Bistatic Correlation Tomography is an innovative radar technique capable of retrieving the vertical structure of the target. By combining pairs of simultaneous SAR images collected in multiple bistatic passes, the distribution in elevation of the backscattered power can be reconstructed. This processing technique is particularly interesting for the observation of natural targets because it is not sensitive to temporal decorrelation. For this reason, we consider its application to forestry. The goal of this work is twofold: In the first place, an analytical model for assessing the performances of Correlation Tomography is derived and validated through a numerical simulation. Then, a procedure for recovering tomographic products in the presence of very irregular baselines is proposed. This procedure is then tested using real data from the TomoSense campaign.

Tomographic synthetic aperture radar (TomoSAR) is a promising technique for the estimation of forest above-ground biomass (AGB), but knowledge gaps still remain concerning the effects of forest type and ground topography. This article presents new results at P- and L-bands based on data acquired during the TomoSense campaign. The study area is a temperate forest, predominantly beech and spruce, with ground slopes ranging up to 40°. Analysis of vertical reflectivity profiles shows distinct differences for spruce and beech. Three AGB retrieval methods are analyzed, i.e., total vertical backscatter$I_{\text {tot}}$, canopy backscatter from a height layer$I_{c}$, and the ratio$I_{\text {cr}} = I_{c}/I_{\text {tot}}$. All three methods show sensitivity to AGB for spruce, whereas for beech, this is only true for the two latter methods. For the P-band, a significant ground slope effect is observed, while less so for the L-band. The highest$R^{2}$is obtained for spruce with HV polarization,$I_{c}$and ground slopes less than 10°, i.e.,$R^{2} = 0.86$and RMSE =15.6% for P-band and$R^{2} = 0.75$and RMSE =12.5% for L-band. Corresponding results by including all forest types are$R^{2} = 0.77$and RMSE =11.4% for P-band and$R^{2} = 0.54$and RMSE =12.0% for the L-band. Moreover, the performance of using$I_{\text {cr}}$is similar to that of$I_{c}$. The ratio$I_{\text {cr}}$can be determined without absolute radiometric calibration which relaxes system requirements. This article reinforces the potential of TomoSAR for forest AGB estimation and draws attention to important effects of tree species and ground slope.

BIOMASS is new ESA Earth Explorer, scheduled for launch in 2024. It will be the first P-band spaceborne Synthetic Aperture Radar (SAR), featuring full polarimetry, repeat pass interferometry and tomography. Its main objective is global routine monitoring of forested areas, its secondary objectives include exploration of glacier dynamics, subsurface geology and sub-canopy terrain topography. In order to correctly retrieve information, interferometric calibration has to address main disturbances affecting repeat pass P-band SAR: ionosphere, baseline errors and troposphere. In this paper we present the scientific design of BIOMASS interferometric calibration processor, detailing the state-of-the-art correction steps implemented. Some preliminary results obtained by processing simulated acquisitions are illustrated to motivate the proposed techniques.

Synspective, a leading Japanese space tech company, is building a constellation of Synthetic Aperture Radar (SAR) satellites. This paper presents an overview of the state of the constellation as of mid-2023, focusing on key aspects such as radar payload calibration, validation through sea wind retrieval, and the implementation of an automatic quality control system. The paper highlights the calibration procedures employed by Synspective, emphasizing their importance in enabling effective cross-satellite and cross-constellation image analysis. Furthermore, it demonstrates how SAR data can be utilized to retrieve sea wind information and validate the accuracy of calibration parameters. Given the substantial volume of images generated by the constellation, Synspective has implemented an automatic quality control system. This system is seamlessly integrated with the SAR-focusing software, allowing for efficient and reliable monitoring of data quality throughout the satellite’s lifetime to ensure the delivery of high-quality SAR imagery and data products.

ESA BIOMASS will be the first spaceborne P-band SAR, and is designed to produce annual, near-global maps of forest biomass. Biomass-independent scene properties can be mitigated by interferometric pre-processing of the acquisitions, after which backscatter is inverted by a model to estimate biomass, relying on some external reference biomass. The model is simple enough to be invertible, while still representing the spatiotemporal variability of parameters in a global scenario. However, it requires a reliable, global reference biomass dataset, with enough coverage to reflect the variability of the chosen model. The global algorithm is also computationally efficient, so can be deployed in the ground segment. In this paper we briefly discuss the design of the global estimation algorithm for BIOMASS and propose a reference biomass dataset for the algorithm. Then, we discuss the robustness of the proposed algorithm using some reference biomass data for three different parameter variability setups.

