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

机译:使用空气传播的高光谱数据来表征黄铁矿矿井尾矿的表面pH值

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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.
机译:高空间分辨率的Hymap空气传播的高光谱数据用于生成西南西南部Sotiel-Migollas Comper Complex的酸性矿山排水(AMD)的预测pH图。这些地图描绘了高度酸性区域的空间分布,这可能与高浓度的重金属相关。使用局部最小二乘(PLS)分析建立预测的pH模型,以确定AMD样品的光谱响应与实验室中测量的渗滤液pH之间的关系。独立数据集的模型的验证在实际和预测的pH值之间显示了0.71的R 2 。显示高光谱图像以提供有效的方法,以定量定量酸度的源。

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