The invention relates to a method for extracting topographical spatial information based on a generalized self-similarity principle, which comprises: transforming the topographical spatial information into an energy spectral density space by Fourier transformation; eliminating the influence of boundary effect generated by the topographical data boundary part; drawing a double logarithmic scatter graph formed by the energy spectral density value (S) and the area (A) included by the isometric line of the energy spectral density value (S), and detecting the fractal rules of the energy spectral density and the area; determining the number and the interval of generalized self-similarity relations; determining the threshold and a corresponding fractal filter; and transforming filtered energy spectrum information back to a spatial domain by inverse Fourier transformation, and achieving the aims of decomposing anomaly and ambient fields and extracting interested topographical spatial information. The method has the advantages of wide practicality, high extraction precision and the like, and is suitable for topographical data such as geological data, mineral data, geochemical data, geophysical data, remote sensing data and the like, and the operations of topographical information extraction and topographical data mining such as mineral exploration, resource assessment, environmental pollution assessment, natural disaster analysis, marine vortex extraction and the like.