Single and Multipolarimetric P-Band SAR Tomography of Subsurface Ice Structure

Banda, Francesco; Dall, Jørgen; Tebaldini, Stefano

doi:10.1109/tgrs.2015.2506399

Cited by 42 publications

(29 citation statements)

References 60 publications

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“…Since a single SAR interferometric pair is not able to provide resolution/sampling in the third dimension [10], it is not possible to perform derivative measurements along the v axis. Therefore the third column of the gradient tensor can not be observed.…”

Section: Gradient Tensor From Insar Measurementsmentioning

confidence: 99%

Estimating Strain and Rotation From Wrapped SAR Interferograms

Parizzi

Jaber

2018

IEEE Geosci. Remote Sensing Lett.

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This letter aims to discuss a general framework that allows the direct interpretation of the wrapped DInSAR phase in terms of surface strain S and rotation R components. The methodology is demonstrated showing the estimation of strain and rotation components of a glacier flow using three TerraSAR-X interferometric geometries (ascending right-looking, descending right-looking and descending left-looking. Finally since the left looking geometry can be difficult to obtain on a regular basis, the surface parallel flow assumption is extended to the phase gradients inversion in order to reduce the amount of necessary geometries from three to two.

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Section: Gradient Tensor From Insar Measurementsmentioning

confidence: 99%

Estimating Strain and Rotation From Wrapped SAR Interferograms

Parizzi

Jaber

2018

IEEE Geosci. Remote Sensing Lett.

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“…The BIOMASS tomographic phase [18] will provide the first global coverage during the first 14 months of operations, by collecting seven ascending and seven descending passes with 3-days repeat pass time, designed to maintain coherency at P-band [19]. Thanks to the long wavelength of about 70 cm it will be possible not only to characterize electromagnetic interactions of radar waves with the forest structure and generate AGB maps over tropical biomes, but also to generate a global map of terrain topography below the vegetation layer (DTM) [17] and subsurface features [20,21]. Previous studies reported that a TomoSAR intensity of 30 m canopy layer in dense tropical forests is strongly correlated to AGB [22][23][24], whereas the ground scattering alone is poorly correlated to biomass.…”

Section: Introductionmentioning

confidence: 99%

Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data

Banda¹,

d’Alessandro

Tebaldini

2020

Remote Sensing

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In this work, the role of volume scattering obtained from ground and volume decomposition of P-band synthetic aperture radar (SAR) data as a proxy for biomass is investigated. The analysis here presented originates from the BIOMASS L2 activities, part of which were focused on strengthening the physical foundations of the SAR-based retrieval of forest above-ground biomass (AGB). A critical analysis of the observed strong correlation between tomographic intensity and AGB is done in order to propose simplified AGB proxies to be used during the interferometric phase of BIOMASS. In particular, the aim is to discuss whether, and to what extent, volume scattering obtained from ground/volume decomposition can provide a reasonable alternative to tomography. To do this, both are tested on P-band data collected at Paracou during the TropiSAR campaign and cross-validated against in-situ AGB measurements. Results indicate that volume backscattered power as obtained by ground/volume decomposition is weakly correlated to AGB, notwithstanding different solutions for volume scattering are tested, and support the conclusion that forest structure actually plays a non-negligible role in AGB retrieval in dense tropical forests.

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“…Synthetic aperture radar tomography (TomoSAR) [1] has successfully been used to reconstruct three-dimensional (3D) urban infrastructures [2,3], to estimate the forest biomass [4,5], and to image ice structures [6,7]. The launch of the new generation of spaceborne satellites (e.g., TerraSAR-X/Tan-DEM-X, COSMO-SkyMed, and Gaofen-3) provides SAR images with unprecedented high resolution up to meter regime and even to submeter regime, which dramatically facilitates the reconstruction and monitoring of urban infrastructures.…”

Section: Introductionmentioning

confidence: 99%

Super-Resolved Multiple Scatterers Detection in SAR Tomography Based on Compressive Sensing Generalized Likelihood Ratio Test (CS-GLRT)

Luo

Dong

et al. 2019

Remote Sensing

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The application of SAR tomography (TomoSAR) on the urban infrastructure and other man-made buildings has gained increasing popularity with the development of modern high-resolution spaceborne satellites. Urban tomography focuses on the separation of the overlaid targets within one azimuth-range resolution cell, and on the reconstruction of their reflectivity profiles. In this work, we build on the existing methods of compressive sensing (CS) and generalized likelihood ratio test (GLRT), and develop a multiple scatterers detection method named CS-GLRT to automatically recognize the number of scatterers superimposed within a single pixel as well as to reconstruct the backscattered reflectivity profiles of the detected scatterers. The proposed CS-GLRT adopts a two-step strategy. In the first step, an L1-norm minimization is carried out to give a robust estimation of the candidate positions pixel by pixel with super-resolution. In the second step, a multiple hypothesis test is implemented in the GLRT to achieve model order selection, where the mapping matrix is constrained within the afore-selected columns, namely, within the candidate positions, and the parameters are estimated by least square (LS) method. Numerical experiments on simulated data were carried out, and the presented results show its capability of separating the closely located scatterers with a quasi-constant false alarm rate (QCFAR), as well as of obtaining an estimation accuracy approaching the Cramer–Rao Low Bound (CRLB). Experiments on real data of Spotlight TerraSAR-X show that CS-GLRT allows detecting single scatterers with high density, distinguishing a considerable number of double scatterers, and even detecting triple scatterers. The estimated results agree well with the ground truth and help interpret the true structure of the complex or buildings studied in the SAR images. It should be noted that this method is especially suitable for urban areas with very dense infrastructure and man-made buildings, and for datasets with tightly-controlled baseline distribution.

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Single and Multipolarimetric P-Band SAR Tomography of Subsurface Ice Structure

Cited by 42 publications

References 60 publications

Estimating Strain and Rotation From Wrapped SAR Interferograms

Estimating Strain and Rotation From Wrapped SAR Interferograms

Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data

Super-Resolved Multiple Scatterers Detection in SAR Tomography Based on Compressive Sensing Generalized Likelihood Ratio Test (CS-GLRT)

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