This paper compares two techniques for obtaining forest height and vertical structure from synthetic aperture radar (SAR) data, namely SAR tomography (TomoSAR) and phase histogram (PH). The comparison is carried out on an experimental basis by using the tomographic SAR dataset from the TomoSense campaign, flown by ESA in 2020/21 to support investigation of forested area for future low frequency spaceborne SAR missions. Both techniques were tested using data at full and degraded resolution. Experimental results show that the PH technique can only loosely approximate the forest vertical structure produced by SAR tomography, although it was able to achieve a fairly good estimate of forest height if the appropriate range of height of ambiguity is used. A degraded performance of the PH technique when applied to low-resolution data indicates that this technique is best fit for the case of high-resolution data, consistently with the assumption of the presence of dominant scatterers. Overall, these findings indicate the PH technique as an interesting option in the context of high-resolution spaceborne missions.

The new ESA TomoSense campaign aims at investigating a temperate forest located at the Eifel natural park, north-west Germany by means of Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Multifrequency (P, L, C), tomographic SAR data were acquired by repeated flights at different heights. Particularly in L- and C-band surveys, two aircrafts were simultaneously flying operated in a single-pass bistatic interferometric configuration. Such dataset could motivate advanced SAR technologies, and support scientific applications for future spaceborne SAR missions. However, a direct tomographic reconstruction on TomoSense L-band data presented unwanted artifacts due to: i) uncertainties in provided navigational data, and ii) a potential presence of clock mismatches as no dedicated communication link was employed for time synchronization. A dedicated calibration approach is therefore developed to compensate above disturbances using natural scatterers. Experimental results indicate that our proposed calibration approach is able to remarkably enhance the interferometric and tomographic performances on TomoSense L-band data.

3-D imaging using SAR tomography is a well-recognized technique for the characterization of forested areas. Studies revealed that the intensity of radar echoes originating from specific locations within the canopy of forest could be used to estimate its above ground biomass. Moreover, a recent work proposed an estimation technique using a pair of interferometric SAR images only. The images are combined in order to cancel contributions from the ground, and to roughly estimate the volume reflectivity. This paper proposes to study the influence of temporal decorrelation of this minimalist approach, which relies on the hypothesis of perfectly correlated signals. A model, based on second order statistics, is proposed and is used to predict the influence of temporal decorrelation of the relative error of the above ground biomass estimation over tropical forests measured at$\mathrm{P}$band.

The new ESA TomoSense campaign includes both airborne and in-situ measurements over a temperate forest in northern Germany. SAR surveys are complemented by several LiDAR acquisition thus making one of the most complete datasets available for forest studies. Tomographic, fully-polarimetric and opposite views acquisitions are available at P- L- and C-bands; furthermore, both monostatic and bistatic data are available at L- and C-bands. These latter acquisition modes required ad-hoc calibration strategies for clean tomograms to be obtained. Also, the baseline distribution of the L-band data motivated the creation of a new model-based tomographic approach for mono-bistatic pairs. The effectiveness of the proposed processing chain is here proved with coherence maps and tomographic profiles. The quality of the tomographic reconstruction is also confirmed by comparing estimates of biophysical parameters with LiDAR measurements.

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.

Polarimetric Synthetic Aperture Radar Tomography (TomoSAR) is a technology to image the three-dimensional (3D) structure of the illuminated media. TomoSAR exploits the key feature of microwaves to penetrate into vegetation, snow, and ice, hence providing the possibility to see features that are hidden to optical and hyper-spectral systems. Several experimental studies by different research groups demonstrate that the use of the 3D information results in an accurate characterization of forested areas, providing access to a number of biophysical variables such as terrain topography below the vegetation, forest height, forest Above Ground Biomass (AGB), and forest classification. This paper is intended to provide the reader with an introduction to the use of TomoSAR for the characterization of forest areas, addressing basic imaging principles and methods, retrieval of biophysical parameters, and perspective for spaceborne missions.

The TomoSense experiment comprises campaign and research activities in support of future Synthetic Aperture Radar (SAR) mission concepts at P-, L-, and C-band by the European Space Agency (ESA). The research is intended to provide a quantitative basis for the evaluation of single-pass interferometry over temperate forests at L- and C-band and investigate potential synergies between C-band convoy mission concepts and future P- and L-band missions. SAR acquisitions include P- L-, and C-band data acquired at the Eifel National Park in Germany by flying approximately 25 trajectories to provide tomographic imaging capabilities. Land C-band data were acquired by simultaneously flying two aircraft to gather bistatic data with varying interferometric baselines. Field activities include forest census (dbh, tree height and species) at 80 plots and Terrestrial Laser Scanning (TLS). The dataset is complemented by small-footprint Airborne Lidar Scanning (ALS) and derived products. Preliminary results are here shown relative to polarimetric tomography at P-band and L-band imaging.

