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In contrast to the random nature of synthetic aperture radar (SAR) data, it is also possible to identify bright targets whose scattering properties scarcely vary within imaging and time. These targets are commonly named point-like scatterers and can be found in both urban and natural environments. Permanent-scatterer interferometry techniques single out stable scatterers in a stack of SAR images, which preserve their backscattering stability along time. However, this methodology may not be optimum in natural scenarios, where the temporal stability of the scattering is rather reduced, or when the number of available SAR acquisitions is significantly small. Consequently, alternative methods have come out to detect stable scatters in a single SAR image, thus reducing all constraints related to their temporal behavior. Particularly, spectral diversity techniques are exploited to detect the so-called coherent scatterers. In this paper, a new detection scheme based on the generalized likelihood ratio test approach (GLRTA) is proposed, and its performance is extensively evaluated compared with three of the traditional methods, namely, the sublook coherence approach, the sublook entropy approach, and the phase variance approach. Remarkably, the GLRTA exploits both amplitude and phase information and does not need any further averaging (apart from sublooking processing with reduced signal bandwidth). The presented analysis is conducted both theoretically and with simulated data. For all scenarios, the new detector outperforms the other methods. The obtained results are validated also on real data. Finally, the proposed GLRTA is tested over different scattering scenarios, considering three TerraSAR-X acquisitions. [ABSTRACT FROM PUBLISHER]

This paper examines the multifaceted effect of the effective spatial baseline, as expressed through the vertical (interferometric) wavenumber, on the inversion of forest height from polarimetric interferometric synthetic aperture radar (Pol-InSAR) data. First, the role of the vertical wavenumber in relating forest height to the interferometric (volume) coherence is introduced. Through the review of the forest height inversion from Pol-InSAR data, the effect of the vertical wavenumber on the inversion performance is evaluated. The selection of optimum with respect to forest height inversion performance, vertical wavenumbers is discussed. The impact of the acquisition geometry and terrain slopes on the vertical wavenumber and their consideration in the inversion methodology is addressed. The individual effects discussed are demonstrated by means of airborne repeat pass Pol-InSAR acquisitions in L- and P-band acquired over different forest conditions, including a boreal, a temperate, and a tropical forest test site. The achieved forest height inversion performance is validated against reference height data derived from airborne LIDAR acquisitions. [ABSTRACT FROM PUBLISHER]

TanDEM-X and TerraSAR-X platforms form together the first spaceborne single-pass polarimetric interferometer in space. This allows, for the first time, the acquisition of spaceborne polarimetric synthetic aperture radar interferometry (Pol-InSAR) data without the disturbing effect of temporal decorrelation. This paper aims to assess the potential of such data for forest applications. For this, single- and dual-pol data acquired over a boreal, a temperate, and a tropical site were investigated to characterize X-band penetration and polarization diversity of the interferometric coherence measurements. Pol-InSAR forest height inversion schemes have been proposed and implemented for the singleand dual-pol cases and cross validated against LIDAR reference measurements for all sites. The single-pol inversion relies on an external ground digital terrain model (DTM) and performed well for all sites with correlation coefficients r2 between 0.80 and 0.98. The dual-pol inversion does not require an external DTM but depends on the visibility of the whole forest layer. Accordingly, its performance varied with forest structure and season: The best performance was achieved for the summer acquisition of the boreal test site (r2 = 0.86) and for the winter acquisition of the temperate test site (r2 = 0.77). For the tropical test site, only a weak correlation (r2 = ~0.50) could be established. [ABSTRACT FROM PUBLISHER]

In the recent years, there has been increased interest in using synthetic aperture radar (SAR) to study and monitor glaciers and ice sheets for glaciological and climate change research. This paper describes the estimation of ice extinctions through the modeling of polarimetric interferometric SAR (Pol-InSAR) coherences as a combination of a surface contribution (from the snow–firn interface and wind-induced sastrugi features) and a volume response. Ground-to-volume scattering ratios derived from a novel polarimetric decomposition are used in conjunction with Pol-InSAR coherence magnitudes to invert the extinction of the ice layer. The inversion is performed for experimental airborne Pol-InSAR data at L-band and P-band acquired by the German Aerospace Center's (DLR) E-SAR system over the Austfonna ice cap in Svalbard, Norway, as part of the 2007 IceSAR campaign. Extinction dependences on frequency and glacier facie are investigated, and validation is performed comparing ground-penetrating radar data to SAR backscatter and extinction values. Best extinction results are obtained at shallow incidence angles with small wavenumbers and for low ground-to-volume scattering ratios. For swath areas in mid range to far range, accuracies of 25\% in extinction are anticipated when averaging over 100 effective looks for a four-baseline inversion constraining solutions to vertical wavenumbers of 0.01 \leq kz \leq 0.1. To allow inversion using single-baseline Pol-InSAR, the proposed model is of limited complexity. Suggested extensions for a more realistic scattering scenario include incorporating multiple englacial ice scattering layers and improving the way multiple baselines are combined [ABSTRACT FROM AUTHOR]

