Symmetry properties in polarimetric remote sensing

Nghiem, S. V.; Yueh, Simon; Kwok, R.; Li, F. K.

doi:10.1029/92rs01230

Cited by 209 publications

(147 citation statements)

References 9 publications

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“…However, linear fullpolarimetric data showed better overall classification accuracy (92.4%) than circular full-polarimetric data (89.7%). This can be explained through azimuthal symmetric conditions for natural targets [17]. Vegetation and other natural features are considered to be azimuthally symmetric but certain fields may exhibit azimuthally asymmetric polarimetric behaviour due to orientation of row crops along the radar line of sight, tillage patterns, lodging (by strong winds) or harvesting patterns [2,8].…”

Section: Comparison Of Crop Classification Using Different Modes Of Smentioning

confidence: 99%

Assessment of L-Band Sar Data at Different Polarization Combinations for Crop and Other Landuse Classification

Haldar¹,

Das²,

Mohan³

et al. 2012

PIER B

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Abstract-In the present study evaluation of L-band SAR data at different polarization combinations in linear, circular as well as hybrid polarimetric imaging modes for crop and other landuse classifications has been carried out. Full-polarimetric radar data contains all the scattering information for any arbitrary polarization state, hence data of any combination of transmit and receive polarizations can be synthesized, mathematically from full-polarimetric data. Circular and various modes of hybrid polarimetric data (where the transmitter polarization is either circular or orientated at 45 • , called π/4 and the receivers are at horizontal and vertical polarizations with respect to the radar line of sight) were synthesized (simulated) from ALOS-PALSAR fullpolarimetric data of 14th December 2008 over central state farm central latitude and longitude 29 • 15 N/75 • 43 E and bounds for northwest corner is 29 • 24 N/75 • 37 E and southeast corner is 29 • 07 N/75 • 48 E in Hisar, Haryana (India) Supervised classification was conducted for crops and few other landuse classes based on ground truth measurements using maximum-likelihood distance measures derived from the complex Wishart distribution of SAR data at various polarization combinations. It has been observed that linear fullpolarimetric data showed maximum classification accuracy (92%) followed by circular-full (89%) and circular-dual polarimetric data (87%), which was followed by hybrid polarimetric data (73-75%) and then linear dual polarimetric data (63-71%). Among the linear dual polarimetric data, co-polarization complex data showed better classification accuracy than the cross-polarization data. Also multidate single polarization SAR data over central state farm during rabi (winter) season was analyzed and it was observed that single date fullpolarimetric SAR data produced equally good classification result as the multi-date single polarization SAR data.

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Section: Comparison Of Crop Classification Using Different Modes Of Smentioning

confidence: 99%

Assessment of L-Band Sar Data at Different Polarization Combinations for Crop and Other Landuse Classification

Haldar¹,

Das²,

Mohan³

et al. 2012

PIER B

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show abstract

“…The difference between the reflection symmetry and non-reflection symmetry targets can be described by the product of the cross-polarization and co-polarization component in the Sinclair matrix, i.e., <S HH S HV *> and <S HV *S VV > [39]. In terms of the reflection symmetry target, the product is nearly zero.…”

Section: Distinguish the Reflection Symmetrymentioning

confidence: 99%

Estimation of Paddy Rice Variables with a Modified Water Cloud Model and Improved Polarimetric Decomposition Using Multi-Temporal RADARSAT-2 Images

