Volume coherence function optimization method for extracting vegetation and terrain parameters from polarimetric synthetic aperture radar interferometry images

An advanced algorithm is introduced to enhance the efficiency in measuring vegetation parameters using L-band polarimetric synthetic aperture radar interferometry data. In this method, the combination of the eigenvalue decomposition technique and the coherence matrix optimization method is to achieve higher accuracy for ground phase estimation. Then an exhaustive search method based on the optimal polarization coherence channel is developed to retrieve the forest parameters. To evaluate the effectiveness of this method, we first apply it to simulated data obtained from PolSARProSim software. Next, the experimental L-band single-baseline single-frequency polarimetric interferometric data are used to assess the applicability of the proposed method for the actual forest topography in Malaysia and Kudara, Lake Baikal, Russia. The obtained results indicate that the proposed algorithm significantly overcomes the disadvantages of the recently published methods. © 2020 Society of Photo-Optical Instrumentation Engineers (SPIE).