ArticleScientific data2023
Mapping the spatial heterogeneity of global land use and land cover from 2020 to 2100 at a 1 km resolution.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
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- Spatial assessment of forest soil carbon and climate-related value inside and outside protected areas in China.Environmental monitoring and assessment · 2026Article
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- Climate Change Alters Elevational Distribution Patterns ofEcology and evolution · 2026Article
- Marine protected areas marginally offset anthropogenic declines in tropical reef fish contributions to nature and people.Nature ecology & evolution · 2026Article
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- Predicting the distribution ofFrontiers in plant science · 2026Article
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- Projecting spatiotemporal changes in Soil Organic Carbon stocks in Mexico under coupled socioeconomic and climate scenarios.PloS one · 2026Article
- 1 km HILDA + based land cover/use map time series of China under 1.5 °C climate of this century.Scientific data · 2025Article
- Integrating MaxEnt and PLUS for Predictive Modeling of Mangrove Suitability and Land Use Impacts in Coastal Guangdong, China.Ecology and evolution · 2025Article
- Impacts of urban and cropland expansions on natural habitats in Southeast Asia.Nature communications · 2025Article
- Global 1-km habitat distribution for endangered species and its spatial changes under future warming scenarios.Scientific data · 2025Article
- Environmental Change and Hemorrhagic Fever with Renal Syndrome Transmission Risk on the China-Russia Border.EcoHealth · 2025Article
- Current and Future Projection of Scrub Typhus Risk Related to Land Use Change in China.GeoHealth · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
A fine global future land use/land cover (LULC) is critical for demonstrating the geographic heterogeneity of earth system dynamics and human-earth interaction. In this study, we produced a 1 km global future LULC dataset that takes into account future climate and socio-economic changes as well as the impact of simulated results of the former year on temporally adjacent periods. By incorporating the variations in climatic and socio-economic factors, we differentiated LULC suitability probabilities for historical and future periods across representative SSP-RCP scenarios. Then, by using an improved cellular automata model-PLUS to simulate the patch-level changes of various land classes, we iteratively downscaled water-basin-level LULC demands in various future scenarios to a spatial resolution of 1 km. Our dataset achieves a high degree of simulation accuracy (Kappa = 0.94, OA = 0.97, FoM = 0.10) and precisely captures the spatial-temporal heterogeneity of global LULC changes under the combined effects of climate change and socio-economic development. This robust and fine-scale LULC dataset provides valuable spatially-explicit information essential for earth system modeling and intricate dynamics between anthropogenic activities and the environment.
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