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Mapping the spatial heterogeneity of global land use and land cover from 2020 to 2100 at a 1 km resolution.


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.

SUBMITTER: Zhang T 

PROVIDER: S-EPMC10613310 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Mapping the spatial heterogeneity of global land use and land cover from 2020 to 2100 at a 1 km resolution.

Zhang Tianyuan T   Cheng Changxiu C   Wu Xudong X  

Scientific data 20231028 1


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 probabiliti  ...[more]

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