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.

The new ESA TomoSense campaign aims to explore the retrieval of biophysical quantities over forests for different acquisition geometries and radar parameters. Tomographic SAR acquisitions are currently being carried out using different wavelengths, both monostatic and bistatic systems and opposite views. This work presents the current advances in the analyses and calibration of the TomoSense data stacks to make them suited for scientific analyses. Airborne monostatic P-band acquisitions as received by MetaSensing presented artifacts connected to the acquisition geometry. Coherence and phase fluctuations were compensated thus obtaining clean tomographic reconstructions and a clear identification of the terrain level. Bistatic L-band data are expected to be available in short time as well.

Tomography SAR (TomoSAR) methods recover the 3D structure of targets by processing several SAR images simultaneously. Depending on the degree of approximation, recovering the vertical structure can amount to a 1D problem (processing a vector of pixels), a 2D problem (processing a matrix) or a 3D problem (processing the whole 3D stack at once). The computational burden decreases from the 3D to the 1D, but the constraints for a proper reconstruction are tighter. Hence, this paper discusses the limit and criterion for the feasibility of each method. The huge computational burden of TomoSAR 3D method is addressed by a fast implementation on GPUs. Theoretical analyses and our approach are demonstrated on simulated data, as well as on real data from the ESA AlpTo-moSAR campaign.

SAR tomography is a powerful tool for analyzing forested environments. ESA seventh Earth Explorer BIOMASS will be the first spaceborne tomographic mission at P-band returning three dimensional reconstruction of the tropical vegetation. The backscattered intensity coming from specific depths inside the forest layer can be effectively related to biophysical parameters as tree height or biomass amount. Biomass estimates are very sensitive to power fluctuations in the measurements that, therefore, have to be minimized. In this work, the tomographic power fluctuations induced by irregular acquisitions and missing images are addressed. Compensation strategies are presented and their effectiveness is demonstrated using real data gathered on tropical forests.

In this letter, we present an experimental assessment of vegetation height retrieval in tropical forests based on P-band synthetic aperture radar (SAR) acquisitions. Two approaches are implemented and compared: 1) parametric height estimation by minimizing the least-square problem between random volume over ground (RVoG) model predictions and multibaseline SAR data and 2) thresholding the vertical backscattering profiles that are focused by SAR Beam-forming tomography. The data set under analysis is from the ESA AfriSAR campaign that was flown over Gabon in 2016. Results show that at a resolution of 25 m × 25 m, which corresponds to about 80 independent looks, both of the two approaches are able to retrieve forest height to within an accuracy of about 3 m or better over the interval of forest height between 30 and 50 m when compared to Light Detection and Ranging (LiDAR) measurements.

A new processing technique, i.e., ground cancellation, which removes the ground signal from a pair of interferometric synthetic aperture radar (SAR) images, is used to emphasize the response from above-ground targets. This technique is of particular interest when studying forest canopies using low-frequency signals able to reach the underlying ground, in which case the portion of the signal coming from the ground interferes with the recovery of information about the vegetation. We demonstrate that the power in ground-canceled P-band HV SAR data gives significantly higher correlations with above-ground biomass (AGB) than the interferometric images considered separately. In addition, a significant increase in the sensitivity of backscatter to AGB is observed. Ground-canceled power may then be modeled or regressed to estimate AGB; these possibilities are not discussed here as they will be the topic of forthcoming publications. The effectiveness of this technique is proven through simulations and analysis of real data gathered on tropical forests. The stability of the technique is analyzed under the digital terrain model and baseline control errors, and compensation strategies for these errors are presented.

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.

In this work we investigate the role of volume scattering obtained from tomography and ground/volume decomposition in retrieving AGB (Above Ground Biomass). Results here presented originate from the BIOMASS L2 study, aimed at defining and implementing the tomographic and interferometric processors of the BIOMASS mission. In particular we aim at discussing whether, and to what extent, ground/volume decomposition can provide a valid alternative to tomography. To do this, both are tested based on the P-Band data collected at the forest site of Paracou, French Guiana, during the TropiSAR campaign, and validated against in-situ AGB measurements in terms of correlation and sensitivity of the retrievals. Quite surprisingly, results indicate that volumebackscattered power as obtained by ground/volume decomposition is almost unsensitive to AGB, notwithstanding different solutions for volume scattering are tested, and lead to conclusion that forest structure actually plays a non-negligible role in AGB retrieval in tropical areas.

