Requirements for Model-based Polarimetric Decompositions

Zyl, J.J. van; Kim, Yun-Jin; Arii, Motofumi

doi:10.1109/igarss.2008.4780117

Cited by 34 publications

(21 citation statements)

References 4 publications

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“…There are known limitations of these types of models. Such models may overestimate volume scattering from vegetation, as evidenced by negative eigenvectors representing the non-volume scattering remaining of the covariance matrix [23,38]. Such limitations have led to the development of a three-component model using thin cylinders and a generalized PDF to model scattering from the canopy [23].…”

Section: Methodsmentioning

confidence: 99%

“…Differences in the extent of cleared areas around settlements are also present. Large differences in response from non-mangrove regions between 2010 and the other two datasets are most likely due to changes in environmental conditions: the growing season, rainfall and flooding (e.g., [23,38]). The 2010 data exhibit a less dramatic difference between settled regions and the surrounding mangrove.…”

Section: Temporal Variationsmentioning

confidence: 99%

“…H/α data acquired over hardwood forests in Queensland, Australia, exhibited very high values of H over mature forest stands, leading to difficulties in differentiating scattering mechanisms [38]. In all years, Sonneratia sites (11A, 16A; Figure S4 and Figure S5 in the Supplementary Materials) demonstrate mean values (0.74-0.78) slightly lower than Rhizophora-and Avicennia-dominant sites (14A, 9A and 5A), which exhibit H values of 0.81-0.84 (Table S1 in the Supplementary Materials).…”

Section: Entropy-anisotropy-alphamentioning

confidence: 99%

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L-Band Polarimetric Target Decomposition of Mangroves of the Rufiji Delta, Tanzania

2016

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Abstract:The mangroves of the Rufiji Delta are an important habitat and resource. The mangrove forest reserve is home to an indigenous population and has been under pressure from an influx of migrants from the landward side of the delta. Timely and effective forest management is needed to preserve the delta and mangrove forest. Here, we investigate the potential of polarimetric target decomposition for mangrove forest monitoring and analysis. Using three ALOS PALSAR images, we show that L-band polarimetry is capable of mapping mangrove dynamics and is sensitive to stand structure and the hydro-geomorphology of stands. Entropy-alpha-anisotropy and incoherent target decompositions provided valuable measures of scattering behavior related to forest structure. Little difference was found between Yamaguchi and Arii decompositions, despite the conceptual differences between these models. Using these models, we were able to differentiate the scattering behavior of the four main species found in the delta, though classification was impractical due to the lack of pure stands. Scattering differences related to season were attributed primarily to differences in ground moisture or inundation. This is the first time mangrove species have been identified by their scattering behavior in L-band polarimetric data. These results suggest higher resolution L-band quad-polarized imagery, such as from PALSAR-2, may be a powerful tool for mangrove species mapping.

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Section: Methodsmentioning

confidence: 99%

Section: Temporal Variationsmentioning

confidence: 99%

Section: Entropy-anisotropy-alphamentioning

confidence: 99%

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L-Band Polarimetric Target Decomposition of Mangroves of the Rufiji Delta, Tanzania

2016

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“…Some attempts have been investigated and proposed in order to cope with this problem. In [20,21] the authors investigated the issue of negative power of the remainder after subtraction of the volume component and introduced a new approach consisting in modulating the contribution attributed to the volume by means of a nonnegative eigenvalue constraint. Alternatively, in [22] the assumption of a forest volume as a maximum entropy scenario was implemented jointly with deorientation [23][24][25] of the coherency matrix for minimizing the cross-polar channel.…”

Section: Fundamentals On Model-based Polsar Modelingmentioning

confidence: 99%

Polarimetric Sar Model for Soil Moisture Estimation Over Vineyards at C-Band

Ballester-Berman¹,

Vicente-Guijalba²,

López-Sánchez³

2013

PIER

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Abstract-In this paper we propose a two-component polarimetric model for soil moisture estimation on vineyards suited for C-band radar data. According to a polarimetric analysis carried out here, this scenario is made up of one dominant direct return from the soil and a multiple scattering component accounting for disturbing and nonmodeled signal fluctuations from soil and short vegetation. We propose a combined X-Bragg/Fresnel approach to characterize the polarized direct response from soil. A validation of this polarimetric model has been performed in terms of its consistency with respect to the available data both from RADARSAT-2 and from indoor measurements. High inversion rates are reported for different phenological stages of vines, and the model gives a consistent interpretation of the data as long as the volume component power remains about or below 50% of the surface contribution power. However, the scarcity of soil moisture measurements in this study prevents the validation of the algorithm in terms of the accuracy of soil moisture retrieval and an extensive campaign is required to fully demonstrate the validity of the model. Different sources of mismatches between the model and the data have been also discussed and analyzed.

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“…Van Zyl et al (2008Zyl et al ( , 2011 proposed NNED method to determine the volume scattering power, which is of benefit to avoid negative powers in decomposition results. However, due to the volume scattering model that also accounts for the HV component for dihedral structures in this paper, the NNED is modified slightly to avoid the denominator of a fractional expression from solving the parameter a to be zero in the data processing procedure.…”

Section: Determination Of the Scattering Powersmentioning

confidence: 99%

Alternative to Four-Component Decomposition for Polarimetric Sar

Zhang¹,

Huang²,

Wei³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:There are more unknowns than equations to solve for previous four-component decomposition methods. In this case, the nonnegative power of each scattering mechanism has to be determined with some assumptions and physical power constraints. This paper presents a new decomposition scheme, which models the measured matrix after polarimetric orientation angle (POA) compensation as a linear sum of five scattering mechanisms (i.e., odd-bounce scattering, double-bounce scattering, diffuse scattering, volume scattering, and helix scattering). And the volume scattering power is calculated by a slight modified NNED method, owing to this method considering the external volume scattering model from oblique dihedral structure. After the helix and volume scattering powers have been determined sequentially, the other three scattering powers are estimated by combining the generalized similarity parameter (GSP) and the eigenvalue decomposition. Among them, due to POA compensation, the diffuse scattering induced from a dihedral with a relative orientation of 45º has negligible scattering power. Thus, the new method can be reduced as four-component decomposition automatically. And then the ALOS-2 PolSAR data covering Guiyang City, Guizhou Province, China were used to evaluate the performance of the new method in comparison with some classical decomposition methods (i.e. Y4R, S4R and G4U).

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Requirements for Model-based Polarimetric Decompositions

Cited by 34 publications

References 4 publications

L-Band Polarimetric Target Decomposition of Mangroves of the Rufiji Delta, Tanzania

L-Band Polarimetric Target Decomposition of Mangroves of the Rufiji Delta, Tanzania

Polarimetric Sar Model for Soil Moisture Estimation Over Vineyards at C-Band

Alternative to Four-Component Decomposition for Polarimetric Sar

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