A Fully Polarimetric Characterization of the Impact of Precipitation on Short Wavelength Synthetic Aperture Radar

Fritz, Jason; Chandrasekar, V.

doi:10.1109/tgrs.2011.2170576

Cited by 16 publications

(7 citation statements)

References 30 publications

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“…The propagation delay caused by rainfall along a propagation path affects the polarimetric data [20], [21]. Rainfall causes a polarization-dependent phase shift through the propagation in the medium, which leads to the co-polarization phase difference (CPD).…”

Section: Influence Of Rainfall In Temp H / Temp  Decompositionmentioning

confidence: 99%

Temporal H/alpha Target Decomposition for Landslide Monitoring Using Ku-Band GB-SAR Time Series

Izumi

Suzuki

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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We investigate the applicability of the entropy (H)/ alpha () target decomposition realized by the temporally averaged coherency matrix, called temporal H/ . We apply the temporal H/  to ground-based synthetic aperture radar (GB-SAR) continuous monitoring data to characterize the scattering mechanism temporal change. As a case study, this work demonstrates the application of the temporal H/  technique to landslide monitoring to detect and investigate the temporal scattering mechanism. The study acquired long-term GB-SAR polarimetric data over the post-landslide slope, Minami-Aso, Kumamoto, Japan. The study first investigated the property of the temporal H/  parameters over selected land cover types by comparing it with that derived by spatial averaging (spatial H/ ) to explain the landslide monitoring results. Also, the rainfall effects on the temporal H/  parameters are demonstrated. The temporal H and  values increase up to 0.07 and 13.54°, respectively, when the rainfall rate is 52.5 mm/h. The time-series analysis of the temporal H/  indicates an obvious temporal transition of the scattering mechanism and a change of the backscattering stationarity when a landslide occurs. The applicability of the temporal H/  for the change-detection is discussed by comparing it with the classical spatial H/  parameters.

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Section: Influence Of Rainfall In Temp H / Temp  Decompositionmentioning

confidence: 99%

Temporal H/alpha Target Decomposition for Landslide Monitoring Using Ku-Band GB-SAR Time Series

Izumi

Suzuki

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…L(Á) is a functional term accounting for the two-way path attenuation and f(Á), f'(Á), f"(Á) are complex functions of the surface and volume scattering matrix elements, depending respectively on ground target, SAR received signal and atmospheric volume. Note that in the literature, the computation of δ co (x,y) is simplified as it is assumed equal to δ co ¼ arg(ρ co ) of the scattering cell in position x,y (Marzano et al 2012), or ignored as in Fritz and Chandrasekar (2012). Marzano et al (2012) suggest a significant correlation between the SAR NRCS and the slant-integrated water contents.…”

Section: Sar Observing Geometry and Response Modelmentioning

confidence: 99%

“…Obtainable polarimetric products include the differential reflectivity, and the differential phase, simulated at both X band and Ku band. Baldini et al (2014) have carried out a review of the model of Fritz and Chandrasekar (2012) adding formulas for simulating X-band SAR observables from ground weather radar reflectivity at C and S band. An analysis of the CSK Ping-Pong mode (alternate HH-VV) was also carried out, showing some interesting features.…”

Section: Introductionmentioning

confidence: 99%

X-Band Synthetic Aperture Radar Methods

Mori

Marzano

Pierdicca

2020

Advances in Global Change Research

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Spaceborne Synthetic Aperture Radars (SARs), operating at L-band and above, offer microwave observations of the Earth at very high spatial resolution in almost all-weather conditions. Nevertheless, precipitating clouds can significantly affect the signal backscattered from the ground surface in both amplitude and phase, especially at X band and beyond. This evidence has been assessed by numerous recent efforts analyzing data collected by COSMO-SkyMed (CSK) and TerraSAR-X (TSX) missions at X band. This sensitivity can be exploited to detect and quantify precipitations from SARs at the spatial resolution of a few hundred meters, a very appealing feature considering the current resolution of precipitation products from space. Forward models of SAR response in the presence of precipitation have been developed for analyzing SAR signature sensitivity and developing rainfall retrieval algorithms. Precipitation retrieval algorithms from SARs have also been proposed on a semi-empirical basis. This chapter will review experimental evidences, modelling approaches, retrieval methods and recent applications of X-band SAR data to rainfall estimation.

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“…Microphysical and electromagnetic models describing radar interaction with volumes of the various hydrometeor types then provide the relationships necessary to calculate measurements of this storm from a radar with a different frequency and observation look angle considering non-spherical precipitation particles using regression theory. Details of all the parameters defining the various hydrometeor types are given in [2]. Simple linear or power law models from least squares regression are capable of handling most particles, but a nonlinear mapping is required for the scaling of hail measurements to higher frequencies due to oscillations of the radar cross section (RCS) as the particle size approaches and exceeds the radar wavelength.…”

Section: Introductionmentioning

confidence: 99%

“…Together with the hydrometeor classification output described above, the model projects the expected propagation and backscatter effects of the storm onto the SAR reference plane. In summary, the steps as detailed in [2] are 1) estimate specific differential phase (K dp ) from the ground radar data, 2) correct for attenuation (for X or C bands) using an algorithm based on the K dp [6] 3) resample and filter to a Cartesian grid, 4) classify the hydrometeors, 5) scale to the frequency and look angle of the SAR, 6) resample to the SAR coordinate system and 7) integrate through the volume to project the impact to the surface.…”

Section: Introductionmentioning

confidence: 99%

Validation of a dual-polarization SAR storm observation model

Fritz

Chandrasekar

Baldini

2011

2011 IEEE RadarCon (RADAR)

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Within the past few years, several X-band Synthetic Aperture Radar (SAR) satellites have been launched and more are planned. While the primary SAR application is surface monitoring, and they are heralded as "all weather" systems, strong precipitation induces significant propagation and backscatter effects in the data even at frequencies near C-band. Characterization of propagation effects and viewing geometry are developed to gain knowledge on exactly how precipitation impacts SAR imagery. This is accomplished by simulating storms in SAR data starting from real measurements of a storm by groundbased polarimetric radar. In addition, real storm observations by current SAR platforms are also quantitatively analyzed by comparison to theoretical results using simultaneous acquisitions by ground radars. Using simultaneous observations by the Italian Space Agency (ASI) COSMO-SkyMed X-band SAR and a Cband polarimetric weather radar operated by Arpa Piemonte on June 29, 2010 the model can be validated and analyzed.

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A Fully Polarimetric Characterization of the Impact of Precipitation on Short Wavelength Synthetic Aperture Radar

Cited by 16 publications

References 30 publications

Temporal H/alpha Target Decomposition for Landslide Monitoring Using Ku-Band GB-SAR Time Series

Temporal H/alpha Target Decomposition for Landslide Monitoring Using Ku-Band GB-SAR Time Series

X-Band Synthetic Aperture Radar Methods

Validation of a dual-polarization SAR storm observation model

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