The Italian Space Agency (ASI) has recently entrusted CO.RI.S.T.A. with the development of a radar system that can be mounted onboard small airplanes or helicopters and may operate, at different frequencies belonging to the P-Band, either as Synthetic Aperture Radar (SAR) or as Sounder. In this work, we present preliminary results of the helicopter-borne desert campaign carried out with this system in 2018 over the Erfoud area, Morocco, in the frame of a project that has involved different public Italian Research Institutes and Universities.

The problem of estimating above ground biomass in tropical regions has been recently tackled by using tomographic SAR data at low frequencies. The added value of tomography is the possibility of focusing on specific heights inside of the vegetation layer, rejecting the echoes coming from other elevations at the same time; in particular, the strong echoes coming from the ground level are greatly attenuated. Recently, a simpler algorithm aiming at this goal has been proposed: the interferometric ground notching. According to this algorithm, two InSAR images are coherently combined to cancel out the ground echo and emphasize the forest backscattering. However, any time lag between the two images introduces temporal decorrelation which, in turn, affects the effectiveness of the coherent subtraction. This work shows an analysis of the effect of the temporal decorrelation from a theoretical point of view and through experiments on real data; results from a boreal forest and a tropical one are presented. As predicted by the theory the impact on the radiometric stability results limited to within 0.5-1dB for taller forest where most of the biomass is stored.

Due to the considerable resources investment, fine tuning the parameters of a spaceborne SAR system far in advance is very important. Most of them can be set by resorting to synthetic data, however models of complex natural phenomena are often not reliable enough to drive the choice. In this case, real data coming from airborne campaigns might be used as long as it is properly translated in a spaceborne setting. The problem of simulating spaceborne acquisitions was recently tackled and led to the definition of a new algorithm here exploited to analyze the effect of small changes in the system parameters. This work presents an analysis of the bond between biomass and tomography varying the orbits of the simulated spaceborne system. Different look angles and total baseline apertures are explored; moreover, random fluctuations of the trajectories are considered. These analyses provide recommendations about the nominal orbits and their accuracy.

This paper focuses on the retrieval of terrain topography below dense tropical forests by means of synthetic aperture radar (SAR) systems. Low-frequency signals are needed to penetrate such a thick vegetation layer; however, this expedient alone does not guarantee proper retrieval. It is, here, demonstrated that the phase center of P-band backscatter may lie several meters above the ground, depending on the slope and incidence angle. SAR tomography is shown to overcome this problem and retrieves the actual topography even in the presence of dense trees up to 50 m tall. Digital terrain models returned by SAR tomography are, here, put in comparison with light detection and ranging (LiDAR) terrain models: the accuracy of radar-derived maps is found to be at least comparable with the one offered by LiDAR systems. Moreover, the discrepancy between tomography and LiDAR is larger if large-footprint LiDAR is considered thus suggesting that, in this case, tomographic maps should be considered the reference height. Analyses are carried out by processing three data sets gathered over different tropical forests in western Africa. The robustness of the radar estimates is assessed with respect to both ground slope and treetop height.

The effectiveness of SAR tomography in estimating forest Above Ground Biomass (AGB) has been repeatedly demonstrated in the recent years. For tropical rain-forests, analysis from the Paracou test site reveals that the best results are achieved when the backscattered power coming from 30m above the ground is considered. As suggested in previous papers, the most likely reason is that ground scattering acts as a disturbing factor for forest biomass retrieval, as it depends on a number of parameters (like topography, moisture), that do not relate to forest biomass. In this paper we further test this hypothesis by proposing the concept of interferometric ground notching. By taking the difference between two phase calibrated, ground-steered, SAR SLC images a third image is obtained where ground scattering contributions are canceled out, hence the name ground-notched SLC. Results indicate that ground-notched data can effectively retain the features of vegetation-only scattering, including its polarimetric signature and correlation with AGB.

We propose a full Space and Time Coherent Change Detection (ST-CCD) that takes advantage of Sentinel-1 (S1) short interferometric revisit to enhance sensitivity in detecting changes at a fine space resolution. It extends the Generalized Likelihood Ratio Test (GLRT) used for change detection by single baseline images, to the multi-pass, multi-polarimetric stacks of S1 data. Applications are shown for damage mapping after hazards and for agriculture. A preliminary validation is performed by processing data referred to central Italy earthquake in 2016.

The objective of this paper is to provide a better understanding of tomographic capabilities to estimate above ground biomass (AGB) in dense forested areas at P-band. The analysis is carried out on airborne data acquired over sites in French Guyana and in Gabon during the ESA campaigns TropiSAR and AfriSAR 2015, respectively. Over both sites, P-band tomography allows us to retrieve the vertical structure of the forest, to better characterize the ground and/or volume scattering mechanisms and to provide a unique solution for the AGB retrieval over the full range of biomass. The relationship between AGB and tomography data was found to be highly similar for forests across continents and sites: Paracou (French Guiana), Lope, Rabi and Mondah (Gabon). The developed metrics derived from the tomographic data have been found highly correlated to reference in situ AGB estimates (R2=0.85) and the root mean square error was 16% (for AGB ranging from 0 to 500 t/ha). These results have strong implications for the tomographic phase of the BIOMASS spaceborne mission.

