The unique contributions of this thesis are: 1) a polarimetric classification algorithm that is a significant improvement over an existing algorithm and 2) introduction of a cube technique to retrieve soil moisture under vegetation.
The most widely used classification algorithm is the three-component scattering technique. Even though it includes three dominant scattering mechanisms, the decomposition approach can cause a non-physical solution due to incorrect assumptions. The Adaptive Non Negative Eigenvalue Decomposition approach in this thesis produces correct solution. It appears that this new approach provides better classification results. It is a significant improvement over the existing technique.
A cube technique is introduced to retrieve soil moisture under vegetation. Using this approach, we have evaluated the retrieval accuracy of several polarimetric combinations. The effects of the incorrect vegetation model and data noise were investigated. In addition, the proposed cube algorithm can be improved by applying the classification result.</p
