The European Space Agency's (ESA) BIOMASS mission is a pioneering Earth observation satellite mission launched on April 29, 2025. Utilizing a P-band synthetic aperture radar (SAR), the objective of BIOMASS is to deliver estimates of above-ground forest biomass, forest height (FH), and forest disturbance (FD), with unprecedented accuracy. The mission's primary scientific goal is to quantify the distribution and changes in forest biomass, thereby reducing uncertainties in carbon flux estimates and informing climate models. The satellite's advanced instrumentation and innovative approach allow it to penetrate dense forest canopies, capturing data even in challenging environments. The mission will operate in two distinct phases: the tomographic phase and the interferometric phase, which will support polarimetric interferometric SAR (Pol-InSAR) and tomographic SAR (TomoSAR) processing. Additionally, BIOMASS will provide valuable observational data for ice sheets, deserts, the ionosphere, below canopy topography, and other domains.

Combining machine learning (ML) with physical models can significantly impact retrieval algorithms designed to invert geophysical parameters from remote sensing data. Such hybrid models integrate physical knowledge with domain expertise through a joint architecture, potentially enhancing performance by increasing the efficiency and flexibility of the physical model as well as the generalization and interpretability of the ML predictions. This work introduces a hybrid model for estimating forest height using single-baseline, single-polarization TanDEM-X interferometric coherence measurements. In this model, the vertical reflectivity profile is derived as a function of input features, including topographic and acquisition geometry descriptors, using a multilayer perceptron network. This profile is then used to invert forest height by leveraging the established physical relationship connecting the vertical reflectivity profile to forest height. The developed model is applied and validated on several TanDEM-X acquisitions over tropical sites with different acquisition geometries, and its performance is assessed against reference data derived from airborne LiDAR measurements.

This paper explores the use of Polarimetric SAR Interferometry (PolInSAR) in order to separate the Ground and Volume components of the SAR signal in the context of agricultural monitoring. This separation assumes a PolInSAR two-layer model and allows to extract the covariance matrix of each component. Then, a polarimetric change analysis technique may be employed to analyze independently the temporal evolution of the ground and volume components.The technique is evaluated with real data from the DLR’s F-SAR sensor CROPEX campaign, containing fully polarimetric PolInSAR data at L-, C- and X-band frequencies. Special attention is given to the validity of the PolInSAR two-layer volume at different frequencies and acquisition dates and the limitations of this separation technique.

As the potential of the radar polarimetry on the parametric observation of the Earth’s environment gets wider awareness, the interest in low-frequency SAR is growing for the Earth observation. For the purpose of environment monitoring using SAR polarimetry, the requirement for the accurate and operational polarimetric calibrations is getting increased, especially under the Faraday rotation (FR). This manuscript proposes a novel method for the cross-talk calibration under FR applicable to L- and P-band spaceborne SAR missions including three generations of ALOS PALSAR series, SAOCOM, NISAR, ROSE-L, as well as BIOMASS. One of the earliest ideas of Klein’s eigenvector regulation and the widely assumed condition of reflection symmetry have been extended to the FR-condition. The channel imbalance is assumed to be calibrated in precedent in order to focus on the cross-talk calibration issue.

Rapid changes in the Greenland Ice Sheet require precise elevation monitoring to understand ice dynamics and predict sea level rise. X-band Interferometric Synthetic Aperture Radar (InSAR) has the potential for this purpose but is limited by microwave signal penetration biases, which can be a few meters. We present a novel hybrid modeling approach that integrates machine learning (ML) with physical models to enhance the estimation of the elevation bias in InSAR data at X-band. Our method addresses the limitations of traditional physical modeling techniques by parameterizing the vertical structure function using a ML model. This approach combines machine learning as input for the physical model. The results demonstrate the improvements in correcting elevation biases, thus increasing the accuracy of X-band InSAR DEMs over Greenland. This advancement has the potential for more precise elevation estimation and ice-sheet monitoring.

In this letter, we discuss the estimation of the location of ionospheric irregularities exploiting the appearance of intensity scintillations in ALOS-2 images, as they are semifocused at different heights. The intensity scintillations (stripes) are not always visible in the single-look complex (SLC) images. However, they start to be visible, as the image is semifocused at different heights with a peak of contrast where electron density irregularities are found (ionospheric height). The slant range between the satellite and the ionospheric plane can be estimated and converted directly into the ionospheric height by autofocusing the stripes. The observations show good agreement with the height of maximum ionization estimated by the International Reference Ionosphere (IRI). Furthermore, we perform an alternative geometric validation based on feature tracking by comparing the shifts between azimuth sublooks. With both methods for the presented dataset, the height of the ionospheric irregularities was estimated to be 330 km.

Model-based forest height inversion from single- and multi-baseline polarimetric synthetic aperture radar interferometry (Pol-InSAR) data is today well-established. One of the critical performance points is the parameterization of the vertical reflectivity profile. In this article, the parameterization of the vertical reflectivity profile using a tomographic reconstruction is proposed. To mitigate the limitations in the tomographic reconstruction induced by the limited vertical resolution especially for the ground-scattering component, the ground and volume contributions are separated using the sum of Kronecker products (SKPs) decomposition. For the forest height inversion, the Pol-InSAR line inclination angle is proposed, which, unlike the absolute coherence and the phase center, is invariant to the presence of a residual Dirac-like ground-scattering contribution. The inversion performance is addressed and compared for both single- and multi-baseline cases, in the absence and presence of temporal decorrelation. In all cases, the ground elevation is estimated from the tomographically reconstructed vertical reflectivity profiles and its accuracy directly influences the achieved inversion performance. The proposed methodology establishes a link between interferometric and tomographic measurements and is therefore relevant for missions that allow the implementation of both techniques. ESA’s BIOMASS is one such mission, and as such is being used as a test case to discuss different implementation scenarios. The different inversion strategies are applied to P-band campaign data acquired in the frame of the AFRISAR 2016 experiment and validated against reference measurements.

This paper provides an overview of the state of the art and an outlook on future developments of spaceborne Synthetic Aperture Radar (SAR) systems with multi-baseline imaging capability, such as 3D differential SAR interferometry (3D-DinSAR), polarimetric SAR interferometry (Pol-InSAR), tomography (TomoSAR), and holography (HoloSAR). The goal is to fill the multidimensional data space with additional information from images with different spatial and/or temporal baselines.

The estimation of the interferometric vertical wavenumber over sloped terrain is an integral step for many interferometric and tomographic synthetic aperture radar (SAR) applications. The state of the art for this estimation is to calculate the angle of incidence and the local terrain slope after geometric corregistration has been performed. In this letter, an alternative approach for estimating the vertical wavenumber is proposed that requires only the estimation of the range corregistration shifts. This considerably simplifies the calculation effort without compromising the estimation performance. The proposed approach is demonstrated on Advanced Land Observing Satellite (ALOS) phased array L-band synthetic aperture radar (PALSAR) data and compared against the conventional methodology.

ESA Forest Carbon Monitoring project (FCM) is developing Earth Observation based, user-centric approaches for forest carbon monitoring. Forest carbon accounting based on forest inventory requires precise and timely estimation of forest variables at various spatial levels accompanied by verifiable uncertainty information. In this paper, we present the algorithm trade-off and selection approach and preliminary results of the algorithm intercomparison exercise in the FCM project. The studies were performed over 7 European test sites located in Finland, Ireland, Romania, Spain and Switzerland, and one tropical forest site in Peru. EO datasets were represented by Sentinel-1, Sentinel-2, TanDEM-X and ALOS-2 PALSAR-2 imagery. Examined approaches include popular parametric and SAR/InSAR scattering physics based approaches, and nonparametric and machine learning approaches such as k-NN, random forests, support vector regression.

The combination of TanDEM-X interferometric measurements with GEDI lidar full waveform measurements can provide continuous high-resolution forest height maps at global scale with sufficient accuracy without using external information about the underlyingtopography. In previous studies, the GEDI lidar full waveforms have been used to provide an approximation of the TanDEM-X X-band (radar) vertical reflectivity function in the height inversion of an entire TanDEM-X scene. This framework has been applied to the whole the whole Brazilian Amazon, and the obtained results are presented and analyzed in this paper. More than 12,000 TanDEM-X scenes and 250 millions GEDI lidar measurements have been processed.have.

Polarimetric SAR Interferometry (Pol-InSAR) is a SAR remote sensing discipline with unique and powerful applications related to the vertical structure of natural and man-made volume scatterers. The coherent combination of single- or multi -baseline interferograms acquired at different polarisations provides sensitivity to the vertical distribution of scattering processes and allows their characterisation by using the associated (volume) interferometric coherences.

Synthetic aperture radar tomography (TomoSAR) at lower frequencies allows the reconstruction of the 3-D radar reflectivity of volume scatterers allowing access to their physical 3-D structure by means of multiangular SAR acquisitions. The performance of the reconstruction critically depends on the number and (spatial) distribution of the tomographic acquisitions (tracks). This dependence is addressed in this letter with respect to forest applications (volume scatters) at L-band. The letter discusses the optimum definition of tomographic configurations based on the peak sidelobe level (PSL) of the point spread function (PSF). For demonstration, a tomographic data set consisting of 15 acquisitions acquired by the DLR’s F-SAR system at L-band over the Traunstein test site in Germany is used, complemented by airborne LiDAR measurements. Three different reconstruction algorithms (Fourier beamforming, Capon beamforming, and compressive sensing) are implemented and compared to each other for scenarios with a reduced number of acquisitions. Although the limitation of the specific forest, the results show the potential of using the PSL of the PSF to define tomographic configurations optimized for forest structure applications.

The TerraSAR-X add on for Digital Elevation Measurement (TanDEM-X) mission provides Interferometric Synthetic Aperture Radar (InSAR) wall-to-wall data (not sparse) at high resolution and at global scale. In addition, the NASA Global Ecosystem Dynamics Investigation (GEDI) is a new spaceborne system that provides (from 51.6°N and 51.6°S) sparse measurements (not images) through LiDAR waveforms. Both systems are sensitivity to the canopy structure such as the forest height but with their own limitations. The TanDEM-X single polarization (HH) interferometric coherence magnitude at X-band provides a continuous mapping of the forest while GEDI provides accurate (but sparse) measurements of the forest. In this paper a methodology of how to combine both systems to estimated forest height is presented and applied to more than 900 TanDEM-X scenes over Gabon in Africa. The forest height results over an area of 1° by 1° are shown and compared respect to GEDI. Finally, a wall-to-wall forest map over the entire country of Gabon is presented as an example of large scale mapping towards a potential global (entire earth) forest height map.

The realistic parameterization of the underlying (vertical) radar reflectivity profile is critical for a model-based inversion of forest height from polarimetric interferometric (Pol-InSAR) data. Indeed, an appropriate parameterization not only affects the final estimation performance, but also enables the inversion from a reduced observation space in terms of number of baselines and / or polarizations. Here, we investigate the possibility of using a full tomographic profile to parameterize the inversion. The proposed methodology is demonstrated and validated using Pol-InSAR and tomographic data acquired in the framework of relevant airborne campaigns.

Polarimetric SAR Interferometry (Pol-InSAR) is a SAR remote sensing discipline with unique and powerful applications related to the vertical structure of natural and man-made volume scatterers. The coherent combination of single- or multi -baseline interferograms acquired at different polarisations provides sensitivity to the vertical distribution of scattering processes and allows their characterisation by using the associated (volume) interferometric coherences [1]–[5].

Active microwave sensors, such as synthetic aperture radars (SARs), offer all-weather and daylight independent operability which is of great advantage for monitoring polar regions, where extreme environmental conditions and long period of darkness strongly limit other kinds of sensors. In addition, microwaves allow penetrating into dry snow and ice, making SAR measurements sensitive to the subsurface structure of glaciers and ice sheets. However, the retrieval of glacier subsurface parameters from SAR observations remains difficult due to their sensitivity to a large number of factors, including snow and ice properties, presence of layers, etc. The objective of this study is to attempt advancing the understanding of SAR measurements of glaciers and ice sheets. A combined analysis of polarimetric and tomographic measurements is carried out to derive a 3-D characterization of the scattering mechanisms occurring in a glacier subsurface scenario. The investigation exploits a fully-polarimetric tomographic airborne dataset, acquired over Greenland by the DLR's F-SAR system in the frame of the ARCTIC15 campaign.

