Accuracy Improvement of Maximum Likelihood Inversion of Forest Heights with Polinsar Data

HEIGHTS WITH POLINSAR DATA Lulu Tan , Ruliang Yang, Weidong Yu 1 Institute of electronics, Chinese Academy of Sciences, China; 2 Graduate University of Chinese Academy of Sciences, China. Email: [email protected]; [email protected]; Polarimetric synthetic aperture radar interferometry (PolInSAR) is a perspective remote sensing technique that has been intensively used for extracting forest heights. There are many forest parameter inversion methods. Among these methods, maximum likelihood inversion method computes the maximum-likelihood estimate of the vegetation parameters based directly on the sample coherency matrix [1, 2]. Moreover, the formula for the coherency matrix of vegetated area was predicted by the model of Treuhaft and Siqueira [3], which is random volume over ground model (RVoG). It is obvious that the estimation of sample coherency matrix is of great importance in this inversion process. A coherency matrix estimation method based on the PolInSAR coherence region shapes is presented in this paper.