Typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge

The invention discloses a typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge, and the method comprises the steps: obtaining multi-dimensional remote sensing big data, and carrying out the data processing of the multi-dimensional remote sensing big data, and obtaining an analysis result; performing spatial data mining of element levels according to an analysis result, and extracting typical resource element attribute features; performing interpretation according to the typical resource element attribute features and a preset knowledge-driven model to obtain a typical resource element classification result, and processing the typical resource element classification result into vector pattern spot data; and comparing the vector pattern spot data with preset annual land change survey data to obtain a classification area accuracy index and an interpretation pattern spot accuracy index. The method can effectively extract remote sensing information in a