The BIOMASS DEM Product Prototype Processor (BIO-DEMPP) is being developed in the frame of ESA's Earth Explorer BIOMASS mission. The prototype includes a complete interferometric SAR chain, from the stack co-registration until the mosaicking of the derived height products (Digital Elevation and Digital Terrain Models). This paper presents an overview of the BIODEMPP architectural design and its validation strategy, as well as first results obtained with simulated BIOMASS-like data.

Scheduled for launch in 2023, ESA's seventh Earth Explorer Mission, BIOMASS, will carry the first P-band synthetic aperture radar (SAR) to be flown in space, to gather fully polarimetric acquisitions over forested areas worldwide in interferometric and tomographic modes. This paper presents the algorithms developed to estimate biophysical parameters from BIOMASS measurements and their implementation in the BIOMASS level 2 (L2) prototype processor. The L2 processor will generate global maps of forest Above Ground Biomass (AGB), Forest Height (FH), Forest disturbance (FD). Accurate generation of these products requires the L2 processor to be closely inter-linked with the BIOMASS interferometric processor, in order to produce phase-calibrated interferometric stacks, retrieve sub-canopy terrain topography, and generate a 3D representation of forest structure by use of SAR tomography. AGB estimation results are here shown using BIOMASS-like acquisitions derived from campaign data acquired over six tropical forests in South America and Equatorial Africa.

This paper describes the rationale and development of the estimation techniques for the level-2 data products of the European Space Agency's 7th Earth Explorer BIOMASS mission. BIOMASS is planned for launch in 2023 and will carry the first-ever P-band synthetic aperture radar (SAR) onboard a satellite. It has been designed to produce consistent global maps of the Earth's forests during a nominal five-year lifetime. Fully polarimetric SAR data will be collected and the satellite orbit will be selected for repeat-pass interferometry and tomography in separated mission phases. Mission requirements call for three level-2 data products: above-ground biomass, forest height and forest disturbance. The paper also discusses the expected limitations of the estimation techniques and remaining problems to be addressed.

TanDEM-X experiments have shown that forest height can be estimated with single polarization X-band interferometric coherences. An external digital terrain model (DTM) not only allows to use both coherence magnitude and phase information, but also to overcome X-band penetration limitations. However, DTM information is not available for large areas. Using coherence magnitudes makes height inversion feasible, but it requires a model relating coherence to height. Here we report an experiment using the X-band local phase center variations. Results over a tropical forest site show that in those stands in which the low X-band penetration is not a limitation, the there is a good correlation between the obtained TanDEM-X heights and the heights from Lidar measurements.

SAR tomographic methods have proven extremely adept at measuring vegetation vertical structure at a variety of wavelengths including L and P-bands. The three dimensional structure of vegetation and its changes resulting from either natural or anthropogenic causes are key parameters in monitoring ecosystems. The NASA/JPL UAVSAR collected data at L and P-bands at Delta Junction, Alaska in September of 2017 whereas the NASA/JPL UAVSAR and DLR F-SAR acquired data at the BERMS site near Saskatoon, Canada on August 19 and 23 of 2018 respectively. Tomographic data sets were collected at L-band and P-band by the NASA/JPL UAVSAR at Delta Junction and at L-band at BERMS and DLR F-SAR acquired data at L-band and S-band. Ground truth data sets and lidar data from the NASA LVIS system were also acquired at BERMS. We compare L and P tomography at Delta Junction and L-band and S-band tomography from the two systems to each other and to the lidar data sets at BERMS. These data are then used to estimate biomass and assess spatial gradients in the canopy vertical structure. We also compare our data with simulated boreal forest data to assess the sensitivity to the data collection geometry and canopy parameters.

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.

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.

This work introduces a methodology to separate the ground and volume contributions from Polarimetric SAR Interferometric acquisitions. Based on the employed two layer model, the radar response may be decomposed into these two main contributions and the polarimetric covariance matrices of the corresponding ground and volume layers may be extracted from the data. The technique will be evaluated with a real single- and multi-baseline fully Polarimetric SAR data acquired by the E-SAR airborne sensor over forest.

The ESA BIOMASS mission will be the 7th Earth Explorer measuring the above-ground biomass (AGB) in the world's forests. The current ESA Level-2 (L2) implementation study focuses on defining and implementing the main algorithms for forest parameter retrieval from BIOMASS data. After the first year of L2 study innovative results were achieved: the development of ground cancellation, in particular, has proved to be huge value, since it removes from the data the effects of environmental variability and contributions unrelated to the forest carried in the ground scattering. In this paper the current processor implementation and validation activities of the L2 team will be described.

NASA's Global Ecosystem Dynamics Investigation (GEDI) waveform lidar is expected to provide unprecedented measurements of forest structure and biomass in tropical and temperate environments. In order to bridge the limitations induced by the ground sampling of the GEDI waveforms, and to obtain enhanced forest structure estimates, the potential of combining TanDEM-X (high resolution) singlepass interferometric coherences and lidar waveforms is currently investigated. In this work, a combination framework based on the ability of lidar and TanDEM-X measurements to express physical forest structure by means of appropriate indices is discussed. In particular, commonalities and complementarities between the different measurements are addressed by means of experimental results obtained in temperate and tropical forest sites in which comparisons among structure indices from lidar, T anDEM-X and field inventories can be established.

Digital elevation models generated with SAR interferometry (InSAR) are an important information source for glacier and ice sheet mass balance. However, the measured elevations suffer from a penetration bias due to the interferometric phase center being up to several tens of meters below the surface. The penetration of the microwave signals depends on SAR parameters (e.g. frequency) and snow and ice conditions. There is potential to estimate this penetration bias directly from the data by means of polarimetric InSAR models. Existing models fail to describe the data across different test sites and ice conditions and phase centers were found to be deeper than predicted by these models. SAR tomography is employed to assess the vertical distribution of backscattering in the data from an airborne campaign. The data are compared to refined models in order to find better representations of the vertical backscattering distribution, while the model complexity is purposely kept simple to make a phase center estimation possible. Additionally, recent work showed the importance of strong subsurface layers which influence phase center depth. Combining the refined subsurface structure models and dominant subsurface layers allows simulating a variety of ice sheet subsurface scenarios and can be used to assess the potential to estimate the InSAR phase center depth directly from the data.

A methodology that allows the separation of Faraday Rotation (FR) distortion from system induced distortion for the calibration of spaceborne polarimetric data is proposed and discussed. The separation is based on the azimuth variation of the FR and relies on the assumption that the antenna patterns are sufficiently well characterized.

Steep terrain presents a challenge in soil moisture estimation. In this paper, we illustrate the necessity of polarization orientation angle compensation for soil moisture estimation based on Bragg scattering. We also emphasize the importance of local incidence angle for soil moisture estimation. We found that azimuth slopes cause underestimation, but range slopes can cause over- or underestimated soil moisture depending on range slopes being positive or negative. Theoretically, if both azimuth and range slope measurements are available, soil moisture level can be retrieved precisely. However, to achieve this, a coregistered DEM is indispensable.

The objective of this paper is to address the penetration capabilities of different synthetic aperture radar (SAR) frequencies in forest scenarios in terms of "visibility" of the ground. First, the ratio between the ground and the volume scattering powers is estimated from multi-baseline polarimetric interferometric (Pol-InSAR) data across different forest types. Afterwards, the resulting performance in the estimation of the ground height is characterized by comparing algorithms based on either the identification of the ground scatterer in tomographic profiles, or on the inversion of a model. This analysis is supported by experimental results obtained with multi-frequency, multibaseline Pol-InSAR data acquired by the DLR's E-/F-SAR airborne platforms over different forest types.

The need of large scale observations with high temporal frequency has promoted airborne and satellite remote sensing techniques for glaciological applications. In particular, active microwave sensors, such as synthetic aperture radars (SARs), offer all-weather and daylight independent operability which is of great advantage at high latitudes, where extreme environmental conditions and long period of darkness strongly limit other kinds of sensors. Moreover, longer wavelengths allow to penetrate significantly into dry snow and ice, interacting with surface as well as subsurface features. On the one hand, this makes SAR measurements suitable to investigate the subsurface structure of glaciers and ice sheets. On the other hand, the complex interaction of microwaves with the subsurface layers makes the interpretation of SAR measurements challenging. This study investigates the potential of SAR techniques to retrieve information about glacier subsurface. SAR polarimetry and tomography are used to gain a 3-D characterization of the scattering scenario of the K-transect, a site located in the ablation zone of Greenland. For this, a fully-polarimetric tomographic airborne dataset, acquired by the DLR's F-SAR system in the frame of the ARCTIC15 campaign, is exploited.

The structure of forests, in terms of mass and the three-dimensional arrangement of individual trees, is a direct indicator of how much carbon is stored in the ecosystem, which in turn, has a profound effect on how the ecosystem functions and cycles carbon, water, and nutrients (Shugart et al., 2015). There is an increased need to understand local to global storage and dynamics of carbon in terrestrial vegetation, as carbon storage is a prerequisite to understanding the coupling of the biosphere to other components of Earth systems including the climate. The BIOMASS mission of the European Space Agency (ESA), to be launched in 2021-2022 will provide, for the first time, synthetic aperture radar measurements at P-band frequency (~70 cm wavelength) and tomographical (TomoSAR) imaging capability to quantify forest structure and above ground biomass.

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.

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 ΛαB/αBmethod but without any scattering assumption. Theoretical analyses and discussions are provided. Experiments show that the proposed method is efficient for compact polarimetric scattering interpretation.

Synthetic Aperture Radar Tomography techniques provide 3D information of the forest due to the ability of microwaves to penetrate through vegetation. Recent studies link the radar 3D information to forest 3D structure in order to translate the tomographic results to an ecological interpretation. However, due to the undersampled nature of tomographic acquisitions, the number and distribution of acquisitions can change the estimated 3D radar reflectivity and as a consequence the forest structure estimates. This paper explores the results for radar as well as for forest structure for different number and distribution of acquisitions in order to analyse the potential and limitations of the estimation of forest structure in future space borne scenarios where the number and distribution of acquisitions will be suboptimal. In this context, the paper analyses a tomographic campaign of 15 tracks acquired over Traunstein (Germany) in 2017 together with ground measurements and Lidar.

Recent TanDEM-X experiments have shown that the limited penetration capability at X-band in forest volumes allow the estimation of the height variability of the top canopy layer, which can be used as a proxy to the horizontal structure (i.e. heterogeneity), by using high resolution digital elevation models (DEMs). However, the use of an external digital terrain model (DTM) is necessary to separate the (high resolution) canopy height variations from the topographic ones. In this work, the possibility of compensating terrain topographic variation by using a low resolution TanDEM-X DEM instead of an external DTM is investigated. The results show that the use of a reference DEM with a resolution on the order of 100 m allows to compensate the terrain-induced topographic variations and to preserve the information on forest horizontal heterogeneity at a large extent.

In this paper, polarimetric multi-baseline (MB) Synthetic Aperture Radar (SAR) Interferometry data are used to estimate the polarimetric ground component under vegetation. However, the solution of the applied separation algorithm is not unique and depends on the constraints in the regularization. First, the effect of this non-uniqueness is analyzed and then exploited to isolate a ground component with minimized influence of depolarizing scattering mechanisms. Using experimental MB SAR data acquired by DLR's airborne sensor F-SAR, the polarimetric entropy and mean alpha angle of the isolated ground component are compared to the original polarimetry of the full image. Finally, the ground polarimetry is interpreted for changing soil moisture vegetation conditions in corn. To this purpose, three dates are compared characterized by 1) a change in soil moisture, 2) a change in vegetation cover or 3) a simultaneous change of soil moisture and vegetation cover.