Yang

Shao

et al. 2016

Remote Sensing

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Rice growth monitoring is very important as rice is one of the staple crops of the world. Rice variables as quantitative indicators of rice growth are critical for farming management and yield estimation, and synthetic aperture radar (SAR) has great advantages for monitoring rice variables due to its all-weather observation capability. In this study, eight temporal RADARSAT-2 full-polarimetric SAR images were acquired during rice growth cycle and a modified water cloud model (MWCM) was proposed, in which the heterogeneity of the rice canopy in the horizontal direction and its phenological changes were considered when the double-bounce scattering between the rice canopy and the underlying surface was firstly considered as well. Then, three scattering components from an improved polarimetric decomposition were coupled with the MWCM, instead of the backscattering coefficients. Using a genetic algorithm, eight rice variables were estimated, such as the leaf area index (LAI), rice height (h), and the fresh and dry biomass of ears (F e and D e ). The accuracy validation showed the MWCM was suitable for the estimation of rice variables during the whole growth season. The validation results showed that the MWCM could predict the temporal behaviors of the rice variables well during the growth cycle (R 2 > 0.8). Compared with the original water cloud model (WCM), the relative errors of rice variables with the MWCM were much smaller, especially in the vegetation phase (approximately 15% smaller). Finally, it was discussed that the MWCM could be used, theoretically, for extensive applications since the empirical coefficients in the MWCM were determined in general cases, but more applications of the MWCM are necessary in future work.

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“…Values of ρ a = −1 (upper part of diagrams) characterize particles with horizontally oriented symmetry axis; ρ a = 0 is typical for uniformly distributed orientation angles θ ; ρ a = 1 (lower part of diagrams) describes a vertically oriented symmetry axis of particles. It should be noticed that ρ a ∼ −0.4 specifies the so-called fully chaotic orientation of particles (Ryzhkov, 2001) which can be considered as a special case of reflection symmetry (Nghiem et al, 1992). In this case the polarimetric variables do not depend on ψ, and Z DR and ρ CX are 0 dB and 0, respectively.…”

Section: Retrieval Techniquementioning

confidence: 99%

Cloud radar with hybrid mode towards estimation of shape and orientation of ice crystals

et al. 2016

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Abstract. This paper is devoted to the experimental quantitative characterization of the shape and orientation distribution of ice particles in clouds. The characterization is based on measured and modeled elevation dependencies of the polarimetric parameters differential reflectivity and correlation coefficient. The polarimetric data are obtained using a newly developed 35 GHz cloud radar MIRA-35 with hybrid polarimetric configuration and scanning capabilities. The full procedure chain of the technical implementation and the realization of the setup of the hybrid-mode cloud radar for the shape determination are presented. This includes the description of phase adjustments in the transmitting paths, the introduction of the general data processing scheme, correction of the data for the differences of amplifications and electrical path lengths in the transmitting and receiving channels, the rotation of the polarization basis by 45 • , the correction of antenna effects on polarimetric measurements, the determination of spectral polarimetric variables, and the formulation of a scheme to increase the signal-to-noise ratio. Modeling of the polarimetric variables is based on existing backscattering models assuming the spheroidal representation of cloud scatterers. The parameters retrieved from the model are polarizability ratio and degree of orientation, which can be assigned to certain particle orientations and shapes. The developed algorithm is applied to a measurement of the hybridmode cloud radar taken on 20 October 2014 in Cabauw, the Netherlands, in the framework of the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) campaign. The case study shows the retrieved polarizability ratio and degree of orientation of ice particles for a cloud system of three cloud layers at different heights. Retrieved polarizability ratios are 0.43, 0.85, and 1.5 which correspond to oblate, quasi-spherical, and columnar ice particles, respectively. It is shown that the polarizability ratio is useful for the detection of aggregation/riming processes. The orientation of oblate and prolate particles is estimated to be close to horizontal while quasi-spherical particles were found to be more randomly oriented.

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Symmetry properties in polarimetric remote sensing

Cited by 209 publications

References 9 publications

Assessment of L-Band Sar Data at Different Polarization Combinations for Crop and Other Landuse Classification

Assessment of L-Band Sar Data at Different Polarization Combinations for Crop and Other Landuse Classification

Estimation of Paddy Rice Variables with a Modified Water Cloud Model and Improved Polarimetric Decomposition Using Multi-Temporal RADARSAT-2 Images

Cloud radar with hybrid mode towards estimation of shape and orientation of ice crystals

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