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Eigen decomposition parameter based forest mapping using Radarsat-2 PolSAR data | IEEE Conference Publication | IEEE Xplore

Eigen decomposition parameter based forest mapping using Radarsat-2 PolSAR data


Abstract:

In this paper, a set of polarimetric eigenvalue and eigenvector based parameters, e.g. entropy and anisotropy, are investigated for forest application. The correlation te...Show More

Abstract:

In this paper, a set of polarimetric eigenvalue and eigenvector based parameters, e.g. entropy and anisotropy, are investigated for forest application. The correlation terms of the eigenvectors, μ1 and μ2, are found to be better for forest mapping in both summer and winter using Radarsat-2 quad-polarimetric space borne SAR data. These are used to automatically identify forest class pixels from the volume scattering category of a Freeman-Durden Wishart unsupervised segmentation map. The algorithm scheme was developed and implemented using fully polarimetric Radarsat-2 SAR (PolSAR) data acquired in July and October and the validity was evaluated using the ground reference data created from SPOT5 K-clustering classification map.
Date of Conference: 25-30 July 2010
Date Added to IEEE Xplore: 03 December 2010
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Conference Location: Honolulu, HI, USA

References

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