Ionospheric parameters e.g., ionospheric height, TEC and the level of disturbances, are estimated using L-band SAR data acquired by ALOS-2 PALSAR-2 over Fairbanks, Alaska. These parameters are compared with coinciding ground-based monitoring data form the Poker Flat Incoherent Scatterer Radar (PFISR) and keograms measured by the University of Alaska, Fairbanks. The comparison results are discussed.

Tandem-L is a proposal for an innovative L-band SAR mission for the systematic observation of dynamic processes on the Earth's surface. The mission concept is based on two SAR satellites flying in close formation featuring latest digital beamforming techniques in combination with a large deployable reflector for increasing the swath width and imaging resolution. This enables innovative operation modes such as polarimetric SAR tomography for determining the vertical structure of vegetation and ice. With novel imaging and processing techniques and the vast recording capacity of up to 8 Terabyte/day, it will provide vital information for solving pressing scientific questions in the biosphere, geosphere, cryosphere, and hydrosphere and will make an essential contribution for a better understanding of the Earth system and its dynamics. This paper gives an overview of the Tandem-L mission project which has successfully passed the intermediate system requirements review of Phase B1.

Interferograms at different polarisations form the basis of Polarimetric SAR Interferometry (Pol-InSAR), a radar remote sensing technique which uses the coherent combination of interferometric and polarimetric information to characterise and estimate structural parameters of natural and man-made (volume) scatterers. In the frame of the BIOMASS mission Pol-InSAR techniques are used to estimate yearly (top canopy) forest height on a global scale with a spatial resolution of 100 × 100 m2 and with an accuracy of 20-30%. The model based estimation is based on the Pol-InSAR data acquired by BIOMASS: three quad-polarimetric acquisitions (separated by 3 or 4 days from each other, with a constant progression on the order of 40% of the critical baseline) acquired in ascending and in descending geometry twice a year.

Polarimetric SAR Interferometry (Pol-InSAR) is a SAR remote sensing discipline with unique and powerful applications related to the vertical structure of natural and man-made volume scatterers. The coherent combination of single- or multi-baseline interferograms acquired at different polarisations provides sensitivity to the vertical distribution of scattering processes and allows their characterisation by using the associated (volume) interferometric coherences [1]-[5].

Space borne implementations of SAR tomography (TomoSAR) for forest volumes are particularly challenging, as the estimation of 3D reflectivity has to be carried out relying on a small number of acquisitions (or interferometric coherences) and/or non-uniform baseline distributions. A way to overcome this shortcoming is to approximate the reflectivity profile by a weighted series of functions, as for example proposed in the case of Polarization Coherence Tomography (PCT). In this case the individual weights can be estimated from a rather small number of interferometric coherences. In this work, we investigate how conventional TomoSAR can be linked to PCT by means of a suitable function basis. A real data analysis is carried out on TomoSAR reflectivity profiles obtained from a data set acquired in an airborne campaign over a temperate forest.

The BIOMASS mission gives completely new challenges in external calibration arising from the orbital pattern needed for the tomographic and Pol-InSAR phases of the mission, the strong effects of the ionosphere at P-band, and the lack of pre-existing P-band data except over very limited parts of the globe. Together these create problems that can only be solved by combining infrequent visits to instrumented calibration sites with systematic exploitation of the properties of distributed targets and targets of opportunity. Proposed approaches to performing radiometric and polarimetric calibration are described, together with meeting geolocation accuracy requirements.

The Earth Explorer Biomass mission will provide the scientific community with accurate maps of tropical, temperate and boreal forest biomass, including height and disturbance patterns. This information is urgently needed to improve our understanding of the global carbon cycle and to reduce uncertainties in the calculation of carbon stocks and fluxes associated to the terrestrial biosphere. It is also crucial for approaches to managing climate, such as the UNFCCC initiative known as Reducing Emissions through Degradation and Deforestation (REDD+), aimed at climate change mitigation through conservation and better management of tropical forests The required measurements are forest biomass and forest height at resolution of 200 m, and detection of deforestation at 50 m. Global maps of biomass are required with accuracy of 20% (or l0 t ha-1when above-ground biomass are less than 50 t ha-1). To achieve this Biomass will be implemented as a P-band SAR mission. It will exploit the unique sensitivity of P-band SAR together with advanced retrieval methods including polarimetric interferometry (Pol-InSAR) and SAR tomography to measure biomass, height and disturbances across the entire biomass range every 6 months. The mission will also support important secondary objectives, including sub-surface imaging in arid zones, production of a bare-earth DTM and ice applications.

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.

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).

The vertical structure of firn below the surface of the Greenland ice sheet is driven by meteorological conditions like the intensity and duration of melting periods. The formation of ice inclusions through meltrefreeze processes leads to strong scatterers whose vertical distribution influences interferometric coherences. Interferometric coherence profiles from quad-pol SAR data show clear sensitivity to the different subsurfaces of two test sites with different melting periods. The differences in coherence are explained in this study through modelling of the different vertical subsurface structures supported by ground penetrating radar measurements. The shown sensitivity demonstrates the potential of polarimetric SAR interferometry to retrieve information about meltrefreeze processes and layering below the surface of ice sheets.

Polarimetric SAR Interferometry (Pol-InSAR) is a SAR remote sensing discipline with unique and powerful applications related to the vertical structure of natural and man-made volume scatterers. The coherent combination of single-or multi-baseline interferograms acquired at different polarisations provides sensitivity to the vertical distribution of scattering processes and allows their characterisation by using the associated (volume) interferometric coherences [1][2][3][4][5].

A methodology that allows the separation of Faraday Rotation (FR) distortion from system induced distortion for the calibration of spaceborne polarimetric data is proposed. The separation is based on the frequency dependency of the FR across the system bandwidth and relies on the commonly used assumption that system distortions are frequency independent. A calibration schema appropriate for the calibration of polarimetric data in the presence of FR is proposed. The proposed methodology is applied and demonstrated on ALOS-2 data.

AfriSAR is an ESA-funded airborne P- and L-band SAR campaign over the African tropical forests of Gabon carried out by ONERA (July 2015) and DLR (February 2016). The different acquisitions were designed in order to collect multibaseline fully polarimetric data allowing the inversion of key forest vertical structure-based parameters, like e.g. forest height and high resolution reflectivity profiles. Results of processing and parameter inversion with the DLR's F-SAR data are shown in this paper at both P- and L-band.

The purpose of this paper is to investigate how SAR Tomography (TomoSAR) can be used to estimate ground polarimetric covariances in forest scenarios in order to increase the amount of information that can be extracted from SAR data stacks is beyond the vertical reflectivity profiles. Under the hypothesis of a two-layer model composed by ground and volume contributions, an algorithm is proposed that makes use of an a priori knowledge of the ground height. The performance in the estimation of the ground polarimetry is investigated with respect to frequency and accuracy of the ground height estimated from the TomoSAR stack. This analysis is carried out by processing an L- and a P-band TomoSAR data stacks acquired by the DLR's E-SAR sensor over the temperate forest of Traunstein.

TanDEM-X forms together with TerraSAR-X the first single-pass polarimetric interferometer in space. This allows for the first time the acquisition and analysis of Single-, Dual-, and Quad-Pol-InSAR data without the disturbing effect of temporal decorrelation globally. For this reason, the exploration of TanDEM-X data for forestry is constantly increasing especially concerning forest height estimation, biomass classification and structure characterization. This paper reports the results of recent experiments aimed at investigating the potentials of TanDEM-X in characterizing quantitatively the spatial variability of the canopy top and phase center height, which is a proxy to horizontal structure. It is shown that such characterization can allow to differentiate among e.g. different successional and / disturbance stages in tropical forests.

In this work, we discuss the retrieval of information about the vertical structure of the ionospheric phase by means of Multi-Squint Interferometry (MSInSAR). A model of the MS phase is proposed that accounts for multiple ionospheric layers and residual topographical terms. This model is then generalized to the case of a continuous distribution, which can be retrieved from the MS phase via a 2D Fourier Transform. Moreover, we demonstrate the possibility to single out the phase screen at each layer, plus the residual topographic phase. The inversion procedure is demonstrated through numerical simulations, based on BIOMASS system parameters.

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.

A two-layer model composed by ground and volume contributions has been proven suitable to describe the 3-D backscattering signatures of forest scenarios in a number of experiments. Under this hypothesis, the purpose of this letter is to investigate how synthetic aperture radar tomography (TomoSAR) can be used to estimate ground and volume polarimetric covariances and with which performance. An algorithm which is able to overcome the intrinsic ambiguity in the estimation problem is proposed, and it is shown to be a reliable alternative to the poorly performing full-rank Capon beamformer for estimating the ground polarimetric covariances. This performance improvement can be achieved, for instance, if an a priori knowledge of the ground topography (or an accurate estimate of it) is available. This analysis is carried out by processing an L-band TomoSAR stack acquired by the DLR's E-SAR sensor over the temperate forest site of Traunstein.

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.

The standard TanDEM-X baselines have been designed to optimize the high resolution global Digital Elevation Model (DEM) generation. However, during the Science Phase of the mission longer baselines are available. This allows interferometric measurements with a higher vertical sensitivity, more appropriate for agricultural applications, where the crop heights are too small to be properly detected and analyzed with the standard baselines. This paper evaluates the use of the experimental long baseline TanDEM-X acquisitions for the monitoring of the agricultural changes in dual-pol single-pass interferometric time series.

AfriSAR is an ESA-funded airborne P-band SAR campaign over the African tropical forests of Gabon that is being carried out by ONERA (July 2015) and DLR (February 2016) in support of the development of the geophysical algorithms of the future BIOMASS mission. Multibaseline fully-polarimetric acquisitions have been designed over four test sites in order to further develop and validate algorithms for the estimation of forest upper canopy height, 3-D structure and biomass by implementing PolSAR (SAR Polarimetry), Pol-InSAR (Polarimetric SAR Interferometry) and TomoSAR (SAR Tomography) P-band measurements. In this paper first data processing results will be shown.

Recent studies indicate the potential of low frequency space-borne SAR sensors to monitor and quantify structure and dynamics of ionosphere [1-3]. At the post-sunset sector of the equatorial ionosphere, the instability of the electron density often induces plasma bubbles aligned to the geomagnetic field [4], whose effects are seen as distinctive stripe patterns on SAR data [5-6]. At the same time, the free-electrons in this sector of ionosphere drift eastward [7]. This paper explores this effect captured on ALOS and ALOS-2 SAR data to estimate the drift velocity and altitude of the bubbles [8]. Based on the azimuth sub-band of SAR data analysis the height and velocities are estimated, and compared to the measurements from ionosonde. The sensitivity of the estimates is analyzed, and finally a possible observation configuration for further ionospheric study is proposed.

Tandem-L is a highly innovative SAR satellite mission for the global observation of dynamic processes on the Earth's surface with hitherto unknown quality and resolution. Thanks to its novel imaging techniques and its unprecedented acquisition capacity, Tandem-L will deliver urgently needed information for the solution of pressing scientific questions in the areas of the biosphere, geosphere, cryosphere and hydrosphere. The feasibility of Tandem-L has been analyzed and confirmed in the scope of a phase A study, which has been conducted in close cooperation between the German Aerospace Center (DLR) and the German space industry. This paper provides an overview of the Tandem-L mission concept and summarizes the actual development status.

This paper provides an overview of the future development of spaceborne SAR systems with multi-baseline imaging capability like polarimetric SAR interferometry (PolInSAR), tomography (TomoSAR) and holography (HoloSAR). The goal is to fill the multi-dimensional data space with additional information from acquisitions having different spatial or temporal baselines. Multi-baseline imaging opens the door for a new class of image products in spaceborne SAR. Well-known examples are across-track and along-track interferometry, which allow the measurement of surface topography, ground deformation, ocean currents as well as glacier movements. While across-track and along-track interferometry are well established techniques and have been widely used by current spaceborne SAR systems, PolInSAR, TomoSAR and HoloSAR are emerging techniques which are shaping the future development of spaceborne SAR. New mission concepts for multi-static SAR configurations with distributed and sparse arrays will pave the way for this development.