This paper presents a new algorithm for forest biomass estimation from P-band synthetic-aperture radar (SAR) backscatter data, notch-filtered at ground-level. A semi-empirical model is fitted to spatial and polarization trends in the backscatter data and no reference biomass data are needed for training. An evaluation on airborne P-band SAR data from a tropical test site in Gabon results in a root-mean-square error lower than 20% and a correlation better than 90%.

Forest biomass is a most important parameter in the context of the global carbon cycle. Mapping above ground biomass (AGB) at a global scale contributes to understanding the dynamics of climate change. Tropical forests are extremely important as they store more biomass. In recent years, SAR tomography has been introduced as a new technique that has shown enormous potential in AGB retrieval. A strong linear relationship between in-situ measurements and tomographic power from 30 m above the terrain was discovered by previous studies carried out in French Guiana. However, the two parameters that determine the linear relationship might vary for different tropical forests. Due to the great difficulty in measuring tropical forest AGB by field surveys, in-situ measurements is unfeasible to relate SAR tomography for mapping global forests AGB. For purpose of solving this problem, we investigate the possibility to use LiDAR derived AGB to find the two parameters of the fit line. Experimental results obtained by processing data from the TropiSAR campaign support the feasibility of the proposed concept.

This paper presents the results achieved by SAR tomography in estimating digital terrain models under tropical forests. Several airborne data stacks have been processed, they have been gathered on dense forests in central Africa in the framework of the AfriSAR campaign and in South America. The joint exploitation of polarimetry and multi baseline interferometry enabled to separate ground from vegetation above and to analyze it alone. Also, airborne LIDAR measurements were available and provided a reliable comparison. Results indicate that terrain topography in tropical forests can be retrieved by P-Band SAR Tomography to within an accuracy at least comparable to that of LIDAR systems. Furthermore, few meaningful details visible in SAR derived DTMs are missing in LIDAR maps probably due to the high density of the vegetation layer.

This paper describes a geometrically rigorous approach for generating a synthetic SAR Tomographic data-set starting from a real one acquired from a different geometry, using large pulse bandwidth and eventually a (slightly) different carrier frequency. This change is made possible by properly taking into account the spectral properties of the scene under observation. Special attention has been paid to the possibility of simulating spaceborne data starting from airborne ones. Data of the forthcoming ESA BIOMASS mission have been simulated from airborne campaigns on tropical forests. The simulated tomographic data preserves the original vertical structure of the illuminated scene as well as total backscat-tered power, while ensuring full consistency between the resulting 3D Impulse Response Function (IRF) and the simulated geometry. The simulation is demonstrated to preserve the same correlation to forest Above Ground Biomass (AGB) as the original airborne data-set and a high sensitivity too.

This paper focuses on the detection, from a stack of repeated-pass interferometric synthetic aperture radar (SAR) images, of such changes causing a target to completely lose the correlation between one epoch and another. This can be the consequence of human activities, such as construction, destruction, and agricultural activities, and also be the consequence of hazards, such as earthquake, landslides, or flooding, to buildings or terrains. The millimetric sensitivity of SAR makes it valuable for detecting such changes. This paper approaches two coherent change detection methods: a space coherent, time incoherent one and a full space and time coherent one, both based on the generalized likelihood ratiob (LR) test. A preliminary validation of the method is provided by processing two Sentinel-1 data stacks of 2016 Central Italy earthquake and by comparing the results with the map of damaged buildings in Amatrice and Accumoli made by Copernicus Emergency Management Service.

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.

This work aims to describe the characteristics and the status of development, including the results of a first preliminary testing campaign, of a low frequency airborne imaging radar developed in Italy for the Italian Space Agency.

A fundamental requirement for coherent processing of repeat pass SAR data stacks is to have precise knowledge of the relative position of each track. Indeed, sub-wavelength position errors give rise to residual phase screens among different passes, which hinder coherent applications. In this paper we describe an approach to estimate and remove phase screens by exploiting distributed targets, based on the concept of equivalent phase center. The proposed approach is demonstrated through numerical simulations and using campaign data. A cross-check of the results from simultaneous P- and L-Band acquisitions indicates that the dispersion of the retrieved flight trajectories is limited to a few millimeters. Preliminary results indicate that Capon-based tomographic imaging is more sensitive to phase errors, potentially resulting in artifacts that do not appear in Fourier-based approaches.

