Estimation of gross land-use change and its uncertainty using a Bayesian data assimilation approach

Levy, Peter; van Oijen, Marcel; Buys, Gwen; Tomlinson, Sam

doi:https://doi.org/10.5194/bg-15-1497-2018

Articles | Volume 15, issue 5

https://doi.org/10.5194/bg-15-1497-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-15-1497-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 5

Research article

|

14 Mar 2018

Research article |

| 14 Mar 2018

Estimation of gross land-use change and its uncertainty using a Bayesian data assimilation approach

Peter Levy, Marcel van Oijen, Gwen Buys, and Sam Tomlinson

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Final revised paper (published on 14 Mar 2018)
Preprint (discussion started on 06 Nov 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Estimation of land-use change using a Bayesian data assimilation approach', Anonymous Referee #1, 08 Dec 2017
- AC1: 'Response to Referee 1', Peter E. Levy, 22 Dec 2017
RC2: 'comments on “Estimation of land-use change using a Bayesian data assimilation approach”', Anonymous Referee #2, 14 Dec 2017
- AC2: 'Response to Referee 2', Peter E. Levy, 22 Dec 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to minor revisions (review by editor) (10 Jan 2018) by Alexey V. Eliseev

AR by Peter E. Levy on behalf of the Authors (02 Feb 2018) Author's response Manuscript

ED: Publish as is (05 Feb 2018) by Alexey V. Eliseev

AR by Peter E. Levy on behalf of the Authors (05 Feb 2018)

Short summary

We present a new method for estimating land-use change using a Bayesian data assimilation approach. This allows us to constrain estimates of gross land-use change with reliable national-scale census data whilst retaining the information available from several other sources. This includes detailed spatial data; further data sources, such as new satellites, could easily be added in future. Uncertainty is propagated appropriately into the output.