流域尺度土壤特性及其中红外光谱数据集

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Alexandre M.J.-C. Wadoux , Felix Stumpf , Thomas Scholten
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引用次数: 0

摘要

该数据集提供了中国湖北省巴东上游流域(31°1′24”N, 110°20′35”E) 4.2 km2流域土壤性质及其相关的中红外光谱信息。收集了由林地、农田和小型农场建筑组成的高度多样化的梯田集水区的表土数据。该数据集包含的土壤属性包括pH值、质地(即粘土、淤泥和砂含量)、总碳、有机碳和CaCO3。此外,对土壤样品进行了中红外扫描。数据收集涉及2013年和2014年期间的三次实地活动,在所有地点以标准化的方式收集表土样本,并按照标准程序在土壤科学实验室进行土壤分析。该数据集提供了对中国中部高度多样化流域土壤性质空间变化的见解。对土壤研究感兴趣的研究人员可以将该数据集用于各种目的,包括建立数字土壤制图模型或土壤光谱模型,与其他数据集对模型进行基准测试,以及土壤侵蚀建模研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A catchment-scale dataset of soil properties and their mid-infrared spectra
The dataset presents information on soil properties and their associated mid-infrared spectra for a drainage basin of 4.2 km2, referred to as Upper Badong catchment (31°1′24′′N, 110°20′35′′E) in the Hubei province, China. Data were collected for topsoil in a highly diverse terrace catchment composed of woodland, cropland and small farm building. Soil properties included in this dataset are pH, texture (i.e. clay, silt and sand content), total carbon, organic carbon and CaCO3. In addition, the soil samples were scanned in the mid-infrared range. The data collection processed involved three field campaigns during 2013 and 2014 where topsoil samples were collected in a standardized way across all sites, and soil analyses in the laboratory of soil science following standard procedures. The dataset offers insights into the spatial variation of soil properties in a highly diverse catchment of central China. Researchers interested in soil research can use this dataset for various purposes, including building digital soil mapping models or soil spectroscopic models, benchmarking of models with other datasets, and research in soil erosion modelling.
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来源期刊
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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