Articles | Volume 21, issue 16
https://doi.org/10.5194/bg-21-3593-2024
https://doi.org/10.5194/bg-21-3593-2024
Research article
 | 
16 Aug 2024
Research article |  | 16 Aug 2024

Monitoring cropland daily carbon dioxide exchange at field scales with Sentinel-2 satellite imagery

Pia Gottschalk, Aram Kalhori, Zhan Li, Christian Wille, and Torsten Sachs

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2988', Anonymous Referee #1, 16 Feb 2024
    • AC1: 'Reply on RC1', Pia Gottschalk, 15 Mar 2024
    • AC2: 'Reply on RC1', Pia Gottschalk, 18 Mar 2024
  • RC2: 'Comment on egusphere-2023-2988', Anonymous Referee #2, 07 Mar 2024
    • AC3: 'Reply on RC2', Pia Gottschalk, 24 Mar 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (07 Apr 2024) by Andrew Feldman
AR by Pia Gottschalk on behalf of the Authors (27 May 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (28 May 2024) by Andrew Feldman
RR by Anonymous Referee #2 (04 Jun 2024)
ED: Publish as is (07 Jun 2024) by Andrew Feldman
AR by Pia Gottschalk on behalf of the Authors (10 Jun 2024)
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Short summary
To improve the accuracy of spatial carbon exchange estimates, we evaluated simple linear models for net ecosystem exchange (NEE) and gross primary productivity (GPP) and how they can be used to upscale the CO2 exchange of agricultural fields. The models are solely driven by Sentinel-2-derived vegetation indices (VIs). Evaluations show that different VIs have variable power to estimate NEE and GPP of crops in different years. The overall performance is as good as results from complex crop models.
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