为了探索应用遥感方法进行Cu元素地球化学异常研究的可行性, 基于岩石样本的反射光谱及化学元素含量数据, 分析了Cu与其他元素及Cu与反射光谱之间的相关关系, 发现Fe与Cu关系最为密切, 其次为Ti和As; Cu含量与反射光谱呈负相关性, 且Cu含量越高, 相关性越强。 基于反射光谱对Cu, Fe, Ti, As四种元素进行了偏最小二乘分析, 其中Ti建模精度最高, 其次为Fe, 精度最差的是As, 虽然 Cu的建模精度不高, 但是可以基于Fe与Cu的强相关性, 通过Fe来建立Cu异常的间接模型。 为了提高建模精度, 对反射光谱进行了多种变换, 基于获得的多种光谱指标对Fe元素进行了偏最小二乘回归分析, 训练样本及验证样本回归模型的最高相关系数分别达0.687 6和0.595 9。

In order to explore the feasibility of studying the geochemical anomaly of copper element by using remote sensing method, the correlation between Cu and other elements and the correlation between Cu and reflectance spectra were analyzed based on the element contents and the reflectance spectra of rock samples. It was found that Fe is most highly correlated with Cu, followed by Ti and As. The relationship between the Cu content and the reflectance spectra is of a negative correlation, and the higher the Cu content, the stronger the correlation. Furthermore, based on the reflectance spectra, the partial least squares regression of the Cu, Fe, Ti and As content was carried out respectively. The result shows that Ti gets the highest accuracy, followed by Fe. The worst is for As. Although the accuracy of the Cu model is not too high, it is feasible to establish an indirect model of copper anomaly on the basis of Fe model because of the strong correlation between them. In order to improve the accuracy of the model, some transformations for the reflectance spectra were performed and many spectral indices were acquired. Based on the spectral indices, the partial least squares regression of Fe was carried out. The accuracy of the regression model increased greatly. The highest correlation coefficient of the regression model is 0.687 6 for the calibration samples and it is 0.595 9 for the validation samples.