Spatial distribution of fine-grained floodplain deposits and anthropogenic materials based on official borehole data in the floodplain of Leipzig, Germany.

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2025-01-04 eCollection Date: 2025-02-01 DOI:10.1016/j.dib.2025.111275
Nele Graubner, Johannes Schmidt
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引用次数: 0

Abstract

This data set includes the spatial model of the thickness and distribution of fine-grained floodplain deposits in the Leipzig floodplain area. The data set originates from borehole records provided by the Saxon State Office for Environment, Agriculture, and Geology [1]. The data processing involved the categorization of the stratigraphic descriptions of the borehole logs. For that, a methodology was implemented to categorize those into 6 broader classifications (sand, gravel, clay, anthropogenic sediments, fine-grained/organic sediments and others) with 33 sub-categories. Subsequently, the stratigraphic layers were analysed to determine the depth and thickness of the fine-grained floodplain deposits, as well as the distribution of anthropogenic material. The data set was filtered, with the condition that each borehole log has at least one clayey layer and a gravel layer of at least 0.7 m thickness and, later, interpolated to present a complete spatial model for the research area. The final data set is based on 3,414 data points (data collection covers the period: 1852 to 2018) within the Leipzig floodplain and offers significant resource for future interdisciplinary research into the natural and anthropogenic history of the Leipzig's floodplains, offering valuable information for more detailed analyses and more precise modelling of fine-grained floodplain deposit distribution in the Leipzig floodplain area.

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Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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