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NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Tomographic Synthetic Aperture Radar (SAR) allows the reconstruction of the 3D radar reflectivity of forests from a large(r) number of multi-angular acquisitions. However, in most practical implementations it suffers from limited vertical resolution and/or reconstruction artefacts as the result of non-ideal acquisition setups. Polarisation Coherence Tomography (PCT) offers an alternative to traditional tomographic techniques that allow the reconstruction of the low-frequency 3D radar reflectivity components from a small(er) number of multi-angular SAR acquisitions. PCT formulates the tomographic reconstruction problem as a series expansion on a given function basis. The expansion coefficients are estimated from interferometric coherence measurements between acquisitions. In its original form, PCT uses the Legendre polynomial basis for the reconstruction of the 3D radar reflectivity. This paper investigates the use of new basis functions for the reconstruction of X-band 3D radar reflectivity of forests derived from available lidar waveforms. This approach enables an improved 3D radar reflectivity reconstruction with enhanced vertical resolution, tailored to individual forest conditions. It also allows the translation from sparse lidar waveform vertical reflectivity information into continuous vertical reflectivity estimates when combined with interferometric SAR measurements. This is especially relevant for exploring the synergy of actual missions such as GEDI and TanDEM-X. The quality of the reconstructed 3D radar reflectivity is assessed by comparing simulated InSAR coherences derived from the reconstructed 3D radar reflectivity against measured coherences at different spatial baselines. The assessment is performed and discussed for interferometric TanDEM-X acquisitions performed over two tropical Gabonese rainforest sites: Mondah and Lopé. The results demonstrate that the lidar-derived basis provides more physically realistic vertical reflectivity profiles, which also produce a smaller bias in the simulated coherence validation, compared to the conventional Legendre polynomial basis. [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. Index Terms--Coherence estimation, forest parameter inversion, polarimetric interferometry, synthetic aperture radar (SAR) speckle filtering.

The objective of this paper is to examine the application of single-baseline polarimetric SAR interferometry to the remote sensing and measurement of structure over forested terrain. For this, a polarimetric coherent scattering model for vegetation cover suitable for the estimation of forest parameters from interferometric observables is introduced, discussed and validated. Based on this model, an inversion algorithm which allows the estimation of forest parameters such as tree height, average extinction, and underlying topography from single-baseline fully polarimetric interferometric data is addressed. The performance of the inversion algorithm is demonstrated using fully polarimetric single baseline experimental data acquired by DLR's E-SAR system at L-band. Index Terms--Forest parameter inversion, polarimetric interferometry, radar polarimetry, synthetic aperture radar (SAR) interferometry.

In this paper, we examine the role of polarimetry in synthetic aperture radar (SAR) interferometry. We first propose a general formulation for vector wave interferometry that includes conventional scalar interferometry as a special case. Then, we show how polarimetric basis transformations can be introduced into SAR interferometry and applied to form interferograms between all possible linear combinations of polarization states. This allows us to reveal the strong polarization dependency of the interferometric coherence. We then solve the coherence optimization problem involving maximization of interferometric coherence and formulate a new coherent decomposition for polarimetric SAR interferometry that allows the separation of the effective phase centers of different scattering mechanisms. A simplified stochastic scattering model for an elevated forest canopy is introduced to demonstrate the effectiveness of the proposed algorithms. In this way, we demonstrate the importance of wave polarization for the physical interpretation of SAR interferograms. We investigate the potential of polarimetric SAR interferometry using results from the evaluation of fully polarimetric interferometric shuttle imaging radar (SIR)-C/X-SAR data collected during October 8-9, 1994, over the SE Baikal Lake Selenga delta region of Buriatia, Southeast Siberia, Russia. Index Terms - Polarimetric interferometry, radar polarimetry, synthetic aperture radar (SAR), SAR interferometry.

In this paper, we exploit the interferometric multifrequency potentiality of the SIR-C/X-SAR system which is equipped with an L-, C-, and X-band sensor. We present a solution to improve the unwrapping performance of the C- and X-band data by considering the L-band unwrapped pattern. A new algorithm for the generation of a single digital elevation model (DEM) combining L-, C-, and X-band information is presented. This solution is based on the fusion of the unwrapped phase patterns by using a Kalman filter. The proposed fusion operation also accounts for the coherence characteristics of the three data sets. The selected test site is the Mt. Etna region in Italy which is very interesting from the volcanological and geological point of view. Numerical assessments of the achieved results are provided by evaluating the height accuracy with respect to a reference DEM.

