Aiming at the deficiency of the H-Alpha based classification

a new scheme of unsupervised terrain classification is proposed based on target scattering similarities.This new scheme divides terrain scattering into three classes with target scattering randomness firstly;and then subdivides these three classes with target scattering similarities ulteriorly.As terrain scattering class is determined by target scattering similarities automatically

the deficiency of the arbitrarily fixed linear decision boundaries of Alpha angle is overcomed.As an application

a new method of unsupervised terrain classification is also presented under the frame of the new scheme.After the partition of terrain scattering with target entropy which is a measure of target scattering randomness

the new method subdivides three classes into ten classes with surface scattering similarity

double scattering similarity and volume scattering similarity ulteriorly.As surface scattering

double scattering and volume scattering are the inherent characteristics of terrain physical scattering mechanisms

the classification result of the new method is consistent with the real terrain scattering.With the real polarimetric data of San Francisco

the feasibility of the new scheme and the validity of the new method are validated.