Correlating Spectral Properties (complex mineral samples: 350–15,375 nm, water: 337–823 nm) with Geochemistry and Mineralogy with focus on Acid Mine Drainage (AMD)

Acid mine drainage (AMD) environments host complex mineral-water systems that challenge conventional spectral libraries built for pure minerals. We present an open, harmonized dataset that integrates spectroscopy of real AMD materials with co-registered mineralogical and geochemical measurements from the Kirki (Saint Philippos) mine, NE Greece. The dataset comprises: (i) laboratory mineral reflectance spectra spanning 350–15,375 nm (Visible–Near Infrared (VNIR) – Shortwave Infrared (SWIR) – Mid-Wave Infrared (MWIR) – Longwave Infrared (LWIR) for natural, compositionally diverse complex mineral samples; (ii) in situ water VNIR spectra from 337–823 nm acquired across a gradient of acidity and turbidity; (iii) co-located field measurements (e.g. temperature, pH); and (iv) wide range of laboratory analyses for both solid and water datasets to support ground truth validation. To demonstrate utility, we relate spectral features to mineralogy and composition using partial least squares regression (PLSR). For solids, VNIR–SWIR regions best predict Fe2O3, while MWIR–LWIR features improve estimation of SiO2 and total S, highlighting diagnostic bands across iron oxides/sulfates and silicate frameworks. For waters, VNIR spectra capture acidity/turbidity-driven variability and enable example detecting gradients of dissolved trace metals. Together, these results show that realistic mixture spectra coupled to independent ground truth support quantitative inference of key AMD parameters. These free datasets can facilitate algorithm development, cross-sensor validation, and environmental assessment in AMD-impacted settings, and serves as a high-fidelity analog for planetary spectroscopy, particularly for sulfate- and Fe-oxide detection and LWIR mineral retrievals. All data products, metadata, and processing notes are openly available via the referenced repository. The associated data paper is available at: https://www.nature.com/articles/s41597-026-07307-y - citeas The MultiMiner project is funded by the European Union’s Horizon Europe research and innovations actions programme under Grant Agreement No. 101091374.酸性矿山排水（Acid Mine Drainage, AMD）环境中存在复杂的矿水耦合体系，这对专为纯矿物构建的常规光谱库带来了挑战。本研究构建了一套开放且标准化的数据集，整合了真实AMD环境样品的光谱数据，以及希腊东北部基尔基（圣菲利普斯）矿山的协同配准矿物学与地球化学测量数据。该数据集包含以下内容：(i) 针对成分多样的天然复杂矿物样品的实验室矿物反射光谱，光谱覆盖范围为350~15375 nm，涵盖可见光-近红外（Visible–Near Infrared, VNIR）、短波红外（Shortwave Infrared, SWIR）、中波红外（Mid-Wave Infrared, MWIR）与长波红外（Longwave Infrared, LWIR）全波段；(ii) 原位水体VNIR光谱，采集波长范围为337~823 nm，数据覆盖了酸度与浊度的梯度变化区间；(iii) 同步匹配的野外实地测量数据（如温度、pH值）；(iv) 针对固体与水体样品数据集的多类实验室分析结果，用于支撑真值验证工作。为验证该数据集的应用潜力，本研究采用偏最小二乘回归（Partial Least Squares Regression, PLSR）方法，建立光谱特征与矿物组成及元素组分的关联模型。针对固体样品，VNIR-SWIR波段区域可最优估算三氧化二铁（Fe₂O₃）含量，而MWIR-LWIR波段特征则提升了二氧化硅（SiO₂）与总硫的估算精度，这凸显了铁氧化物/硫酸盐及硅酸盐骨架的诊断光谱波段。针对水体样品，VNIR光谱可捕捉酸度与浊度驱动的光谱变化，并可实现对溶解态痕量金属梯度分布的示例性检测。综合上述结果可知，真实混合矿物光谱结合独立真值数据，可实现对关键AMD环境参数的定量反演。这套开放免费的数据集可助力AMD受影响区域的算法开发、跨传感器验证与环境评估工作，同时可作为行星光谱学的高保真类比数据集，尤其适用于硫酸盐与铁氧化物的识别以及LWIR波段矿物反演。所有数据产品、元数据与处理说明均可通过文末引用的开源仓库获取。 相关数据论文可通过以下链接获取：https://www.nature.com/articles/s41597-026-07307-y，请按此格式引用： MultiMiner项目由欧盟“地平线欧洲”研究与创新行动计划资助，资助协议编号为101091374。