This article proposes a change detection and analysis technique for monitoring the phenological development of agricultural vegetation by means of multitemporal Polarimetric Synthetic Aperture Radar (PolSAR) acquisitions. The technique relies on the generalized eigendecomposition of the polarimetric covariance matrices of the individual acquisitions. It both quantifies the magnitude of the change between PolSAR images acquired at different times and also provides an interpretation of occurred change in terms of the modified polarization states. This makes the algorithm suitable for investigating scattering dynamics associated with the phenological development of agricultural vegetation. To aid the interpretation of the changes detected, a representation based on the polarization states affected by the change process is proposed. The technique is evaluated using part of the multitemporal AGRISAR 2006 campaign data set. This data set consists of 12 quad-polarimetric images acquired by the German Aerospace Center (DLR) E-SAR airborne system at L-band from April 2006 to August 2006 over the Demmin test site. It covers large parts of the development cycle of different crop types. As a part of the evaluation, reference ground measurements are used to facilitate the interpretation of the data. The evaluation focuses on five important crop types: wheat, barley, rape, maize, and sugar beet. The results show that the proposed technique is able to detect and characterize different types of changes related to distinct development states of different crop types as the plant growing, maturation, and drying processes. [ABSTRACT FROM AUTHOR]

We investigate multichannel imaging radar systems employing coherent combinations of polarimetry and interferometry (Pol-InSAR). Such systems are well suited for the extraction of bio- and geophysical parameters by evaluating the combined scattering from surfaces and volumes. This combination leads to several important differences between the design of Pol-InSAR sensors and conventional single polarisation SAR interferometers. We first highlight these differences and then investigate the Pol-InSAR performance of two proposed spaceborne SAR systems (ALOS/PalSAR and TerraSAR-L) operating in repeat-pass mode. For this, we introduce the novel concept of a phase tube which enables (1) a quantitative assessment of the Pol-InSAR performance, (2) a comparison between different sensor configurations, and (3) an optimization of the instrument settings for different Pol-InSAR applications. The phase tube may hence serve as an interface between system engineers and application-oriented scientists. The performance analysis reveals major limitations for even moderate levels of temporal decorrelation. Such deteriorations may be avoided in single-pass sensor configurations and we demonstrate the potential benefits from the use of future bi- and multistatic SAR interferometers.

Forest structure is a key parameter for forest applications, but it is difficult to be estimated at the required spatial and temporal scales. In this context, synthetic aperture radar Tomography (TomoSAR) that allows, at lower frequencies, the 3-D imaging of natural volume scatterers with high spatial and temporal resolution may be a game changer. The aim of this article is to evaluate three TomoSAR algorithms, Fourier beamforming (FB), Capon beamforming (CB), and compressive sensing (CS) with respect to their performance in the reconstruction of the 3-D forest reflectivity. The implications of volumetric forest scattering, as well as the temporal decorrelation of scatterers, are analyzed. The algorithms are compared on a set of simulated scenarios and then evaluated on an experimental L-band data set composed by four acquisition dates, each one consisting of five tomographic tracks. The data were acquired in 2014, within a time span of two months, over the Traunstein forest (Germany) using the F-SAR system. Additionally, discrete airborne Lidar has been used for a qualitative evaluation. The results indicate that the CS reconstruction is, for many practical cases, superior when compared to FB or CB reconstructions as they achieve higher vertical resolution, especially in cases with a lower number of acquisitions and complex forest scenarios. By combining acquisitions performed at different days, the effect of temporal decorrelation on each algorithm for two different tomographic implementations (repeat-pass vs. single-pass) has been assessed. The results indicate that simultaneously acquired image pairs allow a better reconstruction of the 3-D forest reflectivity. [ABSTRACT FROM AUTHOR]

