Articles | Volume 13, issue 11
Biogeosciences, 13, 3305–3317, 2016
https://doi.org/10.5194/bg-13-3305-2016
Biogeosciences, 13, 3305–3317, 2016
https://doi.org/10.5194/bg-13-3305-2016

Research article 06 Jun 2016

Research article | 06 Jun 2016

Modelling interannual variation in the spring and autumn land surface phenology of the European forest

Victor F. Rodriguez-Galiano et al.

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: Reconsider after major revisions (14 Jan 2016) by Andreas Ibrom
AR by Victor Rodriguez-Galiano on behalf of the Authors (02 Mar 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (07 Mar 2016) by Andreas Ibrom
RR by Anonymous Referee #1 (05 Apr 2016)
ED: Reconsider after major revisions (13 Apr 2016) by Andreas Ibrom
AR by Anna Mirena Feist-Polner on behalf of the Authors (27 Apr 2016)  Author's response    Manuscript
ED: Publish subject to minor revisions (Editor review) (11 May 2016) by Andreas Ibrom
AR by Victor Rodriguez-Galiano on behalf of the Authors (11 May 2016)  Author's response    Manuscript
ED: Publish as is (14 May 2016) by Andreas Ibrom
Download
Short summary
This research reveals new insights into the weather drivers of land surface phenology (LSP) across the entire European forest, while at the same time it establishes a new conceptual framework for modelling LSP. Specifically, a sophisticated machine learning regression method (RF) was introduced for LSP modelling across very large areas and across multiple years simultaneously. The RF models explained 81 and 62 % of the variance in the spring and autumn LSP interannual variation.
Altmetrics
Final-revised paper
Preprint