Articles | Volume 18, issue 3
Research article
05 Feb 2021
Research article |  | 05 Feb 2021

Predicting evapotranspiration from drone-based thermography – a method comparison in a tropical oil palm plantation

Florian Ellsäßer, Christian Stiegler, Alexander Röll, Tania June, Hendrayanto, Alexander Knohl, and Dirk Hölscher


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (16 Aug 2020) by Dan Yakir
AR by Florian Ellsäßer on behalf of the Authors (25 Oct 2020)  Author's response    Manuscript
ED: Publish subject to technical corrections (21 Nov 2020) by Dan Yakir
AR by Florian Ellsäßer on behalf of the Authors (25 Nov 2020)  Author's response    Manuscript

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Florian Ellsäßer on behalf of the Authors (25 Jan 2021)   Author's adjustment   Manuscript
EA: Adjustments approved (01 Feb 2021) by Dan Yakir
Short summary
Recording land surface temperatures using drones offers new options to predict evapotranspiration based on energy balance models. This study compares predictions from three energy balance models with the eddy covariance method. A model II Deming regression indicates interchangeability for latent heat flux estimates from certain modeling methods and eddy covariance measurements. This complements the available methods for evapotranspiration studies by fine grain and spatially explicit assessments.
Final-revised paper