In this paper the Pol-InSAR calibration - including coherence, phase and ionospheric calibration - of ALOS-2 is addressed based on repeat-pass fully polarimetric interferometric SAR data acquired over different sites during the CAL-VAL phase. ALOS-2, launched in May 2014, provides the possibility to demonstrate quantitative Pol-InSAR techniques from space over a wide range of test sites. Compared to ALOS-PalSAR, the increased bandwidth, reduced NESZ level and the shortened interferometric repeat-pass time promises a significantly increased potential of ALOS-2 for Pol-InSAR applications.

Polarimetric SAR Interferometry (Pol-InSAR) is a SAR remote sensing discipline with unique and powerful applications related to the vertical structure of natural and man-made volume scatterers. The coherent combination of singleor multi-baseline interferograms acquired at different polarisations provides sensitivity to the vertical distribution of scattering processes and allows their characterisation by using the associated (volume) interferometric coherences [1][2][3][4][5]. Pol-InSAR is today a well established technique that promises a break-through in solving essential radar remote sensing problems. Indeed, structural parameters of volume scatterers in the biosphere and cryosphere such as vegetation height, structure, biomass, snow depth, and ice layering are today critical inputs for ecological process modeling and enable monitoring and understanding of eco-system change. In this paper we review the actual status of PolInSAR techniques and applications in forestry, agriculture and cryosphere; assess results from actual space (TanDEM-X) and air-borne (F-SAR) campaigns and experiments at different frequencies; and finally discuss new potential applications and challenges.

Systems based on Synthetic Aperture Radar Tomography at low frequencies offer 3D imaging capabilities, appropriate for forest monitoring. However the extraction of an ecologically meaningful measure of forest structure from the 3D reflectivity is not straightforward and several considerations need to be carefully taken into account, in order to avoid misinterpretations of the nature of the information reflected in the tomograms. Besides, it should be noted that the methodology employed in the TomoSAR inversion has a significant effect on the overall performance of the TomoSAR system to estimate forest structure. In this framework, this paper discusses the potential and limitations of TomoSAR systems for forest structure estimation.

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.

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 hemiboreal (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 × 16 m.

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.

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 non-volumetric 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 1.2zhVzis 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 (Δσ = σVV- σHHbetween 0.7 and 1 dB/m) and rape (Δσ = -0.8 dB/m) canopies at L-band.

In this study application results are presented derived from multi-parametric SAR observations covering five different thematic domains: forest, agriculture, ocean, urban and cryosphere. In total 21 application products have been selected and described. Their application on different data sets, space- and airborne sensors, was demonstrated and can independently be reproduced by any scientist. The results and algorithms are available soon through Springer.

ALOS-Next/Tandem-L is a proposal for a highly innovative L-band SAR satellite mission for the global observation of dynamic processes on the Earth's surface with hitherto unparalleled quality and resolution. It is based on a collaboration between DLR and JAXA which started with a pre-phase A study in 2013 and is currently undergoing a phase A study. Thanks to the novel imaging techniques and the vast recording capacity with up to 8 Tbytes/day, it will provide vital information for solving pressing scientific questions in the biosphere, geosphere, cryosphere, and hydrosphere. By this, the new L-band SAR mission will make an essential contribution for a better understanding of the Earth system and its dynamics. ALOS-Next/Tandem-L will, moreover, open new opportunities for risk analysis, disaster management and environmental monitoring by employing especially designed acquisition modes and techniques in combination with a reconfigurable tandem satellite configuration and an L-band SAR instrument with advanced digital beamforming techniques.

Continuous development, experimentation and validation activities with airborne campaigns pushed towards the proposal of spaceborne missions that could implement SAR Tomography (TomoSAR) on a global scale. Together with innovative SAR imaging modes, TomoSAR plays an essential role in forest mapping for the characterization of 3-D structure and its dynamics at high spatial and temporal resolutions. In this framework, the characterization of the structure information content of multibaseline (MB) data stacks is of fundamental importance in order to shape both system design and acquisition concepts. In this paper, MB acquisition tradeoffs are analysed in representative forest scenarios fixing a given performance in the estimation of the parameters characterizing the vertical structure. In addition, the benefit against temporal decorrelation of repeated MB single-pass interferometric acquisitions is quantified with respect to repeat-pass acquisitions, and the role of polarization is discussed.

The paper introduces a new polarimetric scattering model able to interpret and invert coherent polarimetric SAR (PolSAR) measurements over glaciers and ice sheets. Individual scattering components related to ice lenses and pipes are considered to model the subsurface scattering structure of ice sheets. The model is able to interpret the scattering amplitudes, their ratios at the different polarizations as well as the observed polarimetric phase differences. The co-polarization (HH-VV) phase difference is related to the structural anisotropy of the firn layer and will be used to estimate its thickness. The model is validated against L-band PolSAR data acquired by the E-SAR sensor of the German Aerospace Center (DLR) over the Austfonna ice cap in Svalbard during the ICESAR2007 campaign and available GPR profiles.

Synthetic Aperture Radar Tomography provides the 3D reflectivity of the observed scene. Hence, in a forest scenario, it reflects information relevant to forest structure. However, how and to which extent this information is reflected and which are possible ways to quantify it are still open questions. This paper explores the link between ecological measures of forest structure and the 3D spatial distribution of the peaks in the reflectivity profiles at L-band and, with this, proposes measures for forest structure estimation from tomographic SAR data.

Forest height is an important parameter for the allometric estimation of above-ground forest biomass (AGB). However, variable forest stand densities limit the performance of the allometric estimation of AGB from height measurements alone. Recently, the use of vertical forest structure information as an indicator for the variation of stand density has been proposed and used to improve the allometric estimation of AGB from height measurements. In this letter, the use of vertical radar reflectivity profiles at L-band obtained from SAR tomography, as a proxy for vertical forest structure for the allometric estimation of AGB, is investigated. L-band reflectivity profiles, which are reconstructed from data at different polarizations (HH and HV) and acquired under “moist” and “dry” weather conditions, are investigated. The proposed allometric AGB estimator increases the correlation factor from 0.60 to 0.81 and reduces the root-mean-square error from 50.25 to 36.30 Mg/ha when compared with the AGB estimation from forest height alone. The effect of polarization and weather conditions on the AGB estimation performance is discussed.

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).

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.

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.

One common method to estimate biomass is measuring forest height and applying allometric equations to get forest biomass. However, changing forest density or forest structure bias the known allometric relations. Remote sensing systems like SAR or LIDAR allow to measure vertical forest structure. In this paper the value of vertical forest structure information for biomass inversion is investigated. First, vertical biomass profiles are calculated from forest inventory data. Then, a vertical structure descriptor based on Legendre polynomials is suggested and its sensitivity to biomass is evaluated. In a second step, this descriptor is used to describe SAR vertical reflectivity profiles. Then, a biomass estimation algorithm is developed. This is a case study based on inventory data from the Traunstein test site, a temperate mixed forest, located in the southeast of Germany.

L-band fully polarimetric SAR data, acquired within several airborne measurement campaigns from 2006 to 2013 over Germany, are used for soil moisture estimation at high spatial resolution and under distinct agricultural vegetation cover. The fully polarimetric L-band data were acquired by DLR's E-SAR and F-SAR sensors in order to investigate their potential for soil moisture retrieval. A newly developed, iterative, generalized, hybrid decomposition and inversion approach is applied for a flexible soil moisture estimation under a temporally and spatially varying agricultural vegetation. Therefore an iteration-adaptive, generalized scattering model of the vegetation is used. First results of the inverted soil moisture under vegetation cover reveal high inversion rates for the agricultural test sites (>95%). The inverted soil moistures are validated with in situ measurements from simultaneously conducted field campaigns leading to a minimum root mean squarer error (RMSE) of 4.1vol.% for a variety of crop types and in situ moisture conditions (ranging from 5vol.% to 40vol.%).

Synthetic aperture radar (SAR) waves have the capability of penetrating into forest volumes. Multibaseline (MB) polarimetric-interferometric SAR (PolInSAR) systems can retrieve information about the vertical distribution of the radar backscattered power and to relate it to the physical 3-D forest structure of the vegetation. Radar backscattering from forests can change in time due to different weather conditions, to seasonality, and to logging or disturbances. In this paper, experiments with L-band and X-band data are presented for a first characterization of the related effects in the estimated 3-D forest structure parameters.

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 glaciers surface through the shallow snow cover, interacting with surface as well as sub-surface 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 (PolSAR), the understanding of polarization phase differences represent one of the main open issues. In this paper, a physical model is employed to relate co-polarization HH-VV phase difference (co-pol phase) to structural and dielectric properties of snow and firn which characterize the first meters of glaciers subsurface. Modelled co-pol phase values are compared to values measured in experimental airborne L-band (1.3 GHz) SAR data, acquired over the Austfonna ice-cap, in Svalbard, in spring 2005 and 2007. A set of ground measurements is also exploited to properly set up the model and to validate the results. Finally, an interpretation of co-pol phase temporal variations over the period 2005-2007 is attempted based on the proposed model.

This study assesses the potential of single-pass TanDEM-X interferometric SAR (InSAR) data to map forest canopy height, when a corresponding accurate digital terrain model (DTM) is available. In the proposed method, the forest canopy height model (CHM) is extracted by subtracting an airborne lidar DTM from the TanDEM-X digital surface model (DSM). We showed that the TanDEM-X coherence is influenced by local incidence angles and tree basal area. These factors should be taken into account when estimating forest canopy height using TanDEM-X combined to lidar data.

In the frame of the Biomass mission activities, this paper presents the challenges and recent results in the retrieval of forest biomass from polarimetric (PolSAR) and interferometric (PolInSAR) P-band SAR data. During the mission Phase A, critical issues in the biomass retrieval algorithms in boreal and tropical forests have been identified and addressed. In boreal forest, multi polarization backscatter data can be used to mitigate much of the variability due to environment effects. In high biomass tropical forest, because of the low sensitivity of the backscatter to biomass, appropriate correction methods were developed to mitigate the disturbing effects. Also to enhance the retrieval results, a combination of PolSAR and PolInSAR methods was proposed.

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 r2between 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.

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${-}{\rm 5}~{\rm dB}$, respectively, at 90% confidence interval under median solar activity up to the northern tree line (${\sim}{\rm 70}^{\circ}$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${>}{\rm 0.8}$up to 50$^{\circ}~{\rm N}$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.

A recently published hybrid decomposition and inversion approach is adapted and enlarged using a generalized scattering model of the vegetation volume for a refined and more flexible soil moisture estimation under a temporally and spatially varying agricultural vegetation cover. Fully polarimetric SAR data of DLR's E-SAR system at L-band are used as observation basis. The results for the AgriSAR campaign, carried out in 2006 within the Peene catchment, reveal a detailed inversion due to the pixel-based procedure and very high inversion rates (>95%) obtaining a gapless inversion along the entire growth cycle in strongly varying agricultural areas. The validation with in situ measurements for a plurality of summer and winter crops states a root mean square error of 4.55vol.%, while a wide moisture range (~2-30vol.%) is covered by the refined soil moisture inversion under vegetation using solely polarimetric SAR techniques.

TanDEM-X (TDX) forms with TerraSAR-X (TSX) the first single-pass synthetic aperture radar (SAR) interferometer in space with polarimetric capabilities. The availability of such system allows for the first time the acquisition and analysis of X-band Pol-InSAR data from space without the disturbing effect of temporal decorrelation. After two years of mission, time series with variable baseline over the same forest sites are available, allowing to (1) explore their information content, (2) assess penetration capabilities, (3) assess scattering model assumptions, and (4) estimate vertical structure and monitor its dynamics. This paper discusses for the first time the potential of estimating forest vertical structure from spaceborne single-pass interferometers, extending classical tomographic concepts. Results of first experiments with TSX/TDX multibaseline Pol-InSAR data acquired over the Tapajos national forest (Brazil) are shown. Especially regarding tropical forests, potentials and applications of X-band for forest structure monitoring will also be discussed.