Compact polarimetry is a dual-polarization hybrid imaging mode and provides partially backscatter characteristics of scatterers. The compact polarimetric (CP) synthetic aperture radar (SAR) measures the combinations of fully polarimetric (FP) scattering coefficients, which is dependent on the transmit-wave polarization state. The backscattered wave is fully described by a 2-D complex scattering vector, in which the dual-channel polarization ratio represents the vector nature for describing target polarimetric properties. However, due to the dependence of CP measurements on the transmit wave, the complex channel ratio is explained differently for the same scatterers under different observation modes, e.g., the channel ratio ρ = ± j under the left circular mode and ρ = ±1 under the linear π/4 mode for the canonical trihedral and dihedral scatterers. The explanation diversity is inconvenient for the use of CP data, resulting in nonunified target decomposition algorithms. In this study, first, we propose a new formalism method for the general CP SAR mode, such that all CP mode observables are described based on the same standard for target scattering characterization. This provides potential for developing unified CP decomposition algorithms. Then, based on this formalism, a polarization ratio-based scattering characterization method is proposed, which is mathematically equal to the FP ΔαB/αB method but without any scattering assumption. Theoretical analyses and discussions are provided. Experiments show that the proposed method is efficient for compact polarimetric scattering interpretation. [ABSTRACT FROM AUTHOR]

The penetration of microwave signals into snow and ice, especially in dry conditions, introduces a bias in digital elevation models generated by means of synthetic aperture radar (SAR) interferometry. This bias depends directly on the vertical backscattering distribution in the subsurface. At the same time, the sensitivity of interferometric SAR measurements on the vertical backscattering distribution provides the potential to derive information about the subsurface of glaciers and ice sheets from SAR data, which could support the assessment of their dynamics. The aim of this article is to improve the interferometric modeling of the vertical backscattering distribution in order to support subsurface structure retrieval and penetration bias estimation. Vertical backscattering distributions are investigated at different frequencies and polarizations on two test sites in the percolation zone of Greenland using fully polarimetric X-, C-, L-, and P-band SAR data. The vertical backscattering distributions were reconstructed by means of SAR tomography and compared to different vertical structure models. The tomographic assessment indicated that the subsurface in the upper percolation zone is dominated by scattering layers at specific depths, whereas a more homogeneous scattering structure appears in the lower percolation zone. The performance of the evaluated structure models, namely an exponential function with a vertical shift, a Gaussian function, and a Weibull function, was evaluated. The proposed models improve the representation of the data compared with existing models while the complexity is still low to enable potential model inversion approaches. The tomographic analysis and the model assessment is therefore a step forward toward subsurface structure information and penetration bias estimation from SAR data. [ABSTRACT FROM AUTHOR]

Compact polarimetry is a hybrid dual-polarization imaging mode, which is used to enable wide swath coverages and provide more polarimetric information compared with the conventional dual-polarimetric imaging modes (HH/HV and VH/VV). In applications of compact polarimetric synthetic aperture radar (Pol-SAR), pseudo quad-polarimetric (quad-pol) image reconstruction is an important technique. In this study, we propose a least-squares (LS) based method to estimate the quad-pol covariance elements for the linear π/4 compact polarimetric mode. Different from existing quad-pol reconstruction approaches, which use an iterative approach to refine the model solution based on multi-look data, the LS method uses a set of data points to best fit the reconstruction model and is applicable to both multi-look and single-look complex data. In this study, a decomposition-based three-component reconstruction model is exploited to construct the system of non-linear equations. Then, the minimization problem is addressed in a local window for the cross-polarized term, which is optimized with bound constraints. Furthermore, the $m - {\alpha _s}$ decomposition for the linear compact mode is developed, which is used to approximate the reconstruction model parameter for the LS model function. Experiments are performed on C-band RADARSAT-2 data collected over agriculture fields, an urban area, and an area with complex terrain types. In comparison with the iterative-based methods, the LS-based reconstruction method shows its superiority in estimating both the cross-polarized term and the co-polarized phase difference. [ABSTRACT FROM AUTHOR]

