Articles | Volume 14, issue 6
Earth Syst. Sci. Data, 14, 2851–2864, 2022
https://doi.org/10.5194/essd-14-2851-2022
Earth Syst. Sci. Data, 14, 2851–2864, 2022
https://doi.org/10.5194/essd-14-2851-2022
Data description paper
23 Jun 2022
Data description paper | 23 Jun 2022

A 30 m annual maize phenology dataset from 1985 to 2020 in China

Quandi Niu et al.

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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 essd-2021-343', Anonymous Referee #1, 17 Feb 2022
  • RC2: 'Comment on essd-2021-343', Anonymous Referee #2, 21 Feb 2022
  • AC1: 'Comment on essd-2021-343', Q. D. Niu, 27 Apr 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Q. D. Niu on behalf of the Authors (29 Apr 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (09 May 2022) by Alexander Gruber
RR by Anonymous Referee #2 (17 May 2022)
RR by Anonymous Referee #1 (26 May 2022)
ED: Publish subject to technical corrections (01 Jun 2022) by Alexander Gruber
AR by Q. D. Niu on behalf of the Authors (02 Jun 2022)  Author's response    Manuscript
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Short summary
In this paper we generated the first national maize phenology product with a fine spatial resolution (30 m) and a long temporal span (1985–2020) in China, using Landsat images. The derived phenological indicators agree with in situ observations and provide more spatial details than moderate resolution phenology products. The extracted maize phenology dataset can support precise yield estimation and deepen our understanding of the response of agroecosystem to global warming in the future.