期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2013
卷号：6
期号：2
出版社：SERSC
摘要：Forest height is important information for many forest management activities and is a critical parameter in models of ecosystem procedures. Recently, there have been plenty of researches on the retrieval of forest height by single baseline PolInSAR such as the ESPRIT method, three-stage inversion but the methods tend to underestimate the forest height due to attenuation of the electromagnetic waves in the ground medium and vary widely in their sensitivities. This paper proposes a novel algorithm to retrieve forest height using an adaptive scattering model-based decomposition technique with PolInSAR data. The object is to describe each interferometry cross correlation as a sum of contributions corresponding to odd bounce, double bounce and volume scattering processes. This algorithm enables the retrieval not only of the vegetation parameters but also of the magnitude associated with each mechanism. Another advantage of the proposed algorithm is that it makes use of all the information provided by the covariance matrix, which remains unachieved in the previous model-based decompositions. The proposed algorithm has been tested with simulated data from PolSARProSim software and spaceborne data from a test site. Experimental results indicate that accuracy of the forest height estimation can be enhanced by the proposed algorithm.
