R., Kustas, W. P., and Mecikalski, J. R.: A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing, Remote Sens. Environ., 60, 195–216, https://doi.org/10.1016/S0034-4257(96)00215-5, 1997.
Baluja, J., Diago, M. P., Balda, P., Zorer, R., Meggio, F., Morales, F., and Tardaguila, J.: Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV), Irrigation Sci., 30, 511–522, https://doi.org/10.1007/s00271-012-0382-9, 2012.
Barbosa da Silva, B. and Ramana Rao, T. V.: The CWSI variations of a cotton crop in a semi-arid region of Northeast Brazil, J. Arid Environ., 62, 649–659, https://doi.org/10.1016/j.jaridenv.2005.01.017, 2005.
Berni, J. A. J., Zarco-Tejada, P. J., Sepulcre-Cantó, G., Fereres, E., and Villalobos, F.: Mapping canopy conductance and CWSI in olive orchards using high resolution thermal remote sensing imagery, Remote Sens. Environ., 113, 2380–2388, https://doi.org/10.1016/j.rse.2009.06.018, 2009a.
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This study investigates whether the UAV (drone) based WDI can determine crop water stress from fields with open canopies (land surface consisting of both soil and canopy) and from fields where canopies are starting to senesce. This utility could solve issues that arise when applying the commonly used CWSI stress index. The WDI succeeded in providing accurate, high-resolution estimates of crop water stress at different growth stages of barley.
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