Geotechnical and hyperspectral dataset for gold tailings

This dataset contains hyperspectral and geotechnical data collected from 300 artificially prepared gold tailings samples. The test specimens were prepared in petri dishes under controlled laboratory conditions with unique particle size distributions, moisture conditions, and densities. The geotechnical parameters of each test specimen were measured using applicable ASTM standard methods or calculated, and include percent sand, percent silt, percent clay, fines content, solids content, gravimetric moisture content, volumetric moisture content, degree of saturation, void ratio, porosity, total density, and dry density. Hyperspectral data were obtained using an ASD TerraSpec Halo spectrometer, which measures reflectance across a wavelength range of 350 to 2500 nm. The spectrometer includes three hyperspectral detector arrays, including a visible and near-infrared (VNIR) detector with a resolution of 3 nm, a short-wave infrared (SWIR) detector with a resolution of 9.8 nm, and a second SWIR ..., For a full description of the methodology used to collect these data, please refer to the associated publication titled Ex Situ Hyperspectral Sensing and Machine Learning for Tailings Characterization (https://doi.org/10.1139/cgj-2024-0656).  , , # Geotechnical and hyperspectral dataset for gold tailings [https://doi.org/10.5061/dryad.v15dv4278](https://doi.org/10.5061/dryad.v15dv4278) ## Description of the data and file structure The dataset (Tailings-Hyperspectral-Dataset-Bindner_et_al.2024.csv) contains hyperspectral and geotechnical data collected from 300 artificially prepared gold tailings samples. ### Files and variables #### **File: Tailings-Hyperspectral-Dataset-Bindner_et_al.2024.csv** **Description:** Dataset containing geotechnical and optical parameters for gold tailings. **Variables** * Sample_ID: This field ranges from 1-300. Each is associated with a unique combination of particle size distribution, moisture, and density. * PSD_ID: This field ranges from 1-100 and describes the particle size distribution sample that each test specimen (or Sample_ID) was prepared from. * Sand (%): This describes the mass fraction percent sand (g/g) in percent. Sand is defined as particles greater than 75 µm. Percent sand...,本数据集包含从300份人工制备的金尾矿样品中采集的高光谱（hyperspectral）与岩土工程（geotechnical）数据。试验样品均在可控实验室条件下于培养皿中制备，具备独特的粒径分布、含水率状态与密度。每份试验样品的岩土工程参数均采用符合ASTM（美国材料与试验协会）标准的方法测试或计算得到，涵盖砂粒百分含量、粉粒百分含量、黏粒百分含量、细粒含量、固体含量、重量含水率、体积含水率、饱和度、孔隙比、孔隙率、总密度与干密度。高光谱数据通过ASD TerraSpec Halo光谱仪采集，该设备可测量350~2500 nm波长范围内的反射率。光谱仪包含三套高光谱探测器阵列：分别为分辨率3 nm的可见光近红外（VNIR）探测器、分辨率9.8 nm的短波红外（SWIR）探测器，以及第二台短波红外（SWIR）探测器……如需完整了解本数据集的采集方法，请参阅相关学术出版物《尾矿表征的异位高光谱传感与机器学习（Ex Situ Hyperspectral Sensing and Machine Learning for Tailings Characterization）》（https://doi.org/10.1139/cgj-2024-0656）。 # 金尾矿岩土工程与高光谱数据集 [https://doi.org/10.5061/dryad.v15dv4278](https://doi.org/10.5061/dryad.v15dv4278) ## 数据与文件结构说明 本数据集（文件名为Tailings-Hyperspectral-Dataset-Bindner_et_al.2024.csv）包含从300份人工制备的金尾矿样品中采集的高光谱与岩土工程数据。 ### 文件与变量 #### **文件：Tailings-Hyperspectral-Dataset-Bindner_et_al.2024.csv** **【说明】**：包含金尾矿岩土工程与光学参数的数据集。 **变量说明** * Sample_ID：取值范围为1~300，每个编号对应唯一的粒径分布、含水率与密度组合。 * PSD_ID：取值范围为1~100，用于标识每份试验样品（即Sample_ID）所对应的原粒径分布样品。 * 砂粒百分含量（%）：以百分比表示的砂粒质量占比（g/g），其中砂粒定义为粒径大于75 μm的颗粒。砂粒百分含量……