This paper focuses on multiimage synthetic aperture radar interferometry (InSAR) in the presence of distributed scatterers, paying particular attention to the role of target decorrelation in the estimation process. This phenomenon is accounted for by splitting the analysis into two steps. In the first step, we estimate the interferometric phases from the data, whereas in the second step, we use these phases to retrieve the physical parameters of interest, such as line-of-sight (LOS) displacement and residual topography. In both steps, we make the hypothesis that target statistics are at least approximately known. This approach is suited both to derive the performances of InSAR with different decorrelation models and for providing an actual estimate of LOS motion and topography. Results achieved from Monte Carlo simulations and a set of repeated pass ENVISAT images are shown.

Longer wavelength synthetic aperture radars (SARs) are precious in the remote sensing of forested areas, being sensitive to contributions from the whole vegetation layer and from the ground below. The electromagnetic properties of such contributions are retrieved from multipolarimetric acquisitions, whereas their vertical structure is retrieved from multibaseline acquisitions through tomographic imaging. Combining baseline and polarization diversity provides most information, allowing the decomposition of the SAR signal into ground- and volume-only contributions. A formal treatment of this problem is provided with the algebraic synthesis technique, which extends the concepts of PolInSAR. The decomposition, however, is shown to be ambiguous in that different solutions are equally consistent with the data. The main goal of this paper is to discuss this topic in light of the experimental results from a tomographic and polarimetric analysis of the boreal forest within the Krycklan River catchment, Northern Sweden, investigated at P- and L-bands during the ESA campaign BioSAR 2008. Different solutions to the decomposition problem will be discussed by examining the corresponding vertical structures accessible through tomographic techniques. Elements are shown supporting the idea that ground-volume interactions play a nonnegligible role at P-band, and a solution is proposed to isolate contributions from direct volume backscattering. The retrieval of forest top height is discussed as well, leading to the conclusion that such parameter is robust against erroneous choices in the identification of volume-only contributions, thus corroborating the PolInSAR approach for the analysis of single-baseline data.

In this paper, a new methodology is proposed for the analysis of forested areas basing on multipolarimetric multibaseline synthetic aperture radar (SAR) surveys. Such a methodology is based on three hypotheses: 1) statistical uncorrelation of the different scattering mechanisms (SMs), such as ground, volume, and ground-trunk scattering; 2) independence of volumetric and temporal coherence losses of each SM on the choice of the polarimetric channel; and 3) invariance (up to a scale factor) of the average polarimetric signature of each SM with respect to the choice of the track. Under these hypotheses, the data covariance matrix can be expressed as a Sum of Kronecker Products, after which it follows that K SMs are uniquely identified by K (K - 1) real numbers. This result provides the basis to perform SM separation by employing not only model-based approaches, generally retained in literature but also model-free and hybrid approaches, while yielding the best Least Square solution given the hypothesis of K SMs. It will be shown that this approach to SM separation is consistent with the inversion procedures usually exploited in single-baseline polarimetric SAR interferometry. Experimental validation of this methodology is provided on the basis of the P-band data set relative to the forest site of Remningstorp, Sweden, acquired by German Aerospace Center's E-SAR airborne system in the framework of the European Space Agency campaign BioSAR.

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 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 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.

International audienceDeveloping and improving methods to monitor forest carbon in space and time is a timely challenge, especially for tropical forests. The next European Space Agency Earth Explorer Core Mission BIOMASS will collect synthetic aperture radar (SAR) data globally from employing a multiple baseline orbit during the initial phase of its lifetime. These data will be used for tomographic SAR (TomoSAR) processing, with a vertical resolution of about 20 m, a resolution sufficient to decompose the backscatter signal into two to three layers for most closed-canopy tropical forests. A recent study, conducted in the Paracou site, French Guiana, has already shown that TomoSAR significantly improves the retrieval of forest aboveground biomass (AGB) in a high biomass forest, with an error of only 10% at 1.5-ha resolution. However, the degree to which this TomoSAR approach can be transferred from one site to another has not been assessed. We test this approach at the Nouragues site in central French Guiana (ca 100 km away from Paracou), and develop a method to retrieve the top-of-canopy height from TomoSAR. We found a high correlation between the backscatter signal and AGB in the upper canopy layer (i.e. 20–40 m), while lower layers only showed poor correlations. The relationship between AGB and TomoSAR data was found to be highly similar for forests at Nouragues and Paracou. Cross validation using training plots from Nouragues and validation plots from Paracou, and vice versa, gave an error of 16–18% of AGB using 1-ha plots. Finally, using a high-resolution LiDAR canopy model as a reference, we showed that TomoSAR has the potential to retrieve the top-of-canopy height with an error to within 2.5 m. Our analyses show that the TomoSAR-AGB retrieval method is accurate even in hilly and high-biomass forest areas and suggest that our approach may be generalizable to other study sites, having a canopy taller than 30 m. These results have strong implications for the tomographic phase of the BIOMASS spaceborne mission