Improving land use change tracking in the UK Greenhouse Gas Inventory: final outputs report

Levy, Peter ORCID: https://orcid.org/0000-0002-8505-1901; Rowland, Clare ORCID: https://orcid.org/0000-0002-0459-506X; Buys, Gwen; Clark, Liz; Correia, Vera; Ditchburn, Ben; Evangelides, Christopher; Higgins, Alex; Marston, Christopher ORCID: https://orcid.org/0000-0002-2070-2187; Morton, Daniel; Olave, Rodrigo; O'Neil, Aneurin ORCID: https://orcid.org/0000-0003-3591-1034; Raine, Beth ORCID: https://orcid.org/0000-0002-0811-6118; Tomlinson, Sam ORCID: https://orcid.org/0000-0002-3237-7596; Walker, Anthony; Watterson, John; Whitton, Esther; Williamson, Jennifer; Thomson, Amanda ORCID: https://orcid.org/0000-0002-7306-4545. 2024 Improving land use change tracking in the UK Greenhouse Gas Inventory: final outputs report. Department of Net Zero and Energy Security, 293pp. (UKCEH Project no. 07643)

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Official URL: https://naei.beis.gov.uk/reports/reports?report_id...

Abstract/Summary

This report describes work on the project “Improving Land Use Change Tracking in the UK Greenhouse Gas Inventory” for the Department for Business, Energy & Industrial Strategy (reference TRN 2384/05/2020). The aim of the project was to make improved estimates of land-use change in the UK, using multiple sources of data. We applied a method for estimating land-use change using a Bayesian data assimilation approach. This allows us to constrain estimates of gross land-use change with national-scale census data, whilst retaining the detailed information available from several other sources. We produced a time series of maps describing our best estimate of land-use change given the available data, as well as the full posterior distribution of this space-time data cube. This quantifies the joint probability distribution of the parameters, and properly propagates the uncertainty from input data to final output. The output data has been summarised in the form of land-use vectors. The results show that we can provide improved estimates of past land-use change using this method. The main advantage of the approach is that it provides a coherent, generalised framework for combining multiple disparate sources of data, and adding further sources of data in future would be straightforward. Future work could focus on more detailed analysis of existing data sets, introducing independent constraints where possible, and obtaining further relevant data sets. The code is available via GitHub.

Item Type:	Publication - Report (Project Report)
UKCEH and CEH Sections/Science Areas:	Atmospheric Chemistry and Effects (Science Area 2017-) Pollution (Science Area 2017-) Soils and Land Use (Science Area 2017-)
Funders/Sponsors:	Department of Energy Security and Net Zero
Additional Information. Not used in RCUK Gateway to Research.:	Full text available via Official URL link.
NORA Subject Terms:	Ecology and Environment Agriculture and Soil Science Data and Information
Date made live:	15 Apr 2024 15:30 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/537270

Item Type:

Publication - Report (Project Report)

UKCEH and CEH Sections/Science Areas:

Atmospheric Chemistry and Effects (Science Area 2017-)
Pollution (Science Area 2017-)
Soils and Land Use (Science Area 2017-)

Funders/Sponsors:

Department of Energy Security and Net Zero

Additional Information. Not used in RCUK Gateway to Research.:

Full text available via Official URL link.

NORA Subject Terms:

Ecology and Environment
Agriculture and Soil Science
Data and Information

Date made live:

15 Apr 2024 15:30 +0 (UTC)