Articles | Volume 24, issue 7
https://doi.org/10.5194/hess-24-3643-2020
https://doi.org/10.5194/hess-24-3643-2020
Research article
 | 
22 Jul 2020
Research article |  | 22 Jul 2020

Temporal interpolation of land surface fluxes derived from remote sensing – results with an unmanned aerial system

Sheng Wang, Monica Garcia, Andreas Ibrom, and Peter Bauer-Gottwein

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Cited articles

Alfieri, J. G., Anderson, M. C., Kustas, W. P., and Cammalleri, C.: Effect of the revisit interval and temporal upscaling methods on the accuracy of remotely sensed evapotranspiration estimates, Hydrol. Earth Syst. Sci., 21, 83–98, https://doi.org/10.5194/hess-21-83-2017, 2017. 
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Boegh, E., Poulsen, R. N., Butts, M., Abrahamsen, P., Dellwik, E., Hansen, S., Hasager, C. B., Ibrom, A., Loerup, J. K., Pilegaard, K., and Soegaard, H.: Remote sensing based evapotranspiration and runoff modeling of agricultural, forest and urban flux sites in Denmark: From field to macro-scale, J. Hydrol., 377, 300–316, https://doi.org/10.1016/j.jhydrol.2009.08.029, 2009. 
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Short summary
Remote sensing only provides snapshots of rapidly changing land surface variables; this limits its application for water resources and ecosystem management. To obtain continuous estimates of surface temperature, soil moisture, evapotranspiration, and ecosystem productivity, a simple and operational modelling scheme is presented. We demonstrate it with temporally sparse optical and thermal remote sensing data from an unmanned aerial system at a Danish bioenergy plantation eddy covariance site.