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With the continuous exploitation and utilization of mineral resources, the mineral reserves of all countries in the world are decreasing. In this case, the boundary grades and industrial grades of ore are bound to be adjusted downward along with the decrease of mineral resources. Low-grade ore will have mining value and bring economic benefits to enterprises. For low-grade ore, the traditional content determination has the disadvantages of high cost and long time consumption. Therefore, it needs a method that can quickly identify the content of low-grade ore. In addition, mining will destroy the surrounding ecological environment and cause heavy metals in the land to exceed the standard. This paper proposes a method of using spectral information and remote sensing data to determine copper content in mining areas. We trained the calibration model with spectral data as input, and the copper content of the ore as output. Finally, through the remote sensing information of the mining area, the metal content of the entire mining area is inverted. This provides guidance for the later beneficiation technology of ore, and the reclamation of the land after mining. [ABSTRACT FROM AUTHOR]