The F-SAR airborne SAR instrument represents the successor of the E-SAR system of the German Aerospace Center (DLR), which has been extensively used in the last three decades. Its development was triggered by the current demand for data being simultaneously acquired at different wavelengths and polarisations, as well as by the demand for very high resolution in the order of decimetres. F-SAR is a modular development utilising the most modern hardware and commercial off the shelf components. F-SAR is designed to operate fully polarimetrically at X-, C-, S-, L- and P-bands and provides single- pass polarimetric interferometric capabilities in X- and S-bands. Additionally, up to four bands can be acquired simultaneously, partly even in polarimetric acquisition modes. This paper aims to present and evaluate the advanced multi-frequency polarimetric capabilities of the F- SAR system, as well as first results of single-pass polarimetric interferometry at X- and S-band.

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.

The estimation of volumetric soil moisture under low agricultural vegetation from fully polarimetric synthetic aperture radar (SAR) data at L-band using a multi-angular polarimetric decomposition is investigated. Radar polarimetry provides the framework to decompose the backscattered signal into different canonical scattering mechanisms referring to scattering contributions from the underlying soil and the vegetation cover. Multi-angular observation diversity further increases the information space for soil moisture inversion enabling higher inversion rates and a stable inversion performance. The developed approach was applied on the multi-angular L-band data set acquired by German Aerospace Center's ESAR sensor as part of the OPAQUE campaign in 2008. The obtained results are compared against ground measurements collected by the OPAQUE team over a variety of vegetated agricultural fields. The validation of the estimated against ground measured soil moisture results in an root mean square error level of 6-8 vol.% including all test fields with a variety of crop types.

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.

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 ≤kz≤ 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.

One important secondary objective of the proposed Earth-Explorer Candidate Mission BIOMASS is the retrieval of a digital terrain model (DTM) using satellite-borne P-band SAR data. The interferometric phase acquired in repeat-pass mode may be affected by ionospheric effects leading to corrupted phase estimates and, consequently, to errors in the derived DTM. In contrast, line-of-sight orientation angles induced by azimuth slopes can be estimated using single-pass POLSAR measurements. The orientation angle estimates allow a necessary pre-processing of POLSAR observations and the retrieval of topographic information such as a DTM. In this study, the performance of the circular polarization method for orientation angle estimation is examined over forested areas. To this end, the orientation angles computed from P-band POLSAR data are compared with the results obtained from LIDAR DTMs. In particular, the estimation performance is investigated with respect to the impact of topography and vegetation. POLSAR data at P-band are used that have been acquired by the E-SAR system of DLR over three forested test sites: two boreal forests in Sweden (one over flat terrain located at Remningstorp, the other over terrain with topographic variations at Krycklan) and the tropical forest Mawas in Indonesia over flat terrain.

Polarimetric spectral analysis techniques have been recently introduced for processing multibaseline interferometric synthetic aperture radar data that are affected by the speckle phenomenon. In this paper, their phase estimation accuracy for retrieving the three-dimensional structure of scatterers from measurements corrupted by multiplicative noise is examined. The performance of the polarimetric beamforming, Capon, and MUSIC algorithms is investigated by Monte Carlo simulations and compared with the polarimetric Cramér-Rao bound. It is demonstrated by the CRLB that radar probing systems possessing polarization diversity offer the potential of considerably improving the information extracted from the observation space enlarged by scattering polarimetry. Moreover, it is shown that the polarimetric algorithms lead to noticeably enhanced estimation precision, in particular in terms of refined resolution, under the condition of polarization diversity.

In this work we propose a model for the polarimetric backscattering of shallow sub-arctic lakes, which are frozen usually up to two meters depth during winter. The model takes into account the inhomogeneities in the ice layer introduced mainly by CH4bubbles trapped in the lake ice. The model is validated against experimental data acquired by ALOS-PalSAR.

High spatial resolution X-band interferometric SAR data from the TanDEM-X, in the operational DEM generation mode, are sensitive to forest structure and can therefore be used for thematic boreal forest classification of forest environments. The interferometric coherence in absence of temporal decorrelation depends strongly on forest height and structure. Due to the rather homogenous structure of boreal forest, forest biomass can be derived from forest height, on the basis of allometric equations with sufficient accuracy to be used for thematic classification applications. Two test sites in mid- and southern Sweden are investigated. A maximum of 4 biomass classes, up to 250 Mg/ha, are achieved. Larger spatial baselines result in better classification performances.

Soil moisture retrieval under agricultural vegetation is assessed by a hybrid decomposition and inversion algorithm using fully polarimetric SAR data of DLR's E-SAR system at L-band. The results for the AgriSAR and SARTEO campaigns, conducted in 2006 and 2008 within the Peene and the Rur catchment, reveal a very high inversion rate leading to a spatially continuous inversion along the entire growth cycle in agricultural areas. The validation with in situ measurements for a variety of summer and winter crops states a root mean square error of 6.25vol.% and 5.77vol.% respectively, while a wide moisture range (~2-30vol.%) is covered by the soil moisture inversion under vegetation.

The extensive field data base of the TERENO project is utilized to validate inversion results for soil moisture under vegetation within two terrestrial observatories (Central German Lowland Observatory and Lower Rhine Valley Observatory). The recently developed hybrid decomposition and inversion approach is applied to L-band fully polarimetric SAR data acquired within the TERENO campaign of 2011 by DLR's novel high resolution F-SAR sensor in order to investigate its potential. The soil moisture results state a spatially continuous inversion under vegetation with a RMSE between 3.2vol.% and 8.2vol.% for both observatories. Therefore the results are particularly suited for local analyses on the field level in contrast to soil moisture products with low resolution from passive microwave sensors on the catchment level.

A correction method for distortions induced by ionospheric scintillation effects on P-band quad-pol synthetic aperture radar (SAR) data acquired in polar and high latitude regions is presented. For this the estimation of the Faraday rotation (FR) is converted to ionospheric phase and used for the correction of the scintillation. The correction is performed on partially focused SLC data in order to compensate the ionosphere-induced phase and the distortion of the time-Doppler history. The degree of defocusing depends on the altitude of the ionosphere. The performance of the new correction method is tested on P-band simulated data for various ionospheric scenarios.

A validation method for polarimetric SAR model-based decompositions is proposed based on correlation coefficients between polarizations. The correlation coefficient is examined if it ranges from 0 to 1 for covariance matrices after the subtraction of volumetric scattering components. The three combinations of the polarizations seen in covariance matrices are examined. It is confirmed that, in general, the condition above is not held, which clarifies the overestimate of volume scattering, even though conventional procedures take negative powers into account. Furthermore, the possible maximal power of volume scattering is estimated by employing the condition as a constraint. The constraint by correlation coefficients is a part of the one by nonnegative eigenvalues. In order to equalize them, the third-order principal minor, that is the determinant in the case of 3*3 matrices, must be considered. Finally, the possible maximal power, equal to the one derived from the constraint by nonnegative eigenvalues, can be derived analytically, while that is estimated numerically for the case of nonnegative eigenvalues.

Temporal decorrelation is a critical issue for a successful Pol-InSAR inversion in case of repeat-pass SAR data, as provided by conventional satellite or airborne SAR systems. This paper proposes estimation and compensation of temporal decorrelation effects by using multi-baseline Pol-InSAR data. A new approach to quantify different temporal decorrelation levels (one for volume and the other for the ground layer) is performed without resort to the special case of zero spatial baseline interferograms. Both temporal decorrelation coefficients were separately estimated at temporal baselines ranging from 1 to 15 days and compared to height inversion errors caused by them.

This paper provides an overview of the BIOMASS Mission End-to-End simulator (BEES) and of the mission performance analysis performed with it. The end-to-end performance, in terms of biomass estimates error, is close to the 20% error goal set for the mission. The main sources of errors are temporal decorrelation and the limited available bandwidth, while system induced errors have a negligible impact on the final performance.

The theoretical framework necessary to facilitate the mitigation of ionospheric physical effects on amplitude and phase of low-frequency space-based synthetic aperture radars (SAR) is presented. By way of a unique research collaboration the authors have developed mathematical and stochastic descriptors of the spatio-temporal structure and its impact on SAR signals passing through the ionosphere during different levels of scintillation. The authors have developed a prototype integrated ionospheric processor that combines multiple existing and newly developed correction methods with the goal to maximize correction robustness and accuracy. For the first time, realistic stochastic models describing the amplitude and spatial structure the ionosphere were developed and validated; thereby, allowing the study and discovery of the origin of SAR image artifacts that are caused by ionosphere scintillation; i.e., a noise-like high frequency phase distortion.

Forest characterization and biomass estimation by means of remote sensing systems are nowadays “hot topics” within the remote sensing community, given their importance in the terrestrial carbon budget. In fact, forest vertical structure is a key variable for assessing biodiversity and structural degradation and/or regeneration. Moreover, the (vertical) structure information is important as it can allow the development of accurate and robust (alometric) estimators of the forest biomass. In this paper, potentials and challenges of forest vertical structure estimation with low frequency multibaseline polarimetric synthetic aperture radar are reviewed and discussed.

Synthetic aperture radar (SAR) systems in L-band and P-band are characterized by deep penetration capabilities into volumes, enabling new opportunities for the radar remote sensing of forests. In the last years, the interest has been continuously growing in the estimation of the sub-canopy topography, especially by exploiting multibaseline (possibly polarimetric) SAR data. This work intends to contribute on this topic by presenting further experiments with real L-band data about ground topography estimation and by quantifying the obtained performance. Different forest scenarios are considered. Potentials and limitations are analyzed with particular reference to a multibaseline relaxation-based algorithm.

Prior to any processing of multibaseline (MB) synthetic aperture radar (SAR) data stacks, a MB phase calibration is necessary to compensate for phase contributions due to platform motions and/or atmospheric propagation delays. Classical calibration methods rely on the detection of point-like scatterers. However, especially in natural scenarios, their final calibration performance could be impaired by the nature of the scattering and by the typical low number of baselines. In this paper, we propose a calibration method based on the minimization of the entropy of the vertical profile of the backscattered power. This allows to potentially exploit the MB SAR signal independently of the nature of the scattering. The proposed method has been tested by processing simulated and real airborne datasets of a forest stand.

In recent years an increased interest arose in using synthetic aperture radar (SAR) to study and monitor land ice for glaciological applications and climate change research. At long wavelengths, SAR systems can penetrate into glacier ice for several tens to hundreds of meters. This makes them sensitive to near-surface as well as deeper ice volume features. This paper investigates the performance of a volume scattering component, in the course of an electromagnetic (e.m.) model development, to relate Polarimetric SAR (PolSAR) signatures to glacier facie. Indeed, PolSAR ice signatures are still poorly understood, including the importance of scattering from the glacier ice volume and its dependency on frequency and incidence angle. A comparison is performed with airborne Pol-SAR data at L- and P-band collected by DLR's E-SAR system over the Austfonna ice cap in Svalbard, Norway, within the ICESAR campaign.

The BIOMASS mission is designed to provide unique information on the biomass in the world's forests at spatial and temporal resolutions suitable for characterizing their dynamics and their contribution to carbon cycle estimates. To achieve this it combines biomass estimates from direct inversion of polarimetric backscattering coefficients with Pol-InSAR forest height estimates. The mission will also support important secondary objectives, including sub-surface imaging in arid zones, production of a bare-earth DTM and ice applications, and is optimized to be robust against environmental and ionospheric disturbances.

The identification of scatterers having a point-like behavior in SAR images has become an important topic with a wide range of applications, from calibration to information extraction. So far, three different approaches are available for the Coherent Scatterer (CS) detection, based on spectral correlation techniques using only a single SAR image. In this paper, a new approach based on the generalized likelihood ratio test (GLRT) is introduced. An extensive performance analysis using the different detection methods is presented, comparing the new proposed method with the previous ones. Lastly, the new approach is tested using real data.

The BIOMASS mission is designed to map the full range of the world's above-ground forest biomass, for the needs of national scale inventory and global carbon flux calculations. This objective is achieved with advanced P-band SAR techniques. The P-band biomass measurement concept was based on previous work over the past two decades. During the preparatory phase, new campaigns have been conducted to address critical issues on the biomass retrieval algorithms, over tropical and boreal forests. The collected datasets comprise accurate and complete sets of in situ data and advanced P-band SAR data. This paper presents the retrieval algorithms developed using the collected datasets.

