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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]

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]

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]

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]

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]

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]

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.

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.

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]

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]

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]

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]

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]

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]

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]

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]

The estimation and monitoring of 3D forest structure at large scales strongly rely on the use of remote sensing techniques. Today, two of them are able to provide 3D forest structure estimates: lidar and synthetic aperture radar (SAR) configurations. The differences in wavelength, imaging geometry, and technical implementation make the measurements provided by the two configurations different and, when it comes to the sensitivity to individual 3D forest structure components, complementary. Accordingly, the potential of combining lidar and SAR measurements toward an improved 3D forest structure estimation has been recognised from the very beginning. However, until today there is no established framework for this combination. This paper attempts to review differences, commonalities, and complementarities of lidar and SAR measurements. First, vertical lidar reflectance and SAR reflectivity profiles at different wavelengths are compared in different forest types. Then, current perspectives on their combination for the generation of enhanced structure products are discussed. Two promising frameworks for combining lidar and SAR measurements are reviewed. The first one is a model-based framework where lidar-derived parameters are used to initialize SAR scattering models, and relies on both the validity of the models and on the physical equivalence of the used lidar and SAR parameters. The second one is a structure-based framework based on the ability of lidar and SAR measurements to express physical forest structure by means of appropriate indices. These indices can then be used to establish a link between the two kind of measurements. The review is supported by experimental results achieved using space- and airborne data acquired in recent relevant mission and campaigns. [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]

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]

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]

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]