The analysis of data from an airborne synthetic aperture radar (SAR) campaign in the percolation zone of Greenland revealed an interferometric coherence undulation behavior with respect to vertical wavenumber, which cannot be explained with existing models. We propose a model extension that accounts for scattering from distinct layers below the surface. Simulations show that the periodicity of the coherence undulation is mainly driven by the vertical distance between dominant subsurface layers, while the amplitude of the undulation is determined by the ratio between scattering from distinct layers and scattering from the firn volume. We use the model to interpret quad-pol SAR data at X-, C-, S-, L-, and P-bands. The inferred layer depths match layer detections in ground-based radar data and in situ measurements. We conclude that in the percolation zone, scattering from subsurface layers has to be taken into account to correctly interpret SAR data and demonstrate the potential to retrieve geophysical information about the vertical subsurface structure. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) tomography (TomoSAR) allows the reconstruction of the vertical distribution of the power backscattered by natural volumes by combining multiple SAR images acquired with slightly different incidence angles. Being a “radar” quantity, the profile depends on the radar frequency, polarization, and acquisition geometry, the 3-D distribution of the scattering elements and their dielectric properties. The characterization of each one of these factors is crucial to enable the extraction of physical 3-D structure attributes from TomoSAR profiles. The objective of this paper is to investigate how the vertical distribution of the backscattered power at L-band is affected by seasonal- and weather-induced changes. Radiometric (e.g., ground and volume powers) and geometric (e.g., center of mass of the volume-only profiles and phase centers of the volume scattering layers) parameters have been estimated under different weather and season conditions and compared. Then, TomoSAR data sets affected by dielectric nonstationarity (i.e., variability) have been considered in order to assess the invariance degree of each radiometric and geometric parameters. This analysis has been carried out by processing four L-band airborne TomoSAR data sets acquired before and after a rainfall and in spring and autumn over the Traunstein forest (south of Germany). [ABSTRACT FROM AUTHOR]

The aim of this paper is to compare L- and P-band vertical backscattering profiles estimated by means of synthetic aperture radar (SAR) tomography and full light detection and ranging (lidar) waveforms in terms of their ability to distinguish different tropical forest structure types. The comparison relies on the unique DLR F-SAR and NASA Land, Vegetation and Ice Sensor (LVIS) lidar datasets acquired in 2016 in the frame of the AfriSAR campaign. In particular, F-SAR and LVIS data over three different test sites complemented by plot field measurements are used. First, the SAR and lidar three-dimensional (3-D) datasets are compared and discussed on a qualitative basis. The ability to penetrate into and through the canopy down to the ground is assessed at L- and P-band in terms of both the ground-to-volume power ratio and the performance to estimate the location of the underlying ground. The effect of polarimetry on the visibility of the ground is discussed as well. Finally, the 3-D measurements for each configuration are compared with respect to their ability to derive physical forest structure descriptors. For this, vertical structure indices derived from the volume-only 3-D radar reflectivity at L- and P-band and from the LVIS profiles are compared against each other as well as against plot-derived indices. [ABSTRACT FROM AUTHOR]

Understanding the impact of soil and plant parameter changes in agriculture on Synthetic Aperture Radar (SAR) measurements is of great interest when it comes to monitor the temporal evolution of agricultural crops by means of SAR. In this regard, specific transitions between phenological stages in corn, barley, and wheat have been identified associated to certain dielectric and geometric changes, based on a time series of fully polarimetric multibaseline SAR data and in situ measurements. The data have been acquired in the frame of DLR's CROPEX campaign on six dates between May and July in 2014. The experiments reported in this paper address the sensitivity of X-, C-, and L-band to phenological transitions exploiting the availability of multiple baselines on each acquisition date. The application of tomographic techniques enables the estimation of the three-dimensional (3-D) backscatter distribution and the separation of ground and volume scattering components. Tomographic parameters have been derived at different frequencies, namely the center of mass of the profiles of the total and of the volume-only 3-D backscatter, and the ground and volume powers. Their sensitivity and ability to detect changes occurring on the ground and in the vegetation volume have been evaluated focusing on the added value provided by the 3-D resolution at the different frequencies and polarizations available. [ABSTRACT FROM AUTHOR]

The aim of this paper is to interpret and characterize the changes of the 3-D polarimetric scattering signatures of agricultural crops at C-band and to relate them to temporal changes of the soil and plant parameters. For this, a time series of multibaseline (MB) synthetic aperture radar (SAR) data acquired at C-band by the airborne F-SAR system of the German Aerospace Center over the Wallerfing test site in Germany was analyzed. The availability of MB SAR data enables the resolution of scattering contributions in height by means of SAR tomography. The tomographic profiles at different polarizations were analyzed regarding temporal changes for different crop types. First, it was investigated if the center of mass (CoM) of the vertical reflectivity profiles as a single parameter enables the tracking of changes in soil and vegetation. The results show that the vertical reflectivity profiles and their CoM do not allow resolving the ambiguity if a change originates from soil or vegetation dynamics as expected. Thus, the scattering contributions from ground and volume were separated in height, using a filtering approach, and used for the estimation of the ground and volume scattering powers by means of covariance matching. Comparing the outputs with coincident ground measurements showed that dielectric as well as geometric changes in the vegetation are traceable by the separated ground and volume powers. Finally, the estimated powers were analyzed with respect to orientation effects, i.e., to polarimetric anisotropic behavior. They were found to be not significant for the crops under study at C-band. [ABSTRACT FROM AUTHOR]