In this paper we propose some ionospheric correction schemes for space-borne synthetic aperture radar (SAR) and polarimetric interferometric SAR (PolInSAR). The spatial and temporal variation of the free electron density in the uppermost atmosphere affects the propagation of the radar pulse resulting in image distortions. We estimate the total electron content (TEC) by applying the Appleton-Hartree equation to the distortions in the focusing, polarimetry, and interferometry. Then we propose a combined estimator that yields comprehensive differential TEC estimations. The effect of vertical structures of the ionosphere on interferometric phase is further discussed.

This paper discusses the implementation of an end- to-end simulator for the BIOMASS mission. An overview of the system architecture is provided along with a functional description of the modules that comprise the simulator.

Polarimetric SAR Interferometry makes possible a detailed analysis of the volumetric scattering processes present in microwave scattering in case of forest areas. In previous contributions, the authors, under the hypothesis of the RVoG coherent scattering model, developed a process for the direct extraction of the ground topography. In this paper, the authors present a generalization of this technique allowing to determine a set of scattering mechanisms making possible an optimization process for the estimation of the ground topography. The applicability of this technique, in case of X-band polarimetric SAR interferometric data, is explored considering data obtained in the frame of the TanDEM-X mission.

Tandem-L is a mission proposal for an innovative interferometric L-band radar instrument that enables the systematic monitoring of dynamic Earth processes using advanced techniques and technologies. The mission is science driven aiming to provide a unique data set for climate and environmental research, geodynamics, hydrology and oceanography. Important application examples are global forest height and biomass inventories, measurements of Earth deformation due to tectonic processes and/or anthropogenic factors, observations of ice/glacier velocity field and 3-D structure changes, and the monitoring of soil moisture and ocean surface currents. The Tandem-L mission concept consists of two cooperating satellites flying in close formation. The Pol-InSAR and repeat-pass acquisition modes provide a unique data source to observe, analyse and quantify a wide range of mutually interacting processes in the bio-, litho-, hydroand cryosphere. The systematic observation of these processes benefits from the high data acquisition capacity and the novel high-resolution wide-swath SAR imaging modes that combine digital beamforming with a large reflector antenna. This paper provides an overview of the Tandem-L mission concept and its main application areas. It is planned to realise the Tandem-L mission in cooperation with NASA/JPL. The mission concept was developed in detail in a joint two-year pre-phase A study and it will be further studied in the next 18 months. This will allow a cost-effective implementation, whereby each partner contributes its predevelopments and experience. According to current planning, the Tandem-L satellites could be launched in 2019.

This paper investigates the detection of Coherent Scatterers (CSs) in ice and glacier terrain by means of TerraSAR-X time series data in the test site of the Helheim Glacier in Greenland. CSs are evaluated with respect to detection and potential applications. Applying optimized detection scheme can be useful for retrieving information about the glacier movement using time series data. Finally, some conclusions about the temporal stability of natural CSs are obtained by analyzing the rocky area around the glacier.

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.

SIGNAL is an innovative earth exploration mission proposal with the main objective to estimate accurately and repeatedly topography and topographic changes associated with mass change or other dynamic effects on glaciers, ice caps and polar ice sheets. Elevation measurements are complemented with glacier velocity measurements, providing valuable additional information for a better understanding of the hydrology of glacierized basins and of the Arctic and Antarctic water cycle. SIGNAL is capable of monitoring all critical regions with a high spatial resolution and an adequate revisit time. This paper gives an overview about the actual mission design status and provides a brief description of the topography (DEM - digital elevation map) self-calibration strategy and the estimated global interferometric performance.

In this paper, the first detection result of coherent scatterers (CSs) in forest environment is addressed. As a scatterer associated with CS, the dihedral structure consists of the tree-trunk like a vertical cylinder and the ground surface is assumed. The potential of CSs as being the phase stable scatterers as permanent scatterers will be also demonstrated with P-&L-band Pol-InSAR datasets acquired in repeat-pass InSAR mode over boreal forest test site by German Aerospace Center's E-SAR airborne system.

Tandem-L is a proposal for an innovative interferometric and polarimetric radar mission that enables the systematic monitoring of dynamic processes on the Earth surface. Important mission objectives are global forest height and biomass inventories, large scale measurements of millimetric displacements due to tectonic shifts, and systematic observations of glacier movements. The innovative mission concept and the high data acquisition capacity of Tandem-L provide a unique data source to observe, analyze and quantify the dynamics of a wide range of mutually interacting processes in the bio-, litho-, hydro- and cryosphere. By this, Tandem-L will be an essential step to advance our understanding of the Earth system and its intricate dynamics.

The work detailed in this paper analyzes the topographic phase retrieval process on forested areas by means of Polarimetric Interferometric SAR data. On the basis of the Random Volume over Ground scattering model, an alternative implementation for the retrieval of the topographic phase, avoiding the bias introduced by the volumetric scattering components is presented.

In this paper, the decomposition of fully polarimetric SAR data into three canonical scattering mechanisms is investigated with respect to forest biomass retrieval. It is demonstrated that the dominant backscattering contribution depends strongly on the frequency, incidence angle, and stand condition. The relation between in-situ biomass measurements and the individual decomposition components is examined.

The European Space Agency (ESA) released a Call for Proposals for the next Earth Explorer Core Mission in March 2005, with the aim to select the 7thEarth Explorer (EE-7) mission for launch in the next decade. Twenty-four proposals were received and subject to scientific and technical assessment. Six candidate missions were selected and further investigated in the preliminary feasibility studies (Phase 0). One of these missions is BIOMASS, which has recently been selected to proceed to Phase-A. BIOMASS is a response to the urgent need for greatly improved mapping of global biomass and the lack of any current space systems capable of addressing this need.

This paper presents an overview of single-pass interferometric Synthetic Aperture Radar (SAR) missions employing two or more satellites flying in a close formation. The simultaneous reception of the scattered radar echoes from different viewing directions by multiple spatially distributed antennas enables the acquisition of unique Earth observation products for environmental and climate monitoring. After a short introduction to the basic principles and applications of SAR interferometry, designs for the twin satellite missions TanDEM-X and Tandem-L are presented. The primary objective of TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) is the generation of a global Digital Elevation Model (DEM) with unprecedented accuracy as the basis for a wide range of scientific research as well as for commercial DEM production. This goal is achieved by enhancing the TerraSAR-X mission with a second TerraSAR-X like satellite that will be launched in spring 2010. Both satellites act then as a large single-pass SAR interferometer with the opportunity for flexible baseline selection. Building upon the experience gathered with the TanDEM-X mission design, the fully polarimetric L-band twin satellite formation Tandem-L is proposed. Important objectives of this highly capable interferometric SAR mission are the global acquisition of three-dimensional forest structure and biomass inventories, large-scale measurements of millimetric displacements due to tectonic shifts, and systematic observations of glacier movements. The sophisticated mission concept and the high data-acquisition capacity of Tandem-L will moreover provide a unique data source to systematically observe, analyze, and quantify the dynamics of a wide range of additional processes in the bio-, litho-, hydro-, and cryosphere. By this, Tandem-L will be an essential step to advance our understanding of the Earth system and its intricate dynamics. Enabling technologies and techniques are described in detail. An outlook on future interferometric and tomographic concepts and developments, including multistatic SAR systems with multiple receivers, is provided.

In this paper first results of a sensitivity study using dual polarimetric TerraSAR-X data for ice thickness estimation are presented. The sea ice thickness reference data set was measured, coincident to the SAR data take, by means of a helicopter-borne EM sounding device on April 28, 2008 in the Russian Arctic. For some of the signatures, namely the complex correlation coefficient, a relation to ice thickness could be found that is theoretically predicted for L-band SAR. The first results show, that the new generation of polarimetric space borne SAR sensors like TerraSAR-X may open a new opportunity for thin sea ice thickness monitoring from space.

In this paper a modified three component polarimetric decomposition incorporating multi-angular acquisitions is developed to estimate soil moisture under vegetation cover over agricultural areas. The approach is applied on fully-polarimetric L-band data acquired by DLR's airborne E-SAR sensor in the frame of the OPAQUE campaign conducted in May 2008 in the Weißeritz catchment area, near Dresden, Germany. The results for the estimated soil moisture from the overlapping area of the flight strips demonstrate a significant increase of the inversion rate, if more than one acquisition is used. The inverted soil moisture values are validated against in situ measurements for five test fields with different crop types resulting in an RMSE of approximately 7vol.% for different incidence angle constellations. Finally the results show how topographic effects in the soil moisture retrieval can be compensated by multi-angular constellations.

This paper presents the impact of simulation parameters according to the potential future space-borne mission BIOMASS (P-band) in polarimetric and interferometric SAR (Pol-InSAR) inverison performance. Forest height inversion is obtained from the simulated data sets (bandwidth, NESZ and ambiguities) generated from DLR E-SAR (Experimental Synthetic Aperture Radar) airborne SAR data. For this study two campaign data sets (BioSAR 2007 / INDREX-II) have been selected and investigated. The several comparative results of Pol-InSAR between airborne data and the simulated data (incl. bandwidth, NESZ and range/azimuth ambiguities) will be shown and discussed.

In this paper the impact of vertical forest structure on model based Pol-InSAR forest height inversion is discussed. For different scenarios appropriate extensions of the RVoG model are proposed and possible inversion schemata are suggested and validated against experimental data and ground measurements.

The objective of this paper is to make a review of the current status of the PolSARpro v4.0 Software (Polarimetric SAR Data Processing and Educational Toolbox), developed under contract to ESA by a consortium comprising I.E.T.R at the University of Rennes 1, AELc, DLR-HR and Dr mark Williams from Adelaide. The objective of this current project is to provide Educational Software that offers a tool for self-education in the field of Polarimetric SAR data analysis at University level and a comprehensive suite of functions for the scientific exploitation of fully and partially polarimetric multi-data sets and the development of applications for such data. The PolSARpro v4.0 Software establishes a foundation for the exploitation of Polarimetric techniques for scientific developments and stimulates research and applications developments using PolSAR and PolInSAR data.

This paper describes a methodology to extrapolate spaceborne quality SAR image products from long wavelength airborne polarimetric and interferometric SAR data. The methodology is applied to E-SAR data of DLR, partially acquired under ESA contract especially for the development and validation of bio/geo-retrieval algorithms in forested regions. For this purpose not only system (sensor) related parameters are altered, but also those relating to the propagation path (ionosphere) and to temporal decorrelation. Examples for future spaceborne products are presented and the potential of Pol-InSAR methods for the retrieval of forest heights from these data is discussed.

Coherent Scatterers (CSs) are usually detected in SAR data using spectral correlation techniques, by evaluating multilook images in the range direction. The first part of the paper demonstrates an alternative way to detect CSs by exploiting their inherent strong phase stability along frequency. The main advantage of the technique is the absence of a spatial average (necessary in the original procedure), which avoids loss of resolution. The second part of this work illustrates the use of CSs for the estimation and correction of phase errors along the synthetic aperture. Such source of errors may be originated by different effects as platform motion and atmospheric or ionospheric disturbances. For the correction of one and two-dimensional phase errors addressed here, a CSs based autofocus procedure was implemented and applied to simulated and real data.

In this paper, the potential of using polarimetric SAR (PolSAR) acquisitions for the estimation of volumetric soil moisture under agricultural vegetation is investigated. Soil-moisture estimation by means of SAR is a topic that is intensively investigated but yet not solved satisfactorily. The key problem is the presence of vegetation cover which biases soil-moisture estimates. In this paper, we discuss the problem of soil-moisture estimation in the presence of agricultural vegetation by means of L-band PolSAR images. SAR polarimetry allows the decomposition of the scattering signature into canonical scattering components and their quantification. We discuss simple canonical models for surface, dihedral, and vegetation scattering and use them to model and interpret scattering processes. The performance and modifications of the individual scattering components are discussed. The obtained surface and dihedral components are then used to retrieve surface soil moisture. The investigations cover, for the first time, the whole vegetation-growing period for three crop types using SAR data and ground measurements acquired in the frame of the AgriSAR campaign.

