摘要:Most of the current incoherent polarimetric decompositions employ coherent models to describe ground scattering; however, this cannot truly reflect the fact especially in natural ground surfaces. This paper proposes a highly adaptive decomposition with incoherent ground scattering models (ADIGSM). In ADIGSM, Neumann’s adaptive model is employed to describe volume scattering, and to explain cross-polarized power in remainder matrix, so that we can obtain orientation angle randomness for both volume scattering and the dominant ground scattering. The computation of volume scattering parameters is strictly constrained for non-negative eigenvalues, while the volume scattering parameters that explain the most cross-polarized power are selected. When applying ADIGSM to NASA’s UAVSAR data, the negative component powers were obtained in quite a few forest pixels. Compared with several newest decompositions, the volume scattering power is obviously lowered, especially in areas dominated by surface scattering or double bounce scattering. The orientation angle randomness of each component is reasonable as well. ADIGSM has potential to be applied in the fields such as PolSAR image classification, land cover mapping, speckle filtering, soil moisture and roughness estimation, etc.