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

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (02 Apr 2020) by Nunzio Romano
AR by Sheng Wang on behalf of the Authors (02 Apr 2020)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (13 Apr 2020) by Nunzio Romano
RR by Nunzio Romano (28 Apr 2020)
RR by Anonymous Referee #2 (20 May 2020)
ED: Publish subject to revisions (further review by editor and referees) (21 May 2020) by Nunzio Romano
AR by Sheng Wang on behalf of the Authors (01 Jun 2020)  Author's response   Manuscript 
ED: Publish as is (24 Jun 2020) by Nunzio Romano
AR by Sheng Wang on behalf of the Authors (25 Jun 2020)  Manuscript 
Download
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.