Synthetic aperture radar (SAR) data collected over a 2-D synthetic aperture can be processed to focus the illuminated scatterers in the 3-D space, using a number of signal processing techniques generally grouped under the name of SAR tomography (TomoSAR). A fundamental requirement for TomoSAR processing is to have precise knowledge of the platform position along the 2-D synthetic aperture. This requirement is not easily met in the case where the 2-D aperture is formed by collecting different flight lines (i.e., 1-D apertures) in a repeat-pass fashion, which is the typical case of airborne and spaceborne TomoSAR. Subwavelength platform position errors give rise to residual phase screens among different passes, which hinder coherent focusing in the 3-D space. In this paper, we propose a strategy for calibrating repeat-pass tomographic SAR data that allows us to accurately estimate and remove such residual phase screens in the absence of reference targets and prior information about terrain topography and even in the absence of any point- or surface-like target within the illuminated scene. The problem is tackled by observing that multiple flight lines provide enough information to jointly estimate platform and target positions, up to a roto-translation of the coordinate system used for representing the imaged scene. The employment of volumetric scatterers in the calibration process is enabled by the phase linking algorithm, which allows us to represent them as equivalent phase centers. The proposed approach is demonstrated through numerical simulations, in order to validate the results based on the exact knowledge of the simulated scatterers, and using real data from the ESA campaigns AlpTomoSAR, BioSAR 2008, and TropiSAR. A cross-check of the results from simultaneous P- and L-band acquisitions from the TropiSAR data set indicates that the dispersion of the retrieved flight trajectories is limited to a few millimeters.

ALOS-2 satellite has been successfully launched by JAXA on May 24th 2014, it is equipped with an L-Band (PALSAR-2) fully polarimetric SAR. Many improvements have been made with respect to the former ALOS satellite: the exploitation of a dual receiving antenna allows to broaden the imaged swath whereas spotlight mode ensures a very high resolution on a specific location. The revisit time has been lowered from 46 to 14 days and the possibility to provide both left and right looking capability ensures a fast coverage in case of emergencies. The features of the ALOS-2 SAR system are designed to provide monitoring of vegetation (deforestation, agricultural areas), topographic changes (landslides, earthquakes) and several kind of disasters (volcanoes' eruptions, oil spills). The work here presented shows the preliminary calibration assessment of the radar images of ALOS-2. In particular the polarimetric calibration has been analyzed together with the achievable IRF; furthermore, interferometric analyses have also been carried out to assess RFI filtering effect on inter-ferometric phase.

In order to help in the calibration process of the soil moisture map produced by current (SMAP) and future (SAOCOM) missions, a dense network of automatic soil-moisture probes has been set in Monte Buey (Córdoba, Argentina). A series of intensive calibration campaigns were done over the last two years to calibrate the sensors and validate the soil moisture map at various scales. Some of the results are presented here.

The next ESA Earth Explorer Core Mission BIOMASS is envisaged to collect multiple baselines on selected areas during the initial phase of its lifetime. Such data will allow to image the vertical structure of the vegetation layer to within a vertical resolution of about 20 m, sufficient to decompose the backscattered power from a tropical forest into two-three layers. The information provided by tomography has recently been shown to be strictly linked to above ground biomass (AGB) in tropical forest, therefore providing a valuable tool for ABG estimation. The aim of this paper is to present a bird-eye overview of BIOMASS Tomography, along with the main experimental results from airborne campaigns flown during Phase-A BIOMASS activities.

The retrieval of above-ground biomass (AGB) in dense tropical forests using synthetic aperture radar (SAR) images is widely recognized as a challenging task. The first difficulty arises from the decrease of sensitivity of the backscattered intensity to biomass at high biomass values, often referred to as the backscatter saturation effect. At P-band, the decrease of sensitivity can occur at biomass values higher than about 300${\rm t~ha}^{-1}$, e.g., those of many dense tropical forests. Another limiting factor is associated with the ground effects, as they can change significantly the magnitude of returns from vegetation–ground interactions. As a consequence, terrain topography or ground moisture status can determine the variations of the observed signal that are not due to forest biomass. A solution to reduce the ground effects is to have access to layers inside the forest canopy where the backscatter from vegetation–ground interactions is not significant. The study presented in this paper is an attempt to overcome the issues outlined above based on direct 3-D imaging of the forest volume, which is possible through multibaseline SAR tomography. In this way, forest biomass can be investigated by considering not only the backscattered power at each slant range and azimuth location but also its vertical distribution. The data analyzed in this paper are from the P-band airborne dataset acquired by Office National d'Études et de Recherches Aérospatiales (ONERA) over French Guiana in 2009, in the frame of the European Space Agency campaign TropiSAR. The dataset is characterized by a favorable baseline distribution, resulting in a vertical resolution less than half the forest height, which made it possible to decompose the vertical distribution of the backscattered power into a number of layers by coherent focusing, i.e., without assuming any prior knowledge about the forest vertical structure. For each layer, the relationship between the backscattered power and forest AGB was then analyzed. As expected, it was found that the power from the bottom layer is very weakly correlated to AGB, whereas the power from a layer at about 30 m above the ground yields the best correlation and sensitivity to AGB in all polarizations, for actual AGB values ranging from 250 to 450${\rm t~ha}^{-1}$. An interpretation of this result is also provided, based on a forest growth model simulation. Finally, the relevance of tomographic technique in P-band spaceborne mission is discussed.