A significant amount of the data acquired by sun-synchronous space-borne low-frequency synthetic aperture radars (SARs) through the postsunset equatorial sector are distorted by the ionospheric scintillations due to the presence of plasma irregularities and their zonal and vertical drift. In the focused SAR images, the distortions due to the postsunset equatorial ionospheric scintillations appear in the form of amplitude and/or phase “stripe” patterns of high spatial frequency aligned to the projection of the geomagnetic field onto the SAR image plane. In this paper, a methodology to estimate the height and the drift velocity of the scintillations from the “stripe” patterns detected in the SAR images is proposed. The analysis is based on the fact that the zonal and vertical drift of the plasma irregularities are, at the equatorial zone, perpendicular to the geomagnetic field which is almost parallel aligned to the orbit. The methodology takes advantage of the time lapse and change of imaging geometry across azimuth subapertures. The obtained height estimates agree well with the reference measurements and independent estimates reported in the literature, while the drift velocities appear slightly overestimated. This can be attributed to a suboptimum geometry configuration but also to a decoupling of the ambient ionosphere and the plasma irregularities. [ABSTRACT FROM PUBLISHER]

In forest and agricultural scattering scenarios, the backscattered synthetic aperture radar (SAR) signature consists, depending on the frequency, of the superposition of ground and volume scattering contributions. Using multibaseline SAR data, SAR tomography techniques allow resolving contributions occurring at different heights. Two algorithms for the separation of ground and volume scattering are compared with respect to their ability to provide a coherent volume component that can be further used for parameter inversion, both of them requiring only the a priori known ground topography. Once the volume-only coherences are available, the total ground and volume scattering powers are estimated by means of a least squares fitting. The objective of this letter is to quantitatively evaluate the performance of this estimation by means of a Monte Carlo analysis with simulated data focusing on the impact of vertical resolution, errors in the knowledge of the ground topography and phase calibration residuals. [ABSTRACT FROM PUBLISHER]

Boreal forests are characterized by a rather homogeneous stand structure that allows by means of a single allometric equation to estimate biomass from forest height with sufficient accuracy and, therefore, to use this equation for quantitative biomass classifications. In this paper, interferometric TanDEM-X DEM data are used to estimate forest height over boreal forest systems. The accuracy of the height inversion is evaluated for single- and dual-baseline scenarios, under summer and winter conditions. Then, an allometric equation is used to transfer forest height to biomass. For this, two forest sites, boreal (Krycklan) and hemi-boreal (Remningstorp) in north and southern Sweden, respectively, are investigated. A performance analysis is carried out to estimate the maximum number of biomass classes obtained, depending on the height estimation accuracy. For summer acquisitions, four biomass classes can be obtained, with a maximum biomass class of > 200 Mg/ha. For winter acquisitions or when a mixed summer—winter approach is applied, five biomass classes, up to 220 Mg/ha, can be obtained. This classification shows a good agreement with CORINE, an existing land cover classification, and can improve it by adding quantitative forest biomass classes with a high spatial resolution of 16 $\times$ 16 m. [ABSTRACT FROM AUTHOR]

A novel oriented volume over ground (OVoG) inversion scheme is developed and tested on a data set of simulated agricultural scenarios and real SAR acquisitions. The algorithm makes use of multibaseline measurements to estimate the whole set of the OVoG structural parameters (e.g., crop height, differential extinction between eigenpolarizations, and ground-to-volume ratios) and is significantly robust against nonvolumetric decorrelation contributions. The theoretical assessment points out that, in the dual-baseline case, the vegetation height hV can be estimated with a relative root-mean-square deviation (%RMSD) of 7.8% if the selected baselines fulfill the condition 1.2 <\kappazhV <2.8\ \text{rad} ( \kappaz is the vertical wavenumber). Furthermore, the variance of the estimates is inversely related to the number of baselines $Nb$. Compared with the dual-baseline case, the RMSD of the differential extinction is reduced by 45% (from 1.1 to 0.6 dB/m) when Nb=5$ baselines are employed, whereas its mean bias is independent of Nb$. The proposed scheme has been assessed using a set of repeat-pass F-SAR acquisitions at L-, C-, and X-band of an agricultural area in Germany. Using two baselines, the height of maize and rape fields is estimated with an average 10% %RMSD if the inversion is carried out over L-band acquisitions. On the other hand, when X-band data are employed, one can obtain reliable estimates of wheat and barley height, with a %RMSD better than 24%. The study also indicates the existence of differential wave propagation effects through maize ( between 0.7 and 1 dB/m) and rape (\Delta\sigma=-0.8\ \text{dB/m}) canopies at L-band. [ABSTRACT FROM PUBLISHER]

