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.