In this paper we propose a strategy for phase calibrating repeat-pass Synthetic Aperture Radar (SAR) data for tomographic applications. The problem is tackled by observing that multi-baseline data provide equations enough to jointly estimate aircraft and target positions, up to a rototranslation of the coordinate system used for representing the imaged scene. Such a rototranslation is shown to correspond to the forward operator null space, which can be accounted for in order to project the results in the desired coordinate frame. Volumetric scatterers are treated by exploiting the Phase Linking algorithm, which allows to represent them as equivalent phase centers. Results are shown from synthetic data and real SAR data acquired over snow and ice.

This paper aims at characterizing the scattering mechanisms occurring at the ground level in a tropical forest illuminated by a P-band synthetic aperture radar (SAR). The analysis is carried out based on the multibaseline, fully polarimetric, data set collected by ONERA over Paracou, French Guyana, in the frame of the European space agency campaign TropiSAR. The favorable baseline distribution of this data set results in the possibility of removing most contributions from the vegetation layer by tomographic techniques, thus allowing the generation of a new fully polarimetric single look complex SAR image relative to scattering contributions from the ground level only. Such a ground layer image is then analyzed by considering the variation of its polarimetric signature with respect to terrain local slope and Radar look angle. Two major conclusions are drawn: 1) double bounce scattering from trunk-ground interactions is observed to be the dominant scattering mechanism at the ground level on flat terrains, whereas it rapidly tends to vanish as the topographic slope increases, and 2) the characteristic parameter that rules trunk-ground scattering is not the tree height, but rather the available free path facing the tree, as a result of the presence of nearby trees, undulating topography, or understory preventing double bounce scattering from taking place whenever the ground bounce occurs too far away from the considered tree. The mean free path length resulting from the analysis of this data-set is found to be L ≅ 7 m. Finally, we discuss how the concept of free path length can be accounted for in simple terms by assuming an equivalent extinction model characterized by a variation along the horizontal dimension.

The retrieval of above-ground biomass in dense tropical forests using Synthetic Aperture Radar (SAR) images is widely recognized as a challenging task, because of the backscatter saturation effect at high biomass values and the ground topography effect. The study presented in this paper is an attempt to overcome these issues based on direct three-dimensional imaging of the forest volume, which is possible through multi-baseline SAR tomography. In this way, forest biomass can be investigated by considering not only the backscattered power at each slant range, azimuth location, but also its vertical distribution. It was found that the power from the a layer at 30m ± 10m above the ground yields the best correlation and best sensitivity with forest biomass in all polarizations, for biomass ranging from 250 to 450 tons/ha.

This paper aims at characterizing the scattering mechanisms occurring at the ground level in a tropical forest illuminated by a P-Band SAR. The analyzed data set is the one collected by ONERA over Paracou, French Guyana, in the frame of the ESA campaign TropiSAR. The favorable baseline distribution of this data set results in the possibility to remove most contributions from the vegetation layer by tomographic techniques, thus allowing a direct investigation of ground scattering. Two major conclusions are drawn: i) double bounce scattering from trunk-ground interactions is observed to be the dominant scattering mechanism at the ground level on flat terrains, whereas it rapidly tend to vanish as the topographic slope increases; ii) the characteristic parameter that rules trunk-ground scattering is not the tree height, but rather the available free path facing the tree, as a result of the presence of nearby trees or understory preventing double bounce scattering from taking place whenever the ground bounce occurs too far away from the considered tree.

