Modification of Polarimetric SAR Interferometry Target Decomposition With Accurate Topography

Guo, Shenglong; Yang, Li; Zhang, Jingjing; Yin, Qiang; Hong, Wen

doi:10.1109/lgrs.2015.2409311

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…This phase term has two contributions: the difference due to the complex scattering coefficient on the case of using different polarizations for master and slave images φ HV ¼ φ H À φ V , and the interferometric phase related to the position in the vertical coordinate ϕ S . Hence, the covariance matrix for the single bounce contribution is expressed as (Guo, Li, Zhang, Yin, & Hong, 2015):…”

Section: Improved Adaptive Model-based Decomposition Of Polinsar Datamentioning

confidence: 99%

“…The double bounce scattering component is modeled by scattering from the interaction between the ground and tree trunk, where the reflector surface can be made of different dielectric materials. Hence, the covariance matrix of the double-bounce scattering contribution is given by (Guo et al, 2015):…”

Section: Improved Adaptive Model-based Decomposition Of Polinsar Datamentioning

confidence: 99%

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An improved adaptive decomposition method for forest parameters estimation using polarimetric SAR interferometry image

Minh

Ngoc

Nguyen

2019

European Journal of Remote Sensing

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Forest parameters estimation using polarimetric synthetic aperture radar interferometry (PolInSAR) images is one of the greatest interests in remote sensing applications. Applying the model-based decomposition concept to PolInSAR data opened a new way for forest parameters estimation. However, the method tends to underestimate the forest height due to reflection symmetry assumption and required the numerical solution of nonlinear equation system. In order to overcome these limitations, an improved adaptive decomposition technique with PolInSAR data is proposed. In this approach, an accurate topographical phase and asymmetry volume scattering model are applied to the model-based decomposition technique for polarimetric SAR interferometry image. The accurate topographical phase is first estimated and then used as the initial input parameter to our numerical method. This approach is not only avoiding large error generated by the constant topographical phase in fluctuating forest areas but also improve the accuracy of forest height estimation and the magnitude associated with each mechanism. The performance of proposed method is demonstrated with simulated data from PolSARproSim software and SIR-C/X-SAR spaceborne PolInSAR images over the Tien-Shan areas, China. Experimental results indicate that forest parameters could be effectively extracted by proposed method.

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Section: Improved Adaptive Model-based Decomposition Of Polinsar Datamentioning

confidence: 99%

Section: Improved Adaptive Model-based Decomposition Of Polinsar Datamentioning

confidence: 99%

An improved adaptive decomposition method for forest parameters estimation using polarimetric SAR interferometry image

Minh

Ngoc

Nguyen

2019

European Journal of Remote Sensing

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Hydrocarbon Identification and Bedding Fracture Detection in Shale Gas Reservoirs Based on a Novel Seismic Dispersion Attribute Inversion Method

et al. 2022

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Prediction of hydrocarbon enrichment and natural fractures is significant for sweet spot characterization in shale gas reservoirs. However, it is difficult to estimate reservoir properties using conventional seismic techniques based on elastic and isotropic assumptions. Considering that the viscoelastic anisotropic model better represents organic shale, we propose a new seismic inversion method to improve shale gas characterization by incorporating the anisotropic reflectivity theory in the frequency-dependent inversion scheme. The computed P-wave velocity dispersion attribute DP evaluates the hydrocarbon enrichment by estimating the inelastic properties of shale associated with organic materials. The inverted anisotropic dispersion attribute Dε detects the development intensity of bedding fractures using frequency-dependent anisotropy owing to wave-induced fluid flow in parallel fractures. Synthetic tests indicate that DP can robustly estimate shale attenuation and Dε is sensitive to the frequency-dependent anisotropy of shale. The results are validated by reservoir properties measured in gas-producing boreholes and rock physical modeling analysis, supporting the applicability of the dispersion attributes for hydrocarbon identification and bedding fracture detection. The predicted hydrocarbon enrichment and the development of bedding fractures correlate with the structural characteristics of the shale formation. The depth-related shale properties can be described by improving the geological understanding of the study area. Finally, favorable areas with high hydrocarbon enrichment and extensive development of bedding fractures are identified by simultaneously considering high DP and Dε anomalies, providing essential information for predicting potential shale gas reservoirs. Article Highlights A novel seismic inversion method for anisotropy dispersion attributes is proposed P-wave velocity dispersion attribute is used to identify hydrocarbon enrichment in shale Anisotropic dispersion attribute is used to detect bedding fractures in shale

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A general three-component polarimetric SAR interferometry target decomposition

Hu,

Xie,

David Ballester-Berman

et al. 2024

Advances in Space Research

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Modification of Polarimetric SAR Interferometry Target Decomposition With Accurate Topography

Cited by 5 publications

References 11 publications

An improved adaptive decomposition method for forest parameters estimation using polarimetric SAR interferometry image

An improved adaptive decomposition method for forest parameters estimation using polarimetric SAR interferometry image

Hydrocarbon Identification and Bedding Fracture Detection in Shale Gas Reservoirs Based on a Novel Seismic Dispersion Attribute Inversion Method

A general three-component polarimetric SAR interferometry target decomposition

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