Using airborne hyperspectral data to characterize the surface pH of pyrite mine tailings

Natalie Zabcic, B. Rivard, C. Ong, A. Müller
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引用次数: 14

Abstract

High spatial-resolution Hymap airborne hyperspectral data was used to generate predictive pH maps of acid mine drainage (AMD) for the Sotiel-Migollas mine complex, Southwest Spain. These maps portray the spatial distribution of highly acidic areas, which are likely associated with high concentrations of heavy metals. A predictive pH model was built using partial least squares (PLS) analysis to determine the relationship between the spectral response of AMD samples and their leachate pH measured in the laboratory. A validation of the model for an independent data set shows a r2 of 0.71 between actual and predicted pH values. Hyperspectral imagery is shown to provide an effective means to quantitatively pinpoint sources of acidity.
利用航空高光谱数据对黄铁矿尾矿表面pH值进行表征
利用高空间分辨率Hymap航空高光谱数据为西班牙西南部Sotiel-Migollas矿区酸性矿井水(AMD)生成预测pH图。这些地图描绘了高酸性地区的空间分布,这可能与高浓度的重金属有关。采用偏最小二乘法(PLS)建立预测pH模型,确定AMD样品的光谱响应与其实验室测量的渗滤液pH之间的关系。对独立数据集的模型验证表明,实际pH值与预测pH值之间的r2为0.71。研究表明,高光谱图像提供了一种有效的方法来定量地确定酸度的来源。
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