estimating evaporation with thermal uav data and two-source energy balance models
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2016
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Abstract
Estimating evaporation is important when managing water
resources and cultivating crops. Evaporation can be estimated using land
surface heat flux models and remotely sensed land surface temperatures
(LST), which have recently become obtainable in very high resolution using
lightweight thermal cameras and Unmanned Aerial Vehicles (UAVs). In this
study a thermal camera was mounted on a UAV and applied into the field of
heat fluxes and hydrology by concatenating thermal images into mosaics of
LST and using these as input for the two-source energy balance (TSEB) modelling
scheme. Thermal images are obtained with a fixed-wing UAV overflying
a barley field in western Denmark during the growing season of 2014 and a
spatial resolution of 0.20 m is obtained in final LST mosaics. Two models
are used: the original TSEB model (TSEB-PT) and a
dual-temperature-difference (DTD) model. In contrast to the TSEB-PT model,
the DTD model accounts for the bias that is likely present in remotely sensed
LST. TSEB-PT and DTD have already been well tested, however only during
sunny weather conditions and with satellite images serving as thermal input.
The aim of this study is to assess whether a lightweight thermal camera
mounted on a UAV is able to provide data of sufficient quality to constitute
as model input and thus attain accurate and high spatial and temporal
resolution surface energy heat fluxes, with special focus on latent heat
flux (evaporation). Furthermore, this study evaluates the performance of the
TSEB scheme during cloudy and overcast weather
conditions, which is feasible due to the low data retrieval altitude (due to
low UAV flying altitude) compared to satellite thermal data that are only
available during clear-sky conditions. TSEB-PT and DTD fluxes are compared
and validated against eddy covariance measurements and the comparison shows
that both TSEB-PT and DTD simulations are in good agreement with eddy
covariance measurements, with DTD obtaining the best results. The DTD model
provides results comparable to studies estimating evaporation with similar
experimental setups, but with LST retrieved from satellites instead of a
UAV. Further, systematic irrigation patterns on the barley field provide
confidence in the veracity of the spatially distributed evaporation revealed
by model output maps. Lastly, this study outlines and discusses the thermal
UAV image processing that results in mosaics suited for model input. This
study shows that the UAV platform and the lightweight thermal camera provide
high spatial and temporal resolution data valid for model input and for
other potential applications requiring high-resolution and consistent LST.
| Reference Key |
hoffmann2016hydrologyestimating
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|---|---|
| Authors | ;H. Hoffmann;H. Nieto;R. Jensen;R. Guzinski;P. Zarco-Tejada;T. Friborg |
| Journal | materials research bulletin |
| Year | 2016 |
| DOI |
10.5194/hess-20-697-2016
|
| URL | |
| Keywords |
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