Introducing LandScaleR: A novel method for spatial downscaling of land use projections

Tamsin L. Woodman; Cristina Rueda-Uribe; Roslyn C. Henry; David F.R.P. Burslem; Justin M.J. Travis; Peter Alexander

doi:10.1016/j.envsoft.2023.105826

Introducing LandScaleR: A novel method for spatial downscaling of land use projections

Tamsin L. Woodman^*, Cristina Rueda-Uribe, Roslyn C. Henry, David F.R.P. Burslem, Justin M.J. Travis, Peter Alexander

^*Corresponding author for this work

University of Edinburgh

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Abstract

Land use and land cover (LULC) projections do not always have sufficient spatial resolution to allow them to be used by environmental models that project how LULC impacts a range of variables, including ecosystem services, biodiversity, and hydrology. We present a downscaling method designed to generate the high resolution LULC projections often required for environmental modelling. LULC change is allocated to a high-resolution reference map based on the density of LULC classes in neighbouring grid cells. Increasing a parameter that controls the likelihood of cells adjacent to existing LULC classes being converted to the same class generated less spatially aggregated landscapes that better represented historic LULC patterns in Colombia between 1960 and 2019. This new downscaling method is available as an R package and will enable the reconciliation of the spatial resolution of LULC projections and key processes that are embedded in a range of environmental models.

Original language	English
Article number	105826
Number of pages	14
Journal	Environmental Modelling and Software
Volume	169
Early online date	23 Sept 2023
DOIs	https://doi.org/10.1016/j.envsoft.2023.105826
Publication status	Published - Nov 2023

Bibliographical note

Funding Information:
TW was funded by an EASTBIO UKRI BBSRC grant number BB/T00875X/1 . Downscaling simulations and calculation of landscape pattern metrics were performed on the University of Aberdeen HPC, Maxwell.

Data Availability Statement

Software name: LandScaleR.
Developer: Tamsin L. Woodman.
Developer contact information: tlw36@cantab.ac.uk.
First year available: 2023.
Hardware requirements: PC/Mac.
Software requirements: R statistical environment and language;
Software availability: https://github.com/TamsinWoodman/L
andScaleR;
Cost: free.
Program language: R.
Program size: 3.56 MB.
The code and HILDA+ dataset that were used to validate the LandScaleR method are available at https://github.com/TamsinWoodman
/LandScaleR-validation and https://doi.pangaea.de/10.1594/PANGAEA.921846 (Winkler et al., 2020), respectively.

Keywords

Colombia
Downscaling
Land use and land cover
Land use models

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Woodman_Etal_EMS_Introducing_LandScaleR_A_VOR
1364-8152/© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Final published version, 6.29 MBLicence: CC BY

Cite this

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title = "Introducing LandScaleR: A novel method for spatial downscaling of land use projections",

abstract = "Land use and land cover (LULC) projections do not always have sufficient spatial resolution to allow them to be used by environmental models that project how LULC impacts a range of variables, including ecosystem services, biodiversity, and hydrology. We present a downscaling method designed to generate the high resolution LULC projections often required for environmental modelling. LULC change is allocated to a high-resolution reference map based on the density of LULC classes in neighbouring grid cells. Increasing a parameter that controls the likelihood of cells adjacent to existing LULC classes being converted to the same class generated less spatially aggregated landscapes that better represented historic LULC patterns in Colombia between 1960 and 2019. This new downscaling method is available as an R package and will enable the reconciliation of the spatial resolution of LULC projections and key processes that are embedded in a range of environmental models.",

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author = "Woodman, {Tamsin L.} and Cristina Rueda-Uribe and Henry, {Roslyn C.} and Burslem, {David F.R.P.} and Travis, {Justin M.J.} and Peter Alexander",

note = "Funding Information: TW was funded by an EASTBIO UKRI BBSRC grant number BB/T00875X/1 . Downscaling simulations and calculation of landscape pattern metrics were performed on the University of Aberdeen HPC, Maxwell. ",

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AU - Burslem, David F.R.P.

AU - Travis, Justin M.J.

AU - Alexander, Peter

N1 - Funding Information: TW was funded by an EASTBIO UKRI BBSRC grant number BB/T00875X/1 . Downscaling simulations and calculation of landscape pattern metrics were performed on the University of Aberdeen HPC, Maxwell.

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N2 - Land use and land cover (LULC) projections do not always have sufficient spatial resolution to allow them to be used by environmental models that project how LULC impacts a range of variables, including ecosystem services, biodiversity, and hydrology. We present a downscaling method designed to generate the high resolution LULC projections often required for environmental modelling. LULC change is allocated to a high-resolution reference map based on the density of LULC classes in neighbouring grid cells. Increasing a parameter that controls the likelihood of cells adjacent to existing LULC classes being converted to the same class generated less spatially aggregated landscapes that better represented historic LULC patterns in Colombia between 1960 and 2019. This new downscaling method is available as an R package and will enable the reconciliation of the spatial resolution of LULC projections and key processes that are embedded in a range of environmental models.

AB - Land use and land cover (LULC) projections do not always have sufficient spatial resolution to allow them to be used by environmental models that project how LULC impacts a range of variables, including ecosystem services, biodiversity, and hydrology. We present a downscaling method designed to generate the high resolution LULC projections often required for environmental modelling. LULC change is allocated to a high-resolution reference map based on the density of LULC classes in neighbouring grid cells. Increasing a parameter that controls the likelihood of cells adjacent to existing LULC classes being converted to the same class generated less spatially aggregated landscapes that better represented historic LULC patterns in Colombia between 1960 and 2019. This new downscaling method is available as an R package and will enable the reconciliation of the spatial resolution of LULC projections and key processes that are embedded in a range of environmental models.

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Introducing LandScaleR: A novel method for spatial downscaling of land use projections

Abstract

Bibliographical note

Data Availability Statement

Keywords

UN SDGs

Access to Document

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Cite this