Articles | Volume 17, issue 9
https://doi.org/10.5194/essd-17-4331-2025
https://doi.org/10.5194/essd-17-4331-2025
Data description paper
 | 
05 Sep 2025
Data description paper |  | 05 Sep 2025

A typology of global relief classes derived from digital elevation models at 1 arcsec resolution

Xin Yang, Sijin Li, Junfei Ma, Yang Chen, Xingyu Zhou, Fayuan Li, Liyang Xiong, Chenghu Zhou, Guoan Tang, and Michael E. Meadows

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Cited articles

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Amatulli, G., McInerney, D., Sethi, T., Strobl, P., and Domisch, S.: Geomorpho90m, empirical evaluation and accuracy assessment of global high-resolution geomorphometric layers, Sci. Data, 7, 162, https://doi.org/10.1038/s41597-020-0479-6, 2020. 
Beck, H. E., McVicar, T. R., Vergopolan, N., Berg, A., Lutsko, N. J., Dufour, A., Zeng, Z., Jiang, X., van Dijk, A. I., and Miralles, D. G.: High-resolution (1 km) Köppen-Geiger maps for 1901–2099 based on constrained CMIP6 projections, Sci. Data, 10, 724, https://doi.org/10.1038/s41597-023-02549-6, 2023. 
Chen, Y. and Digital Terrain Analysis Group: nnu-dta/Global-Relief-Classes: GRC-pre-release, Version pre-release, Zenodo [software], https://doi.org/10.5281/zenodo.16979975, 2025. 
Drăguţ, L. and Blaschke, T.: Automated classification of landform elements using object-based image analysis, Geomorphology, 81, 330–344, https://doi.org/10.1016/j.geomorph.2006.04.013, 2006. 
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Short summary
Surveys of global relief classes are important for understanding the morphology and land processes of Earth's surface. This study proposes a novel framework integrating the accumulated slope and a new surface relief index for global relief classification (GRC) with 1 arcsec resolution. This dataset can provide abundant and detailed land surface information for the field of Earth sciences.
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