This paper addresses the potential and limitations of polarimetric synthetic aperture radar (SAR) interferometry (Pol-InSAR) inversion techniques for quantitative forest-parameter estimation in tropical forests by making use of the unique data set acquired in the frame of the second Indonesian Airborne Radar Experiment (INDREX-II) campaign - including Pol-InSAR, light detection and ranging (LIDAR), and ground measurements - over typical Southeast Asia forest formations. The performance of Pol-InSAR inversion is not only assessed primarily at L- and P-band but also at higher frequencies, namely, X-band. critical performance parameters such as the ldquovisibility of the groundrdquo at L- and P-band as well as temporal decorrelation in short-time repeat-pass interferometry are discussed and quantitatively assessed. Inversion performance is validated against LIDAR and ground measurements over different test sites.

In this paper we introduce a new algorithm for radar estimation of the vertical structure of vegetated land surfaces. The algorithm is based on a low frequency 3-D image reconstruction using polarization coherence tomography or PCT. We first summarize the technique, present a new method for selecting the optimum interferometric baseline and then apply it to airborne P and X-Band data from the DLR E-SAR system. We conclude by assessing the potential of the technique for providing improved global and regional forestry products using space-borne radar remote sensing.

In this paper the focus is given to the soil moisture retrieval under a vegetation cover, exemplarily for two crop types winter wheat and rape. For this Pol-SAR data over a whole vegetation period were used acquired in the frame of the AGRISAR campaign in 2006 at L-band. The potentials and limitations over time are investigated by modifications of the model based Freeman decomposition in order to decompose the scattering contributions and to invert the surface and dihedral scattering component for soil moisture estimation. The applied decomposition approaches for agricultural land surfaces are suitable, but exhibit deficiencies in modeling the volume component, even though some improvements due to the modifications could be presented. In the end the soil moisture estimation does not perform constantly well over the whole acquisition period due to the complexity of the crop vegetation.

PolInSAR data is a good example of a high dimensional SAR data. A blind filtering of these data does not make use of possible constraints imposed by the scattering process. In this paper it is shown that the scattering over forested areas induces some constrains on the data that can be fruitfully exploited to improve the final filtering, with que consequent improved of the quantitative estimation process.

The objective of this paper is to make a review of the current status of the PolSARpro v3.3 Software (Polarimetric SAR Data Processing and Educational Toolbox), developed under contract to ESA by a consortium comprising I.E.T.R at the University of Rennes 1, AELc, DLR-HR and Dr mark Williams from Adelaide. The objective of this current project is to provide Educational Software that offers a tool for selfeducation in the field of Polarimetric SAR data analysis at University level and a comprehensive suite of functions for the scientific exploitation of fully and partially polarimetric multi-data sets and the development of applications for such data. The PolSARpro v3.3 Software establishes a foundation for the exploitation of Polarimetric techniques for scientific developments and stimulates research and applications developments using PolSAR and PolInSAR data.

In this paper we evaluate X- and L-band SAR coherence tomography in boreal forest with the help of detailed digital terrain and canopy height models, produced by laser scanning. Polarimetric coherence tomography (PCT) needs accurate estimates of ground phase and tree height. Supplemental accurate elevation models allow us to evaluate the performance of PCT in normal case when initial values are derived from RVoG model inversion and provides opportunity to use PCT for nonpolarimetric data. The work is based on E-SAR L-band and X-band measurements in Finland. Our results show that with accurate elevation and tree height information single polarization X-band coherence tomography is feasible and works well. Accurate ground elevation information improves also the performance of fully polarimetric repeat pass L-band PCT. The laser DEM provides better ground phase estimate than RVoG model inversion in the presence of temporal decorrelation. Our results show that accurate ground phase estimation is more critical for successful coherence tomography than other parameters.

Faraday rotation and scintillation will seriously affect P-band SAR images if methods are not used to deal with them. There are published methods for correcting Faraday rotation when polarimetric data are available, but less is known about scintillation. Scintillation is unlikely to present a problem if data acquisitions at low and mid latitudes avoid the post-sunset equatorial region, but correction procedures are likely to be needed in the auroral zones. Such correction is possible using autofocus methods; this is demonstrated using the Phase Gradient Algorithm applied to SAR imagery seriously affected by simulated scintillation.

A sparse pine forest is investigated at X-band on a single-pass polarimetric synthetic aperture radar interferometry (PolInSAR) data set using HH and HV channels. These first preliminary results show that the associated phase centers present a significant vertical separation (about 6 m) allowed by penetration through gaps in the canopy. Forest parameter inversion using the random volume over ground (RVoG) model is evaluated and adapted at this frequency. The forest height can be retrieved accurately by supposing a high mean extinction coefficient (around 1.6 (dB/m). The penetration depth is estimated to be around 4 m, based on the forest height ground measurements. Finally, a time-frequency analysis using a sublook decomposition is performed to increase the vertical separation of the polarimetric phase centers. As a consequence, RVoG-inversion performance is improved, and a penetration depth that is in better accordance with a previous work (of the order of 2 m) is found. This paper has shown that the height inversion of a pine forest was possible using PolInSAR X-band data and that the performance was more dependent on the forest density than at lower frequencies.

ALOS, an enhanced successor of the Japanese Earth Resources Satellite 1 (JERS-1), was launched from JAXA's Tanegashima Space Center in January 2006. An important contribution to the ALOS mission is the verification of PALSAR products to be distributed by the European ADEN node using the PALSAR processor developed by JAXA. A total of 28 ALOS PALSAR products have been analysed with respect to radiometric, geometric and polarimetric quality (including effects of Faraday rotation caused by the ionosphere) and a summary of the results is shown in this paper.

The paper deals with the problem of reconstructing the height of forests from polarimetric/multi-baseline SAR data. The approach consists of optimizing an objective functional defined as the distance between the measured data and the data predicted by the model at the actual estimate of the unknowns. We indicate the role of global optimization on the performance of the forest height reconstruction algorithm. As global optimizer, a multilevel single-linkage method, which incorporates a local optimization into the global search, is exploited, thus offering computational efficiency and reliability. The performance of the method are illustrated against numerically simulated data.

Polarimetric SAR interferometry (Pol-InSAR) is a powerful remote sensing method for forest height estimation by using the random volume over ground model (RVoG). At higher frequencies implementation of forest height estimation in X band is limited to less dense and low forest types where X band is able to penetrate through the volume to the ground. However, the penetration depth at X band is insufficient to cover all forest types. In the paper, forest height inversion at X band using two different approaches is demonstrated with focus on the impact of extinction on forest height estimation.

Coherent Scatterers (CSs) are scatterers detected by using spectral correlation properties and characterized by a deterministic scattering behavior. In this paper we investigate, for the first time, the temporal behavior of CSs using quad-pol data acquired by ALOS/PalSAR. In this sense, we can evaluate the stability of the deterministic scattering nature of individual scatterers.

The launch of JAXA's ALOS in January 2006 provides - for the fist time since the SIR-C/X-SAR mission's in the 80's - the opportunity to acquire Pol-InSAR data from space. Indeed, PalSAR (i.e. the SAR instrument onboard of ALOS) is able to operate in a quad-pol mode - declared by JAXA as an "experimental mode" - that allows the acquisition of Pol-InSAR data in a repeat- pass mode. In this sense, ALOS-PalSAR allows the application, validation and development of Pol-InSAR inversion techniques on a much wider range of sites distributed world-wide and accessible to a much wider scientific user community than possible with airborne sensors. In this paper we present the analysis of fully- and/or dual-polarimetric and interferometric data sets acquired by ALOS/PalSAR during its CAL-VAL and operational data acquisition phase and discuss the potential and the limitations for different polarimetric interferometric applications. More developed applications as forest height estimation from single- and multi-baseline Pol-InSAR ALOS-PalSAR data inversion - addressed in the frame of JAXA's Karbon & Kyoto initiative - as well as novel applications regarding soherent scatterer's detection and interpretation in urban environments are discussed. The impact of critical mission and operation design parameters as spatial coverage, repeat-pass time, observation scenario, and orbit control are evaluated and discussed.

In this paper we study the extinction coefficient of boreal forest by utilizing airborne E-SAR X-band POLInSAR and HUTSCAT X-band profiling scatterometer measurements. By combining E-SAR VV-pol coherency with HUTSCAT tree height measurements we calculate forest extinction coefficients by RVoG model inversion and compare the results with extinction values obtained from HUTSCAT measurements. For retrieval of the extinction coefficient we propose robust RVoG model inversion procedure and discuss the model inversion conditions. Our results show, that extinction coefficient for boreal forest is quite low even for X-band, especially from nadir looking instruments. The extinction coefficient of forest canopy retrieved from HUTSCAT measurements is 0.15 dB/m and retrieved from E-SAR and HUTSCAT measurements is 0.9 dB/m.

The last decade has seen an increasing demand for accurate mapping and wide-coverage monitoring of glaciers and ice sheets in order to measure and predict their response to global climate change and their contribution to sea level rise. This in turn requires a more complete understanding of their properties including topography, accumulation rates and vertical profiles. One promising new technique for vertical profile reconstruction using polarimetric interferometric SAR (Pol-InSAR) data is polarization coherence tomography (PCT) and for the first time, PCT is adapted here to a glacier scenario. The inversion algorithm to reconstruct vertical ice profiles is applied to both simulated data to assess its accuracy and sensitivity to input parameters, and to airborne Pol-InSAR data at L- and P-band and InSAR data at X-band collected using DLR's E-SAR system over the Austfonna ice cap in Svalbard, Norway.

We investigate the impact of polarimetry and polarimetric effects on the Differential Interferometry (DinSAR) technique for the coherent backscattering reciprocal case, with the aim to obtain better accuracy and to extract additional information about the scatterer. Emphasis is given to the effects of Faraday and scatterer line-of-sight (LOS) rotations, and to the determination of the intrinsic scatterer scattering mechanism.

In this letter, we present results from the FinSAR project, where the E-SAR and Helsinki University of Technology Scatterometer (HUTSCAT) instruments were operated together in order to validate tree-height retrieval algorithms for boreal forest. The campaign was carried out in Finland in fall 2003. The main instruments of the campaign were the E-SAR airborne radar (operating at L- and X-band) and the HUTSCAT helicopter-borne profiling scatterometer (operating at X- and C-band). We compare and discuss forest height obtained from the inversion quad-pol polarimetric interferometric synthetic aperture radar (SAR) data sets at L-band and forest height obtained from the inversion of single-pol X-band in SAR data with forest height estimates from HUTSCAT scatterometer data. Our results show that the forest height values, which are estimated by means of two different radar instruments, are in good agreement. The correlation between HUTSCAT and E-SAR height estimates ( at L-band and at X-band) underlines the good agreement between the results obtained by the two approaches.

Tropical rain forest environments are highly complex and heterogeneous in terms of species composition and structure and is often difficult to access. Radar remote sensing is for large tropical regions the only available information source for monitoring. Pol-InSAR is a novel developed radar remote sensing technique sensible to the vertical structure of forest that allows the estimation and mapping of forest height. In this paper we demonstrate forest height inversion at two frequencies - L band and P band - by means of Pol-InSAR using INDREX-II data and addresses the problem of temporal decorrelation.

In this study we concentrate on the application and validation of forest height estimation by polarimetric SAR interferometry for boreal forest. The study material was collected during the FinnSAR campaign, carried out in Finland in fall 2003. The main instruments of the campaign were E-SAR airborne radar (L- and X-band) and HUTSCAT helicopter-borne profiling scatterometer (X- and C-band). The validated forest height estimation algorithm is based on random volume over ground (RVoG) model inversion by using POLinSAR data. We compare POLinSAR-derived forest height with results from profiling HUTSCAT scatterometer measurements and with ground measurements and discuss the results. Our results show that the forest height values, estimated by means of two different instruments, are in good agreement.