Over the last 30 years, the use of airborne and satellite remote sensing techniques has revolutionized glaciology through unequaled improvements in the scale and in the temporal and spatial resolutions of cryospheric observations. In this sense, the use of synthetic aperture radar (SAR) configurations likely was the greatest advance of the past two decades in the monitoring of the Earth's cryosphere. This paper describes a novel polarimetric scattering model to interpret polarimetric SAR (PolSAR) measurements of glaciers and ice sheets. Different scattering components are considered according to the specific glacier facies, in order to infer physical parameters of the ice volume. Total backscattering is modeled as the incoherent sum of possible surface and volume contributions. Surface scattering is described using the X-Bragg model in order to account for roughness, whereas clouds of spheroidal scatterers (either prolates or oblates) are considered to model volume scattering. The model includes differential propagation effects related to firn anisotropy and is therefore able to interpret polarimetric phase differences often present in PolSAR data acquired over glaciers. The developed model is used to interpret different scenarios imaged at L-band in fully polarimetric mode by the E-SAR sensor of the German Aerospace Center (DLR) over test sites located on the Austfonna ice cap, Svalbard, Norway, as part of the ICESAR2007 campaign. The obtained results are consistent with the reference information provided by the available ground measurements about the subsurface structure of the study area and encourage the use of dedicated scattering models for the different glacier zones. [ABSTRACT FROM PUBLISHER]

Spaceborne synthetic aperture radars (SARs) represent a powerful tool to perform cryospheric observations due to their high spatial resolution and capability to acquire data during the winter time. Especially at lower frequencies, SAR signals penetrate beneath the glacier surface through the shallow snow cover, interacting with surface as well as subsurface features. This makes the scattering scenario very complex and the interpretation of SAR backscattering from glaciers and ice sheets not straightforward. In the case of polarimetric SARs, the understanding of polarization phase differences represents one of the main open issues. In this letter, a physical model is employed to relate copolarization HH-VV phase difference (CPD) to structural and dielectric properties of snow and firn which characterize the uppermost layers of glaciers. Modelled CPD values are compared to values observed in airborne L-band (1.3 GHz) SAR data, acquired over the Austfonna ice cap, in Svalbard, in spring 2007. The inversion of the employed model shows promising results toward the retrieval of firn properties. In particular, the obtained thickness estimates are found to be in good agreement with the GPR profiles measured in coordination with the SAR acquisitions. [ABSTRACT FROM PUBLISHER]

A correction methodology for distortions induced by ionospheric scintillation on fully polarimetric synthetic aperture radar (SAR) data is proposed. The correction is based on deriving the phase distortion induced by the ionosphere from Faraday rotation estimates. The estimated phase distortion is then used for correction. In order to compensate the phase and time–Doppler history distortions, the correction has to be performed at the slant range of the ionospheric layer, i.e., on partially focused single-look complex data. Accordingly, the performance of the proposed correction methodology depends, among other factors, on knowledge of the altitude of the effective ionospheric layer (assuming the thin ionospheric layer model). Its estimation from the SAR data itself is therefore also addressed. The methodology was applied and validated on simulated P-band data for various ionospheric conditions and on real L-band data acquired by the Advanced Land Observation Satellite Phased Array L-band SAR (PALSAR). [ABSTRACT FROM PUBLISHER]

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]

An iterative, generalized hybrid polarimetric decomposition, combining model-based and eigen-based techniques together with a generalized vegetation model, is developed for soil moisture retrieval under agricultural vegetation cover. The algorithm is physically based without the need of empirical calibration or fitting with auxiliary data and runs in two iterations. The algorithm is applied on L-band fully polarimetric data sets acquired by DLR’s E-SAR sensor. The flights were conducted within the AgriSAR, OPAQUE, and SARTEO campaigns carried out between 2006 and 2008 on three different test sites. The algorithm achieves inversion rates always higher than 95% for a variety of crop types at different phenological stages. The validation is performed against in situ time-domain reflectometry (TDR), frequency-domain reflectometry (FDR), and gravimetric measurements. The moisture levels range from 5 vol.% to 40 vol.%. The achieved root-mean-square error (RMSE) levels stay between 4.0 vol.% and 4.4 vol.% for all three sites across different vegetation and soil types, comprising the entire phenological cycle (e.g., April–July 2006). [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]

