NDLI: Robust vegetation height Extraction using maximum likelihood estimation for Dual-baseline PolInSAR

Content Provider	IEEE Xplore Digital Library
Author	Wei Shunjun Zhang Xiaoling Han Di
Copyright Year	2008
Description	Author affiliation: E.E. Dept., Univ. of Electron. Sci. & Technol. of China, Chengdu (Wei Shunjun; Zhang Xiaoling; Han Di)
Abstract	Polarimetric SAR interferometry technique has been widely used for parameters extraction of the earth's surface vegetation. In this paper, based on the two layers Random Volume over Ground model, we present a vegetation height inversion algorithm for dual-baseline PolInSAR data. The method obtained the ground and volume scattering component respectively by using the theory of Freeman polarimetric decomposition. Then the maximum likelihood estimation of the covariance matrix was used to construct the vegetation height for dual-baseline PolInSAR. The proposed algorithm overcomes the restriction of traditional maximum likelihood estimation method which required the parameters of ground scattering to be known. Finally, the experimental results of L-band PolInSAR simulated data show that the algorithm improves the effect of height estimation compare to the coherence method.
File Size	243993
File Format	PDF
ISBN	9781424428076
DOI	10.1109/IGARSS.2008.4779072
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Vegetation Maximum likelihood estimation Data mining Interferometry Parameter extraction Earth Covariance matrix Scattering parameters L-band dual-baseline SAR PolInSAR vegetation height inversion
Content Type	Text
Resource Type	Article

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