This study investigates whether a water deficit index (WDI) based on imagery
from unmanned aerial vehicles (UAVs) can provide accurate crop water stress
maps at different growth stages of barley and in differing weather
situations. Data from both the early and late growing season are included
to investigate whether the WDI has the unique potential to be
applicable both when the land surface is partly composed of bare soil and
when crops on the land surface are senescing. The WDI differs from the
more commonly applied crop water stress index (CWSI) in that it uses both a
spectral vegetation index (VI), to determine the degree of surface greenness,
and the composite land surface temperature (LST) (not solely canopy
temperature).Lightweight thermal and RGB (red–green–blue) cameras
were mounted on a UAV on three occasions during the growing season 2014, and
provided composite LST and color images, respectively. From the LST, maps of
surface-air temperature differences were computed. From the color images, the
normalized green–red difference index (NGRDI), constituting the indicator of
surface greenness, was computed. Advantages of the WDI as an irrigation map,
as compared with simpler maps of the surface-air temperature difference, are
discussed, and the suitability of the NGRDI is assessed. Final WDI maps
had a spatial resolution of 0.25 m.It was found that the UAV-based WDI is in agreement with measured stress values from an eddy covariance
system. Further, the WDI is especially valuable in the late growing
season because at this stage the remote sensing data represent crop water
availability to a greater extent than they do in the early growing season,
and because the WDI accounts for areas of ripe crops that no longer
have the same need for irrigation. WDI maps can potentially serve as water
stress maps, showing the farmer where irrigation is needed to ensure healthy
growing plants, during entire growing season
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