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Small, N.; Prosser, H.; Durance, I.

Predicted outcomes from land use change scenarios in upland Wales catchments
(DURESS)

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© NERC and Cardiff University

This dataset is made available under the terms of the Open Government Licence

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https://doi.org/10.5285/0dd30cc6-d4fb-42f5-a5a4-954cf01a230b
A spatial approach was developed to interpret qualitatively expressed scenarios, and predict the probability and amount of change for 10 land-cover types across 127 sub-catchments in upland Wales. Existing data, which have a temporal coverage of 1998-2007, were used for the underpinning mapping, and fed into the tabular land cover change summary data. For each scenario, the maximum and minimum land-cover change was projected using rules based on current land cover, agricultural land quality, ownership type, and nature conservation status. For each combination, total land-cover change summaries have been created, which indicate how land cover within the 127 sub-catchments may respond to change in the future. This work was part of the Diversity in Upland River Ecosystem Service Sustainability (DURESS) project, NERC grant NE/J014826/1.
Publication date: 2017-02-28
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More information

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Format

Comma-separated values (CSV)

Spatial information

Study area
Spatial representation type
Tabular (text)
Spatial reference system
OSGB 1936 / British National Grid

Temporal information

Temporal extent
2014-07-01    to    2015-12-01

Provenance & quality

Existing spatial datasets were collected and used to predict the maximum and minimum outcomes for land use change scenarios. These data include the 25 x 25m Land Cover Map 2007 raster, which was aggregated to 13 classes (see supporting documentation). The Agricultural Land Classification (ALC), designated boundary, and ownership data were also used. Using GIS, sub-catchment boundaries were used to clip the land cover, agricultural land quality, ownership, and designated sites data. Following this, two separate polygon layers were built to represent maximum (using land-cover and ALC data), and minimum (land-cover, ALC, plus additional datasets representing protected areas and areas of ownership) change. These were created by using the 'union' process in ArcGIS.
A unique identifier was created in the polygon layers, and in each rule-base. The purpose of this unique identifier was to help match all attributes in the data and rule-base and join them together. In ArcGIS, calculations such as land cover area, land cover area percent, and net change (before and after scenario was applied) were made. Due to multiple land cover, ALC, designation and protected area permutations, a final summary was needed to illustrate by how much land cover changed under the different scenarios. Therefore, in Excel, each land cover in each sub-catchment was summarised and a total area before and after scenario was calculated. These values were exported into Excel spreadsheets and then into comma separated values for ingestion into the EIDC.

Licensing and constraints

This dataset is made available under the terms of the Open Government Licence

Cite this dataset as:
Small, N.; Prosser, H.; Durance, I. (2017). Predicted outcomes from land use change scenarios in upland Wales catchments. NERC Environmental Information Data Centre. https://doi.org/10.5285/0dd30cc6-d4fb-42f5-a5a4-954cf01a230b

© NERC and Cardiff University

Related

Correspondence/contact details

Small, N.
Cardiff University
Sustainable Places Research Institute, 33 Park Place
Cardiff
CF10 3BA
 SmallN@cardiff.ac.uk

Authors

Small, N.
Cardiff University
Prosser, H.
Cardiff University
Durance, I.
Cardiff University

Other contacts

Custodian
NERC EDS Environmental Information Data Centre
 info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
 info@eidc.ac.uk

Additional metadata

Topic categories
economy
environment
health
inlandWaters
INSPIRE theme
Land Cover
Keywords
Biodiversity & Ecosystem Service Sustainability (BESS) , catchments , Diversity in Upland River Ecosystem Service Sustainability (DURESS) , land-cover , scenarios , uplands
Funding
Natural Environment Research Council Award: NE/J014826/1
Last updated
21 March 2025 13:35