The European Space Agency is conducting studies for a low-earth orbiting polarimetric synthetic aperture radar called BIOMASS to provide global measurements of forest biomass and tree height. Phase scintillation across the synthetic aperture caused by ionospheric irregularities can degrade the impulse response function (IRF) and cause squinting, and its temporal variation can cause decorrelation in repeat-pass interferometry. These effects are simulated for a range of conditions for the baseline BIOMASS system configuration using the Wideband model of scintillation, which predicts that for a dawn-dusk orbit, impacts of scintillation over forest regions are negligible under all conditions except at high latitudes in the North American sector under high sunspot activity. In this sector, single-look IRFs have mean integrated sidelobe ratios (ISLRs) and peak sidelobe ratios (PSLRs) better than 0 and -5 dB, respectively, at 90% confidence interval under median solar activity up to the northern tree line ( ~ 70° geomagnetic). Degradation in the mean 3-dB resolution of up to 10% is predicted, with mean absolute azimuth shifts of the IRF peak of up to 2 m, which increases to 5 m at high sunspot number. Similar values are found for the dawn and dusk sides, and seasonal variations are negligible for latitudes below the tree line. Repeat-pass interferometric image pairs maintain coherence up to 50 ° N under median sunspot conditions. Four-look processing improves the ISLR and PSLR by several decibels, but causes significant degradation of the 3-dB resolution due to incoherent averaging of images with different random azimuth shifts. [ABSTRACT FROM PUBLISHER]

In this study, polarimetric synthetic aperture radar (SAR) parameters are analysed and compared within situmeasurements in order to develop a methodology for detecting cutting practices within grassland areas. The grasslands were monitored with TerraSAR-X radar imaging in dual polarization HH/VV mode and are located near the banks of the Kasari River, close to the Baltic Sea coast of Estonia. The parameters analysed include HH, VV, HH + VV, and HH – VV backscatter, HH/VV polarimetric coherence magnitude and phase, T12polarimetric coherence magnitude and phase, and also dual polarimetric entropy, alpha, and alpha dominant parameters. Using these parameters derived from the dual polarimetric TerraSAR-X data set, it was virtually impossible to distinguish tall grass (height >30 cm) from short grass (height <30 cm). On the other hand, it proved feasible to detect areas where grass had been cut and left on the ground. Several parameters showed specific behaviour for the state of grassland and the most notable change was found in the dual polarimetric dominant scattering alpha angle. This angle changed from 10° to 25° after tall grass had been cut and left on the ground. This behaviour of the dominant scattering alpha angle can effectively be described using a particle scattering model for vegetation backscattering. [ABSTRACT FROM AUTHOR]

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]

Temporal decorrelation is the most critical issue for the successful inversion of polarimetric SAR interferometry (Pol-InSAR) data acquired in an interferometric repeat-pass mode, typical for satellite or lower frequency airborne SAR systems. This paper provides a quantitative estimation of temporal decorrelation effects at L-band for a wide range of temporal baselines based on a unique set of multibaseline Pol-InSAR data. A new methodology that allows to quantify individual temporal decorrelation components has been developed and applied. Temporal decorrelation coefficients are estimated for temporal baselines ranging from 10 min to 54 days and converted to height inversion errors caused by them. The temporal decorrelations of \gammaTV (volume temporal decorrelation) and \gammaTG (ground temporal decorrelation) depend not only on the wind-induced movement but also strongly on the rain-induced dielectric changes in volume and on the ground at temporal baseline on the order of day or longer. At temporal baselines on the order of minutes, the wind speed is a critical parameter and the speed of 2 m/s already hampers the application of Pol-InSAR forest parameter inversion. The approach is supported and validated by using L-band E-SAR repeat-pass data acquired in the frame of three dedicated campaigns, BioSAR 2007, TempoSAR 2008, and TempoSAR 2009. [ABSTRACT FROM PUBLISHER]

