基于岩石光谱吸收特征的白云母含量反演

岩石是由多种矿物组成,其反射率光谱吸收特征与矿物含量之间存在紧密联系,矿物光谱在特定波段处的光谱吸收特征是定量估算含量的重要指标之一。为提升岩石光谱吸收特征定量反演矿物含量的准确度与精度,以白云母为研究对象,分析岩石光谱在2.2 μm附近的光谱吸收特征及其白云母含量,采用Savitzky-Golay平滑滤波和连续统去除法对岩石光谱反射率进行处理,进而提取光谱吸收特征参数（吸收深度、吸收宽度、吸收面积）,分析岩石光谱在2.2 μm附近吸收特征与白云母含量之间的相关性。研究中采用单一吸收特征建立统计模型、多维吸收特征建立偏最小二乘法（PLS）和多层感知器（MLP）模型,对岩石中白云母含量与光谱吸收特征参数进行分析,进而提出一种非线性预测岩石中矿物含量的方法。研究结果表明,岩石光谱在2.2 μm附近的光谱吸收特征中,吸收深度与白云母含量之间的相关性最高。基于单一吸收特征的统计模型中,二次曲线模型对吸收深度拟合的效果最佳,R2为0.935 0,RMSE为0.063 0,岩石光谱的吸收深度随白云母丰度满足二次曲线变化,岩石中白云母的含量越高,岩石光谱吸收深度值越大;基于多维光谱吸收特征的PLS模型相较于MLP模型拟合的效果更佳,其R2为0.947 7高于MLP的0.901 2,RMSE为0.002 7低于MLP的0.005 1;整体上,多维模型优于单一维度模型,PLS模型反演能力最佳,该模型在预测白云母含量上具有运算量小、精度高的特点。通过分析岩石在诊断特征处的光谱吸收特征,为其矿物组分的含量等进行定量反演提供理论参考,为矿产资源监测与评估提供快速高效便捷的方法。

The Inversion of Muscovite Content Based on Spectral Absorption Characteristics of Rocks

Rock is composed of various minerals, and there is a close relationship between the reflectance spectral absorption characteristics and mineral content. The spectral absorption characteristics of mineral spectra at specific bands are one of the important indicators for the quantitative estimation of content. This paper takes muscovite as the research object, analysing the rock spectrum’s spectral absorption characteristics near 2.2 μm and muscovite content. Moreover, uses Savitzky-Golay smoothing filter and Continuum Removal method to process the spectral reflectance of rock, and then extracts the spectral absorption characteristic parameters (absorption depth D, absorption width W, absorption area A ), and analyzes the correlation between the absorption characteristics of rock spectrum near 2.2 μm and muscovite content. In this paper, the statistical model was established by a single absorption feature, and the Partial Least Squares (PLS) and Multilayer Perceptron (MLP) models were established by multi-dimensional absorption feature. The muscovite content and spectral absorption characteristic parameters in rocks were analyzed, and a non-linear representation method for predicting mineral content in rocks was proposed. The results show that the spectral absorption characteristics of rock spectrum near 2.2 μm, the correlation between absorption depth and muscovite content among the highest. In the statistical model based on single absorption characteristics, the quadratic curve model has the best fitting effect on the absorption depth. R2 is 0.935 0, RMSE is 0.063 0. The absorption depth of the rock spectrum changes with the abundance of muscovite. The higher the muscovite content in rock, the greater the value of rock spectral absorption depth. The PLS model based on multidimensional spectral absorption characteristics was more effective than the MLP model. The R2 was 0.947 7 higher than 0.901 2 for MLP, and the RMSE was 0.002 7 lower than 0.005 1 for MLP. On the whole, the multidimensional model is better than the single-dimension model, and the PLS model has the best inversion ability. The model has the characteristics of a small amount of calculation and high precision in predicting muscovite content. Analyzing the spectral absorption characteristics of rocks at the diagnostic characteristics provides a theoretical reference for the quantitative inversion of the content of mineral components. It provides a fast, efficient, and convenient method for the monitoring and evaluating mineral resources.