A comprehensive grain-size database of surface sediments from the Taklamakan Desert

This study compiles the most comprehensive open-access surface sediment grain-size database (n = 596 samples) spanning the entire Taklamakan Desert, obtained through systematic field sampling and laser diffraction analysis. It provides essential data for understanding the desert formation, evolution, sand sources, and the restoration of aeolian environments. By analyzing key sediment parameters (mean grain size, sorting, skewness, kurtosis) and particle compositions, the dataset reveals sediment transport dynamics and depositional processes critical for understanding desert formation, sand provenance, and aeolian environmental reconstruction. The quantitative characterization of sediment texture and sorting mechanisms provides foundational data for investigating regional dust emissions, wind erosion patterns, and sediment transport capacities. While the primary focus is on the Taklamakan Desert, the methodology and dataset apply to other arid regions, making it a valuable resource for comparative desert studies. It is an indispensable tool for researchers investigating desert landscapes and addressing environmental challenges related to desertification and aeolian processes.

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Publication Details

Journal
Scientific Data
Published
2025-04-07
DOI
https://doi.org/10.1038/s41597-025-04936-7
Citations
3
Primary Topic
Geology and Paleoclimatology Research
Type
article
Field-Weighted Citation Impact
3.90
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article

A comprehensive grain-size database of surface sediments from the Taklamakan Desert

Yongcheng Zhao, Zuowei Yang, Jie Zhou, Zihao Hu et al.
3 citations
Scientific Data
Geology and Paleoclimatology Research
3.90
article

A comprehensive grain-size database of surface sediments from the Taklamakan Desert

Yongcheng Zhao, Zuowei Yang, Jie Zhou, Zihao Hu, Zhuo Chen, Shengyu Li, Xin Gao, Hao Li
article en
3 citations

Abstract

This study compiles the most comprehensive open-access surface sediment grain-size database (n = 596 samples) spanning the entire Taklamakan Desert, obtained through systematic field sampling and laser diffraction analysis. It provides essential data for understanding the desert formation, evolution, sand sources, and the restoration of aeolian environments. By analyzing key sediment parameters (mean grain size, sorting, skewness, kurtosis) and particle compositions, the dataset reveals sediment transport dynamics and depositional processes critical for understanding desert formation, sand provenance, and aeolian environmental reconstruction. The quantitative characterization of sediment texture and sorting mechanisms provides foundational data for investigating regional dust emissions, wind erosion patterns, and sediment transport capacities. While the primary focus is on the Taklamakan Desert, the methodology and dataset apply to other arid regions, making it a valuable resource for comparative desert studies. It is an indispensable tool for researchers investigating desert landscapes and addressing environmental challenges related to desertification and aeolian processes.

Scientific DataVol. 12(1)
Institute of Ecology and Geography (MD), Xinjiang Institute of Ecology and Geography (CN), University of Chinese Academy of Sciences (CN), Xinjiang University (CN)
Life below water
Openalex Percentile: Top 7%
Geology and Paleoclimatology Research
3.90
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