Stokes matrix statistics in sea ice polarimetric SAR images
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A new technique for calibration of multipolarization synthetic aperture radar (SAR) imagery is described. If scatterer reciprocity and lack of correlation between co- and cross-polarized radar echoes (for azimuthally symmetric distributed targets) is assumed, the effects of signal leakage between the radar data channels can be removed without the use of known ground targets. If known targets are available, all data channels may be calibrated relative to one another and radiometrically as well. The method is verified with simulations and application to airborne SAR data.
Multispectral radar polarimeter data were collected over the Manix Basin Area of the Mojave desert using an airborne SAR. An analysis of the data reveals unusual polarization responses which are attributed to the formation of wind ripples on the surfaces of fields that have been abandoned for more than 5 years. This hypothesis has been confirmed through field observations, and a second-order perturbation model is shown to effectively model the polarization responses. The results demonstrate the usefulness of remote sensing techniques for the study of land degradation at synoptic scales.
Relative phase calibration of radar polarimetry data may be achieved by utilizing the phase information of the receiver calibration tone and knowledge of the antenna path differences among channels measured upon installation of the radar polarimeter. This calibration method does not require any assumptions on the scattering behavior of the scene. This method of phase calibration may be verified by examining the polarization signatures of calibration instruments such as the trihedral corner reflectors.
Radar backscatter from abandoned circular alfalfa fields in the Manix Basin area of the Mojave desert shows systematic changes with length of abandonment. The obliteration of circular planting rows by surface processes could account for the disappearance of bright spokes, which seem to be reflection patterns from remnants of the planting rows, with increasing length of abandonment. An observed shift in the location of the maximum L-band copolarization return away from VV, as well as an increase in surface roughness, both occurring with increasing age of abandonment, seems to be attributable to the formation of wind ripples on the relatively vegetationless fields.
Mapping of floodplain inundation patterns is a key element in developing hydrological and biogeochemical models for large tropical river basins such as the Amazon. Knowledge of the time sequence of inundation is necessary to determine both water routing and biogenic gas fluxes. Synthetic Aperture Radar (SAR) is uniquely suited for this application because of its ability to penetrate cloud cover and, in many cases, to detect flooding beneath a forest or herbaceous canopy. A procedure for discriminating flooded forest, flooded herbaceous vegetation, and open water from other cover types for a coastal wetland site on the lower Altamaha floodplain, Georgia, emphasizing robust classifiers that are not site-specific is currently being developed.
Results of ongoing efforts to develop an algorithm for soil moisture retrieval from Synthetic Aperture Radar (SAR) imagery are reported. Estimates of soil moisture are of great importance in numerous environmental studies, including hydrology, meteorology, and agriculture. Previous studies using extensive scatterometer measurements have established the optimum parameters for moisture retrieval as C-band HH radar operating at incidence angles between 10 to 15 deg. However, these parameters were not tested or verified with imaging radar systems. The results from different investigators showed considerable variability in the relationship between soil moisture and radar backscattering. This variability suggests that those algorithms are site-specific. Furthermore, the small incidence angle requirement limits the spatial application, especially for airborne radar systems.
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TanDEM-X (TDX) enables to generate an interferometric coherence without temporal decorrelation effect that is the most critical factor for a successful Pol-InSAR inversion, as have recently been used for forest parameter retrieval. This paper presents mangrove forest height estimation only using single-pass/single-baseline/dual-polarization TDX data by means of new dual-Pol-InSAR inversion technique. To overcome a lack of one polarization in a conventional Pol- InSAR inversion (i.e. an underdetermined problem), the ground phase in the Pol-InSAR model is directly estimated from TDX interferograms assuming flat underlying topography in mangrove forest. The inversion result is validated against lidar measurement data (NASA's G-LiHT data).
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