During the last decade, synthetic aperture radar (SAR) became an indispensable source of information in Earth observation. This has been possible mainly due to the current trend toward higher spatial resolution and novel imaging modes. A major driver for this development has been and still is the airborne SAR technology, which is usually ahead of the capabilities of spaceborne sensors by several years. Today's airborne sensors are capable of delivering high-quality SAR data with decimeter resolution and allow the development of novel approaches in data analysis and information extraction from SAR. In this paper, a review about the abilities and needs of today's very high-resolution airborne SAR sensors is given, based on and summarizing the longtime experience of the German Aerospace Center (DLR) with airborne SAR technology and its applications. A description of the specific requirements of high-resolution airborne data processing is presented, followed by an extensive overview of emerging applications of high-resolution SAR. In many cases, information extraction from high-resolution airborne SAR imagery has achieved a mature level, turning SAR technology more and more into an operational tool. Such abilities, which are today mostly limited to airborne SAR, might become typical in the next generation of spaceborne SAR missions. [ABSTRACT FROM PUBLISHER]

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 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. However, due to the medium's complexity, SAR backscattering from ice remains poorly understood, including the relative importance of scattering from surface and volume layers and also dependences on frequency and glacier zone. Extreme weather conditions can result in quickly changing surface conditions influencing backscatter signatures while leaving the underlying volume of interest unchanged. Surface and volume components must thus be separated in order to infer information regarding the properties of the ice volume. This paper describes a three-component scattering model to decompose polarimetric SAR (PolSAR) images of glacier ice. Total backscatter is modeled as the incoherent summation of surface, volume, and sastrugi (wind-induced feature) components. The proposed model adapts and extends the Freeman and Durden decomposition for an ice volume scenario in which the volume is a dielectric medium. Forms of the model for both random and oriented volumes are considered, and a new oriented sastrugi component is introduced which is able to explain backscatter behavior between different winter scenes. Validation is performed with airborne PolSAR data at L- and P-band collected using the E-SAR system of the German Aerospace Center over the Austfonna ice cap in Svalbard, Norway, as part of the ICESAR campaign. [ABSTRACT FROM AUTHOR]

The knowledge of glacier zones' extent and their temporal variations is fundamental for the retrieval of surface mass balance of glaciers and ice sheets. In this context, a key parameter is the firn line (FL), the lower boundary of the percolation zone, whose location is an indicator of time-integrated mass balance changes. Several approaches have been developed in the last decades to map the FL by means of Synthetic Aperture Radar (SAR) imagery, mainly exploiting backscatter intensities and their seasonal variation. In this paper, an alternative approach is proposed, based on co-polarisation phase differences (CPDs). In particular, CPDs are interpreted as the result of propagation through anisotropic firn layers and are, therefore, proposed as an indicator of the presence of firn. A model is employed to demonstrate the link between CPDs and firn depth, indicating the potential of polarimetric SAR to improve firn characterization beyond spatial extent and FL detection. The proposed approach is demonstrated on L-band airborne data, acquired on 21 May 2015 by the F-SAR sensor of DLR in West Greenland during the ARCTIC15 campaign, and validated with in-situ information available from other studies. [ABSTRACT FROM AUTHOR]

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]

Synthetic Aperture Radar (SAR) measurements are unique for mapping forest 3D structure and its changes in time. Tomographic SAR (TomoSAR) configurations exploit this potential by reconstructing the 3D radar reflectivity. The frequency of the SAR measurements is one of the main parameters determining the information content of the reconstructed reflectivity in terms of penetration and sensitivity to the individual vegetation elements. This paper attempts to review and characterize the structural information content of L-band TomoSAR reflectivity reconstructions, and their potential to forest structure mapping. First, the challenges in the accurate TomoSAR reflectivity reconstruction of volume scatterers (which are expected to dominate at L-band) and to extract physical structure information from the reconstructed reflectivity is addressed. Then, the L-band penetration capability is directly evaluated by means of the estimation performance of the sub-canopy ground topography. The information content of the reconstructed reflectivity is then evaluated in terms of complementary structure indices. Finally, the dependency of the TomoSAR reconstruction and of its structural information to both the TomoSAR acquisition geometry and the temporal change of the reflectivity that may occur in the time between the TomoSAR measurements in repeat-pass or bistatic configurations is evaluated. The analysis is supported by experimental results obtained by processing airborne acquisitions performed over temperate forest sites close to the city of Traunstein in the south of Germany. [ABSTRACT FROM AUTHOR]

Focuses on synthetic aperture radar interferometric phase images and their noise filtering problem. Characteristics of phase noise; Information on cross-track radar interferometry; Characterization of the statistics of interferometric phase images.