PALSAR L-band SAR will be affected by Faraday rotation. In this study, PALSAR system is briefly described, and the Freeman calibration method is considered for PALSAR calibration. However, this method requires the deployment of a minimum of one corner reflector (CR) for the calibration of each scene, and this is not convenient in practice. In this paper, the use of human-made and natural symmetric targets is investigated for the calibration of SAR subject to Faraday rotation. The target scattering vector model (TSVM), which permits a unified decomposition of point and distributed target scattering, is used to derive a new calibration method that does not require the deployment of CRs. It is shown that the orientation (i.e. target tilt angle) and roll invariant maximum polarization parameters of symmetric target scattering can be used to measure and remove Faraday rotation and channel imbalance errors from PALSAR data. Antenna gain and cross-talk incidence angle variations are measured using data acquisitions over the Amazonian forests, under low Faraday rotation conditions.

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.

In this paper we present an analysis of the potential for \nimplementing polarimetric SAR Interferometry (POLInSAR) \nwith the new L band phased array SAR sensor (PALSAR) to be \nlaunched on board the JAXA-ALOS satellite. We first summarise \na new system design concept, the phase tube, we have developed \nfor general POLInSAR assessment and then present a detailed \nanalysis of the dual and quadpol modes of ALOS-PALSAR.

We address the problem of reconstructing parameters \nregarding the vertical structure of forests from multibaseline \nSAR data. The attention is focused on the retrieval of the \nforest height so that the case of vanishing ground scattering is \nconsidered. \nThe cross-spectral density of the scattered field is taken as datum \nof the problem and the forest height is searched for by tackling \nan optimization problem. An analytical and numerical analysis \nof the involved functional is performed by taking due care to the \ndiscrete nature of the scatterers.

In this paper the detection of point-like coherent scatterers (CSs) in single and quad-pol images is addressed and applied on polarimetric and interferometric high-resolution SAR data. For the detection of CSs two different approaches are described, both based on spectral correlation. The effect of multi acquisitions on the number and quality of CSs is verified and the results are discussed. The role of polarimetry on the detection is evaluated and the potential of polarimetric based information extraction as the estimation of the orientation angle – is addressed.

The polarimetric cross-talk calibration algorithm proposed by Quegan, which is more general than the one proposed by van Zyl, is modified to improve polarimetric SAR calibration. L-band polarimetric SAR data acquired by the JAXA/NICT airborne Pi-SAR, including a variety of natural and artificial targets, are calibrated introducing noise imbalance of cross-polarized channels into the Quegan algorithm and deriving the cross-talk parameters from areas with low correlation between like and cross-polarized observed echoes. The achieved enhancement in stability of cross-talk parameter estimation and removal over is demonstrated in terms of CR response analysis and polarimetric classification result

In this paper, inversion of synthetic aperture radar data is dealt with and, in particular, the problem of reconstructing forest height is addressed. The forest is modelled as a random volume of particles over a rough ground. Under this model, the forest height turns out to be related to the bandwidth of the scattered field. The inversion is cast as an optimization one. Preliminary results using DLR-ESAR experimental SAR data are shown

Polarimetric SAR interferometry (Pol-InSAR) permits an accurate forest height extraction by inverting the SAR data with the Random Volume over Ground-model (RVoG). These forest heights were subsequently converted to forest biomass through forest height-biomass relation (allometry). Both the height extraction (L-band) and the allometric biomass conversion proved a good performance over dense forest stands. In open forests and stands of variable canopy height (here referred to as heterogeneous stands), the behaviour of the height extracting algorithm is unknown, and height-biomass allometry cannot easily be applied. To facilitate a direct biomass comparison of the Pol-InSAR-height extraction with ground measurements, the effective height heffwas introduced as a direct biomass equivalent. Examples from spruce dominated sites of variable stand densities showed a sensitivity of the height extraction to the stand density, though not in correlation with the heff. It might be promising to exploit additional information from the shape of the extracted heights-histogram for an accurate biomass estimation even over dense and heterogeneous forests

Forest biomass (wood volume) is the most integrative forest structural parameter. Since no remote sensing technique can measure wood volume or biomass directly, a direct biomass determination from air- or spaceborne images always has a regression character. A different approach is to estimate forest biomass indirectly from a forest parameter that can be extracted more accurately than biomass, of which forest height is the closest related one. This makes it possible to utilize remote sensing methods that extract forest heights for biomass assessments: stereoscopic aerial photography, Lidar and Pol-InSAR. In this paper, forest heights were extracted from polarimetric interferometric SAR data (Pol-InSAR) over the spruce dominated test site `Fichtelgebirge'. The extracted heights proved a good correlation with the upper canopy height (h100, top height), and could be converted into forest biomass by means of height-biomass allometry. On this basis, the potential of Pol-InSAR systems for forest biomass estimation is critically discussed, and directions towards a performance optimisation are pointed out

In this overview, reasons are provided on why we do need to place multi-modal, multi-band single and multiple pass POLinSAR monitoring platforms into air and space. The questions "on what POLinSAR monitoring can provide that POL-SAR and IN-SAR by themselves cannot accomplish" is assessed; whereupon facts and justifications on placing POL-IN-BISAR satellite clusters into space are presented. Reasons for this technology becoming a basic requirement for current, near-future and much more so for future all day & night year-round monitoring of the terrestrial covers are analyzed in view of the un-abating and uncontrollable terrestrial population explosion, which has, does and for ever will result in unavoidable conflicts deteriorating unfortunately at times into terrorism. The pertinent questions on how to reduce the exorbitant cost for initiating this "home-globe security protection" technology are therefore also broached, and the expected benefits are laid out. The pertinent National and International airborne and space borne multi-modal, multi-band SAR remote sensing and security conflict surveillance support agencies are herewith invited for co-sponsoring our proposal, which is timely and fleets of orbiting multi-band POLinSAR platforms are urgently required to be placed into space.

This paper presents first results obtained from the analysis of fully polarimetric / interferometric land ice data. It is demonstrated that L-band data from an ice cap located in the percolation zone of Greenland show a strong polarization de- pendent interferometric behavior. No model-based inversion has yet been attempted, but a radar reflector deployed on the ice surface suggests an effective penetration depth of about 15 m.

In this work the potential of using the interferometric coherence at different polarization over surface scatterers to extract information about surface parameters is investigated. The sensitivity of the individual coherence contributions to surface roughness and moisture conditions is discussed and simulated using a novel hybrid polarimetric surface scattering model. The model itself consists of a coherent part obtained from the extended Bragg model and incoherent part obtained from the integral equation model. Finally, the experimental airborne SAR data are used to validate the proposed model at different polarizations.

Various remote sensing techniques do not derive forest biomass directly but forest parameters that are related to biomass such as forest height or LAI (leaf area index). This article focuses on the accuracy of the allometric relation relating forest biomass to forest height. The main error of a height-to-biomass allometry is the missing information on stand density (basal area). Yet, the relation derived from standard forestry tables (1) showed less than 15 % variance for a large range of temperate forest types. Comparing the table-derived height-biomass relation to data from standard field inventory, it was found that the table-based rela- tion overestimates biomass. A modified allometric relation is proposed that compensates the systematic overestimation.

This paper addresses the effect of temporal decorrelation on the inversion of forest parameters using Pol- InSAR techniques. The modeling of temporal decorrelation and the inversion of single-baseline Pol-InSAR data in the presence of temporal decorrelation is discussed. Model based simulations and experimental multi-temporal fully polarimetric and repeat pass interferometric data from the SIR-C Space shuttle mission are used for the performance analysis of the proposed approach. Keywords-component: Polarimetric SAR interferometry (Pol- InSAR), Forest Parameter Estimation.

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/spl times/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.

Radar Polarimetry, Radar Interferometry and Polarimetric SAR Interferometry represent the current culmination in 'Microwave Remote Sensing' technology, but we still need to progress very considerably in order to reach the limits of physical realizability. Whereas with radar polarimetry the textural fine-structure, target orientation, symmetries and material constituents can be recovered with considerable improvement above that of standard 'amplitude-only' radar; by implementing 'radar interferometry' the spatial (in depth) structure can be explored. With Polarimetric Interferometric Synthetic Aperture Radar (POL-IN-SAR) imaging, it is possible to recover such co-registered textural and spatial information from POL-IN-SAR digital image data sets simultaneously, including the extraction of Digital Elevation Maps (DEM) from either Polarimetric (scattering matrix) or Interferometric (dual antenna) SAR systems. Simultaneous Polarimetric-plus-Interferometric SAR Imaging offers the additional benefit of obtaining co-registered textural-plus-spatial three-dimensional POL-IN-DEM information, which when applied to Repeat-Pass Image-Overlay Interferometry provides differential background validation and environmental stress-change information with highly improved accuracy. Then, by either designing multiple dual polarization antenna POL-IN-SAR systems or by applying advanced POL-IN-SAR image compression techniques, will result in 'POL-arimetric TOMO-graphic' (Multi-Interferometric) SAR or POL-TOMO-SAR imaging.

In this work the potential of using the interferometric coherence at different polarisations over surface scatterers in order to extract information about surface parameters is investigated. The sensitivity of the individual coherence contributions to surface roughness and moisture conditions is discussed and simulated using a polarimetric surface scattering model. Finally, experimental airborne SAR data are used to demonstrate the discussed effects.

Polarimetric SAR interferometry has generated much interest for forest applications. In this paper, we study problems associated with interferometric coherence estimation and propose two algorithms to improve the accuracy in the coherence estimation based on speckle filtering of the 6 /spl times/ 6 polarimetric interferometry matrix.

In this paper, a noise model for the extended six dimensions covariance matrix used in polarimetric synthetic aperture radar (SAR) interferometry is proposed. This noise model is able to interpret interferometric, as well as polarimetric noise characteristics for the diagonal and non-diagonal elements of the covariance matrix.

Forest biomass is one of the most important and most unknown parameters for accurate global carbon stock modelling. In this paper we address an alternative methodology for estimating above ground forest biomass from radar remote sensing data, based on forest height estimates from single frequency polarimetric-interferometric SAR data.

Recently, several passive interferometric configurations consisting of two or more receiving only micro-satellites operating in a fully polarimetric mode positioned ahead or behind a master satellite have been proposed as a cost efficient option for future single-pass interferometric spaceborne SAR systems. In this paper the potential performance of such a passive polarimetric and interferometric micro-satellite concept for the estimation of forest structure parameters in terms of polarimetric interferometry is investigated.

In this paper we summarise the recent results from the Glen Affric radar project, a multi-disciplinary program addressing the potential of polarimetric radar interferometry to provide vegetation structural information of importance in forest mapping and ecology studies. We present a comparison of results from L-band repeat pass SAR imagery with detailed in-situ measurements of forest height and topography.

Examines 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.

The authors examine the role of polarimetry in synthetic aperture radar (SAR) interferometry. They first propose a general formulation for vector wave interferometry that includes conventional scalar interferometry as a special case. Then, they 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 them to reveal the strong polarization dependency of the interferometric coherence. They 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, they demonstrate the importance of wave polarization for the physical interpretation of SAR interferograms. They 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.

This paper addresses the noise filtering problem for synthetic aperture radar (SAR) interferometric phase images. The phase noise is characterized by an additive noise model. The model is verified with an L-band shuttle imaging radar (SIR)-C interferogram. An adaptive filtering algorithm based on this noise model is developed. It emphasizes filtering noise adaptively according to the local noise level and filtering along fringes using directionally dependent windows. This algorithm is effective, especially for the tightly packed fringes of X-band interferometry. Using simulated and SIR-C/X-SAR repeat-pass generated interferograms, the effectiveness of this filter is demonstrated by its capabilities in residue reduction, adaptive noise filtering, and its ability to filter areas with high fringe rates. In addition, a scheme of incorporating this filtering algorithm in iterative phase unwrapping using a least-squares method is proposed.

The authors exploit the interferometric multifrequency potentiality of the SIR-C/X-SAR system which is equipped with an L-, C-, and X-band sensor. They 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.