Abstract: A remote sensing classification method based on relative entropy includes: determining sample points of n types of ground objects in a study area and determining series remote sensing parameters; extracting, based on the sample points, remote sensing parameter values to form standard time series plots as a first distribution; taking remote sensing parameter values of to-be-classified pixels as a second distribution, determining, based on the second distribution and the first distribution, KL values of the to-be-classified pixels by using a KL-divergence formula, then obtaining n KL layers; and comparing n KL values of each to-be-classified pixel to classify it to be a type of ground objects with a minimum KL value.