This paper investigates the polarimetric dependence of the interferometric complex correlation and proposes a methodology for cancelling individual scattering mechanisms, in terms of the complex correlation coefficient phase, under the assumption of the random volume over ground model. This allows the estimation of the ground topography on forested and vegetated areas. The first part of the analysis considers the separation of the volume from the ground (including the double-bounce scattering mechanism). This process identifies the polarization states, without constraining them to be equal in both polarimetric acquisitions, which allow to cancel either the volume scattering contribution or the ground contribution. In order to have access to the interferometric phase of the remaining or isolated scattering mechanism, the polarimetric phase contribution of this scattering mechanism has to be removed in a second step. In the case of forested areas, the previous methodology is considered from two different point of views. For the estimation of the underlying ground topography, the cancellation of the volume scattering contribution makes possible to access the interferometric phase associated to the ground contribution. In addition, the interferometric information associated to the volume scattering contribution is estimated based on the cancellation of the ground contribution. The proposed techniques are analyzed on the basis of simulated and experimental polarimetric interferometric synthetic aperture radar data, demonstrating that the ground topography, as well as the height associated to the volume contribution, are asymptotically nonbiased and dependent on the shape of the particles of the random volume. In case of spheres (\eta = 0), the ground-to-volume ratio presents large values favoring the accurate estimation of the topographic phase. For the case of dipole like particles (\eta = 0.5), the ground-to-volume ration decreases producing a coherence \vert\rho\vert in the order of 0.1, making necessary a large speckle filtering to obtain a reliable estimation of the topographic phase. [ABSTRACT FROM PUBLISHER]

In this paper the concept of point-like coherent scatterers (CSs) in urban areas is introduced. The detection of CSs in single and quad-polarized images is addressed and applied on polarimetric and interferometric high-resolution airborne SAR data at L-band. For the detection of CSs two different approaches are proposed and their individual performance is analyzed. The properties of the detected CSs and their polarimetric and interferometric characteristics are assessed. The role of polarimetry on the detection of the CSs is evaluated and the potential of extracting the orientation and dielectric properties of individual CSs is finally addressed. [ABSTRACT FROM AUTHOR]

Recently, polarimetric synthetic aperture radar (SAR) interferometry has generated much interest for forest applications. Forest heights and ground topography can be extracted based on interferometric coherence using a random volume over ground coherent mixture model. The coherence estimation is of paramount importance for the accuracy of forest height estimation. The coherence (or correlation coefficient) is a statistical average of neighboring pixels of similar scattering characteristics. The commonly used algorithm is the boxcar filter, which has the deficiency of indiscriminate averaging of neighboring pixels. The result is that coherence values are lower than they should be. In this paper, we propose a new algorithm to improve the accuracy in the coherence estimation based on speckle filtering of the 6 x 6 polarimetric interferometry matrix. Simulated images are used to verify the effectiveness of this adaptive algorithm. German Aerospace Center (DLR) L-Band E-SAR data are applied to demonstrate the improved accuracy in coherence and in forest height estimation. [ABSTRACT FROM AUTHOR]

Presents a study on the application of single-baseline polarimetric synthetic aperture radar (SAR) interferometry to the remote sensing and measurement of structure over forested terrain. Overview of SAR interferometry; Introduction of a polarimetric coherent scattering model; Effect of polarization on the interferometric coherence; Geometrical interpretation of the scattering model.

Investigates the importance of polarimetry in synthetic aperture radar (SAR) interferometry. Information on SAR interferometry; What is depended on by an interferometric system's performance; Examination of the advantages using radar polarimetry; In-depth look at the study.

Knowledge of the spatial patterns of successional stages (i.e., primary and secondary forest) in tropical forests allows to monitor forest preservation, mortality and regeneration in relation to natural and anthropogenic disturbances. Different successional stages have also different capabilities of re-establishing carbon stocks. Therefore, a successful discrimination of successional stages over wide areas can lead to an improved quantification of above ground biomass and carbon stocks. The reduction of the mapping uncertainties is especially a challenge due to high heterogeneity of the tropical vegetation. In this framework, the development of innovative remote sensing approaches is required. Forests (top) height (and its spatial distribution) are an important structural parameter that can be used to differentiate between different successional stages, and can be provided by Interferometric Synthetic Aperture Radar (InSAR) acquisitions. In this context, this paper investigates the potential of forest heights estimated from TanDEM-X InSAR data and a LiDAR digital terrain model (DTM) for separating successional stages (primary or old growth and secondary forest at different stages of succession) by means of a maximum likelihood classification. The study was carried out in the region of the Tapajós National Forest (Pará, Brazil) in the Amazon biome. The forest heights for three years (2012, 2013 and 2016) were estimated from a single-polarization in bistatic mode using InSAR model-based inversion techniques aided by the LiDAR digital terrain model. The validation of the TanDEM-X forest heights with independent LiDAR H100 datasets was carried out in the location of seven field inventory plots (measuring 50 × 50 m, equivalent to 0.25 ha), also allowing for the validation of the LiDAR datasets against the field data. The validation of the estimated heights showed a high correlation (r = 0.93) and a low uncertainty (RMSE = 3 m). The information about the successional stages and forest heights from field datasets was used to select training samples in the LiDAR and TanDEM-X forest heights to classify successional stages with a maximum likelihood classifier. The identification of different stages of forest succession based on TanDEM-X forest heights was possible with an overall accuracy of about 80%. • TanDEM-X forest heights for Tapajós National Forest are estimated with low uncertainty (~3 m) • Discrimination of tropical forest in successional stages using TanDEM-X forest heights can reach an overall accuracy of 80% • TanDEM-X height estimation performance is stable over time [ABSTRACT FROM AUTHOR]