The aim of this letter is to discuss recent results from the tomographic analysis of the P-band synthetic aperture radar multibaseline data set acquired by ONERA over French Guyana, in the frame of the European Space Agency campaign TropiSAR. Such a data set is characterized by a vertical resolution of about 20 m, whereas forest height ranges from 20 to 40 m. These features make it possible to map the 3-D distribution of the scene complex reflectivity in up to three independent layers by coherent focusing, i.e., without assuming any physical model or employing superresolution techniques. The most relevant features within the observed results are the presence of dihedral-like scattering in the ground layer, which is hardly noticeable in the original single-look complex data, and the substantial invariance of the innermost forest layer to topographic slopes.

In this paper we discuss some relevant features observed concerning wave penetration at P-band in boreal and tropical forests. The discussion will be based on results obtained from the multi-polarimetric and multi-baseline data-sets relative to the forest sites within the Krycklan river catchment, Sweden, and the area of Paracou in French Guyana, collected in the frame of the ESA campaign BioSAR 2008 and TropiSAR 2009, respectively. The analysis is carried out by exploiting the SAR tomography technique, which allows to separate backscattering contributions from different heights within the vegetation layer. One first relevant result is relative to the difference between the vertical distribution of the backscattered power in the two investigated test sites. In the boreal forest site the most relevant scattering contributions are observed at the ground level, not only in copolarized channels but also in HV, whereas in the tropical forest the presence of scattering from the ground is poorer and the vegetation volume is well visible. Most relevant features of the investigated tropical forest site are those relative to the dependency of the vertical backscattering distribution with respect to topographic slope and forest biomass. In particular, the innermost forest layer is observed to be substantially invariant to topographic slopes, whereas the backscattered power at 30 m above the ground is observed to yield the best connection with forest biomass, resulting, in this case, in a correlation factor of 0.82 with respect to in-situ measurements at 125 m spatial resolution.

This paper deals with the estimation of terrain topography from multipass synthetic aperture radar (SAR) interferometry (InSAR), focusing on the case where variation of the system geometry within the imaged swath is relevant. A typical case is represented by airborne multipass interferometric campaigns where, due to the closeness between the radar sensor and the targets, the incidence-angle sensitivity undergoes a dramatic increase with respect to the spaceborne case, resulting in a high spatial variability of the normal baselines. The space-varying nature of the system geometry gives rise to a major issue in multipass InSAR analyses in that it prevents from compensating for the presence of interferogram phase offsets by simply phase locking the data stack to a reference point, therefore hindering the retrieval of terrain topography. To cope with this issue properly, we propose a novel approach that exploits the algebraic properties of the problem. Such an approach allows casting the problem in terms of identification of a null-space component for terrain topography after which both topography and the interferogram phase offsets are quickly obtained without exploiting calibration points. Experimental results are shown based on a P-band data set acquired by the Experimental SAR (E-SAR) airborne system, operated by the German Aerospace Center (DLR), in the framework of the European Space Agency (ESA) campaign BIOSAR 2008.

This work deals with the estimation of terrain topography from multi-pass Synthetic Aperture Radar (SAR) interferometry (InSAR), focusing on the case where the variation of the system geometry within the imaged swath is relevant, as in airborne multi-pass interferometric campaigns. The space varying nature of the system geometry gives rise to a major issue in multi-pass InSAR analyses, in that it prevents from compensating for the presence of interferogram phase offsets by simply phase locking the data stack to a reference point, therefore hindering the retrieval of terrain topography. To cope with this issue properly we propose a novel approach that exploits the algebraic properties of the problem. Such an approach allows to cast the problem in terms of identification of a null space component for terrain topography, after which both topography and the interferogram phase offsets are quickly obtained without exploiting calibration points.

SAR data gathered from forested areas collect contributions coming from the vegetation layer, from the ground below and from other scattering mechanisms (SMs). Multi-baseline data allow a tomographic analysis thus retrieving information about the vertical structure of the target. Multi-polarimetric acquisitions enrich the data, providing ways to identify the targets basing on their electromagnetic properties. The joint exploitation of multi-polarimetric and multi-baseline data suggests the possibility of linking the estimation of the vertical structure of different SMs with their polarimetric signature. A formal framework in which this task can be accomplished is provided by the Algebraic Synthesis (AS) technique, which extends the concepts within PolInSAR through the assumption of the Sum of Kronecker Products (SKP) structure. By assuming the presence of two SMs (for example ground and volume scattering), the SKP assumption leads to a cross dependence between the polarimetric and interferometric coherences, in that ground structure is shown to be related to volume polarimetry, and dually volume structure is shown to be related to ground polarimetry. The aim of this paper is to investigate the implications of this cross relation. Experimental results will be shown basing on a data-set of multi-polarimetric and multi-baseline SAR images at P-band acquired by DLR's E-SAR over the Krycklan catchment, in northern Sweden, in the framework of the ESA campaign BioSAR 2008.