Cite this dataset as
Xu, J.; Renaud, F.G.; Barrett, B. (2021). Land use maps under the trend, expansion, sustainability, and conservation scenarios in 2030 in the Luanhe River Basin, China by using the CLUMondo Model. NERC EDS Environmental Information Data Centre. (Dataset). https://doi.org/10.5285/a94640dc-fe21-4c38-936b-d62dfca0c952
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This dataset is available under the terms of the Open Government Licence 
Land use maps under the trend, expansion, sustainability, and conservation scenarios in 2030 in the Luanhe River Basin, China by using the CLUMondo Model
Dataset contains the Land Use/Land Cover (LULC) map under four scenarios (Trend, Expansion, Sustainability, and Conservation) in 2030 in the Luanhe River Basin (LRB), China, with a resolution of 1km. The scenarios were based on different socio-economic development and environmental protection targets, local plans and policies, and the information from a stakeholders’ workshop, to explore land system evolution trajectories of the LRB and major challenges that the river basin may face in the future.
The map includes nine different land use classes: 1) Extensive cropland, 2) Medium intensive cropland, 3) Intensive cropland, 4) Forest, 5) Grassland with low livestock, 6) Grassland with high livestock, 7) Water, 8) Built-up area and 9) Unused land. The land system classification is based on three main classification factors: (1) land use and cover, (2) livestock, and (3) agricultural intensity.
The data was funded by UK Research and Innovation (UKRI) through the Natural Environment Research Council’s (NERC) Towards a Sustainable Earth (TaSE) programme, for the project “River basins as ‘living laboratories’ for achieving sustainable development goals across national and sub-national scales” (Grant no. NE/S012427/1) .
The map includes nine different land use classes: 1) Extensive cropland, 2) Medium intensive cropland, 3) Intensive cropland, 4) Forest, 5) Grassland with low livestock, 6) Grassland with high livestock, 7) Water, 8) Built-up area and 9) Unused land. The land system classification is based on three main classification factors: (1) land use and cover, (2) livestock, and (3) agricultural intensity.
The data was funded by UK Research and Innovation (UKRI) through the Natural Environment Research Council’s (NERC) Towards a Sustainable Earth (TaSE) programme, for the project “River basins as ‘living laboratories’ for achieving sustainable development goals across national and sub-national scales” (Grant no. NE/S012427/1) .
Publication date: 2021-07-06
Where/When
- Study area
-
- Temporal extent
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2030-01-01 to 2030-12-31
Provenance & quality
The map was developed based on three steps:
First, land systems of the Luanhe River Basin (LRB) in the years 2000 and 2015 were mapped by integrating different datasets related to human-environment attributes. Then, the relationship between the land systems and local explanatory factors was calculated for the initial year (2000).
Second, the CLUMondo model was parameterised and calibrated based on the 2015 land systems map.
Finally, changes in the land systems from 2015 to 2030 were simulated under different scenarios, including alternative sets of demands for commodities and services and represented different pathways on managing LRB’s land resources.
First, land systems of the Luanhe River Basin (LRB) in the years 2000 and 2015 were mapped by integrating different datasets related to human-environment attributes. Then, the relationship between the land systems and local explanatory factors was calculated for the initial year (2000).
Second, the CLUMondo model was parameterised and calibrated based on the 2015 land systems map.
Finally, changes in the land systems from 2015 to 2030 were simulated under different scenarios, including alternative sets of demands for commodities and services and represented different pathways on managing LRB’s land resources.
Related
Correspondence/contact details
Authors
Xu, J.
School of Interdisciplinary Studies, University of Glasgow
https://orcid.org/0000-0003-2949-5353
Renaud, F.G.
School of Interdisciplinary Studies, University of Glasgow
Barrett, B.
School of Geographical & Earth Sciences, University of Glasgow
Other contacts
- Custodian
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NERC EDS Environmental Information Data Centreinfo@eidc.ac.uk
- Publisher
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NERC EDS Environmental Information Data Centreinfo@eidc.ac.uk
- Rights Holder
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University of GlasgowJiren.Xu@glasgow.ac.uk
Additional metadata
- Topic categories
- Environment , Imagery / Base Maps / Earth Cover
- Keywords
- China, CLUMondo, Cropland, Forest, Grassland, Land use, Luanhe River Basin, Urban
- INSPIRE Theme
- Environmental Monitoring Facilities
- Funding
- Natural Environment Research Council Award: NE/S012427/1
- Spatial representation type
- Vector
- Spatial reference system
- WGS 84 / Pseudo-Mercator
- Last updated
- 18 May 2022 12:28