A comprehensive grain-size database of surface sediments from the Taklamakan Desert
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,...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04936-7 |
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| Summary: | 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. |
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| ISSN: | 2052-4463 |