Abstract
This study investigates a two component decomposition technique for HH/VV-polarized PolSAR (Polarimetric Synthetic Aperture Radar) data. The approach is a straight forward adaption of the Yamaguchi decomposition and decomposes the data into two scattering contributions: surface and double bounce under the assumption of a negligible vegetation scattering component in Tundra environments. The dependencies between the features of this two and the classical three component Yamaguchi decomposition were investigated for Radarsat-2 (quad) and TerraSAR-X (HH/VV) data for the Mackenzie Delta Region, Canada. In situ data on land cover were used to derive the scattering characteristics and to analyze the correlation among the PolSAR features. The double bounce and surface scattering features of the two and three component scattering model (derived from pseudo-HH/VV- and quad-polarized data) showed similar scattering characteristics and positively correlated-R2 values of 0.60 (double bounce) and 0.88 (surface scattering) were observed. The presence of volume scattering led to differences between the features and these were minimized for land cover classes of low vegetation height that showed little volume scattering contribution. In terms of separability, the quad-polarized Radarsat-2 data offered the best separation of the examined tundra land cover types and will be best suited for the classification. This is anticipated as it represents the largest feature space of all tested ones. However; the classes “wetland” and “bare ground” showed clear positions in the feature spaces of the C- and X-Band HH/VV-polarized data and an accurate classification of these land cover types is promising. Among the possible dual-polarization modes of Radarsat-2 the HH/VV was found to be the favorable mode for the characterization of the aforementioned tundra land cover classes due to the coherent acquisition and the preserved co-pol. phase. Contrary, HH/HV-polarized and VV/VH-polarized data were found to be best suited for the characterization of mixed and shrub dominated tundra.
Highlights
The decomposition of Polarimetric Synthetic Aperture Radar (PolSAR) data is an important analysis step to characterize different types of backscatter and to derive higher level products for earth observation
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Comparing the features of quad- and HH/VV-polarized data, it can be noted that the characteristics of power components of surface (Ps) and Pd of the two and three component decomposition were very similar
Summary
The decomposition of Polarimetric Synthetic Aperture Radar (PolSAR) data is an important analysis step to characterize different types of backscatter and to derive higher level (beyond level 2.0) products for earth observation. During the last decades much attention was paid to the decomposition of quad-polarized Synthetic Aperture Radar (SAR) data [1,2,3,4,5] and on the utilization of compact polarimetric systems (exemplarily: [6,7]). There are fewer concepts on the decomposition of dual-polarized data [8,9,10] This type of PolSAR data advances higher spatial resolution and larger area coverage compared to the quad-polarized mode. Co-polarimetric phase as well as amplitude information of the complex SAR measurement is available for the analysis This kind of data allows investigating the polarimetric phase-relation between the HH and VV channels. This information is known to be an important discriminator for the characterization of surface and double bounce scattering, respectively of odd and even bounce [1,5]
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