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

Zhang, Tianyuan; Cheng, Changxiu; Wu, Xudong

doi:10.1038/s41597-023-02637-7

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学術論文

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

Authors

Zhang, Tianyuan
External Organizations;

Cheng, Changxiu
External Organizations;

/persons/resource/xudong.wu

Wu, Xudong
Potsdam Institute for Climate Impact Research;

URL

https://doi.org/10.6084/m9.figshare.23542860.v1
(付録資料)

フルテキスト (公開)

2023_11_Wu_Zhang et al. - Global land use and land cover.pdf
(出版社版), 5MB

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引用

Zhang, T., Cheng, C., & Wu, X. (2023). Mapping the spatial heterogeneity of global land use and land cover from 2020 to 2100 at a 1 km. Scientific Data, 10:. doi:10.1038/s41597-023-02637-7.

引用: https://publications.pik-potsdam.de/pubman/item/item_28981

要旨

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.