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.
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.
Mapping tropical forest aboveground biomass (AGB) is important for quantifying emissions from land use change and evaluating climate mitigation strategies but remains a challenging problem for remote ...sensing observations. Here, we evaluate the capability of mapping AGB across a dense tropical forest using tomographic Synthetic Aperture Radar (TomoSAR) measurements at P-band frequency that will be available from the European Space Agency's BIOMASS mission in 2024. To retrieve AGB, we compare three different TomoSAR reconstruction algorithms, back-projection (BP), Capon, and MUltiple SIgnal Classification (MUSIC), and validate AGB estimation from models using TomoSAR variables: backscattered power at 30 m height, forest height (FH), backscatter power metric (Q), and their combination. TropiSAR airborne campaign data in French Guiana, inventory plots, and airborne LiDAR measurements are used as reference data to develop models and calculate the AGB estimation uncertainty. We used univariate and multivariate regression models to estimate AGB at 4-ha grid cells, the nominal resolution of the BIOMASS mission. Our results show that the BP-based variables produced better AGB estimates compared to their counterparts, suggesting a more straightforward TomoSAR processing for the mission. The tomographic FH and AGB estimation have an average relative uncertainty of less than 10% with negligible systematic error across the entire biomass range (~ 200-500 Mg ha
). We show that the backscattered power at 30 m height at HV polarization is the best single measurement to estimate AGB with significantly better accuracy than the LiDAR height metrics, and combining it with FH improved the accuracy of AGB estimation to less than 7% of the mean. Our study implies that using multiple information from P-band TomoSAR data from the BIOMASS mission provides a new capability to map tropical forest biomass and its changes accurately.
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4.
Coherent Change Detection for Multipass SAR Monti-Guarnieri, Andrea Virgilio; Brovelli, Maria Antonia; Manzoni, Marco ...
IEEE transactions on geoscience and remote sensing,
11/2018, Volume:
56, Issue:
11
Journal Article
Peer reviewed
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.
Synthetic Aperture Radar (SAR) Tomography is a technique to provide direct three-dimensional (3D) imaging of the illuminated targets by processing SAR data acquired from different trajectories. In a ...large part of the literature, 3D imaging is achieved by assuming mono-dimensional (1D) approaches derived from SAR Interferometry, where a vector of pixels from multiple SAR images is transformed into a new vector of pixels representing the vertical profile of scene reflectivity at a given range, azimuth location. However, mono-dimensional approaches are only suited for data acquired from very closely-spaced trajectories, resulting in coarse vertical resolution. In the case of continuous media, such as forests, snow, ice sheets and glaciers, achieving fine vertical resolution is only possible in the presence of largely-spaced trajectories, which involves significant complications concerning the formation of 3D images. The situation gets even more complicated in the presence of irregular trajectories with variable headings, for which the one theoretically exact approach consists of going back to raw SAR data to resolve the targets by 3D back-projection, resulting in a computational burden beyond the capabilities of standard computers. The first aim of this paper is to provide an exhaustive discussion of the conditions under which high-quality tomographic processing can be carried out by assuming a 1D, 2D, or 3D approach to image formation. The case of 3D processing is then further analyzed, and a new processing method is proposed to produce high-quality imaging while largely reducing the computational burden, and without having to process the original raw data. Furthermore, the new method is shown to be easily parallelized and implemented using GPU processing. The analysis is supported by results from numerical simulations as well as from real airborne data from the ESA campaign AlpTomoSAR.
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Synthetic aperture radar (SAR) tomography (TomoSAR) is an emerging technology to image the 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. The research on the use of P-band waves, in particular, has been largely propelled since 2007 in experimental studies supporting the future spaceborne Mission BIOMASS, to be launched in 2022 with the aim of mapping forest aboveground biomass (AGB) accurately and globally. The results obtained in the frame of these studies demonstrated that TomoSAR can be used for accurate retrieval of geophysical variables such as forest height and terrain topography and, especially in the case of dense tropical forests, to provide a more direct link to AGB. This paper aims at providing the reader with a comprehensive understanding of TomoSAR and its application for remote sensing of forested areas, with special attention to the case of tropical forests. We will introduce the basic physical principles behind TomoSAR, present the most relevant experimental results of the last decade, and discuss the potentials of BIOMASS tomography.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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.
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.
Low-frequency tomographic synthetic aperture radar (TomoSAR) techniques provide an opportunity for quantifying the dynamics of dense tropical forest vertical structures. Here, we compare the ...performance of different TomoSAR processing, Back-projection (BP), Capon beamforming (CB), and MUltiple SIgnal Classification (MUSIC), and compensation techniques for estimating forest height (FH) and forest vertical profile from the backscattered echoes. The study also examines how polarimetric measurements in linear, compact, hybrid, and dual circular modes influence parameter estimation. The tomographic analysis was carried out using P-band data acquired over the Paracou study site in French Guiana, and the quantitative evaluation was performed using LiDAR-based canopy height measurements taken during the 2009 TropiSAR campaign. Our results show that the relative root mean squared error (RMSE) of height was less than 10%, with negligible systematic errors across the range, with Capon and MUSIC performing better for height estimates. Radiometric compensation, such as slope correction, does not improve tree height estimation. Further, we compare and analyze the impact of the compensation approach on forest vertical profiles and tomographic metrics and the integrated backscattered power. It is observed that radiometric compensation increases the backscatter values of the vertical profile with a slight shift in local maxima of the canopy layer for both the Capon and the MUSIC estimators. Our results suggest that applying the proper processing and compensation techniques on P-band TomoSAR observations from space will allow the monitoring of forest vertical structure and biomass dynamics.
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This paper presents an algorithm for simulating tomographic synthetic aperture radar (SAR) data based on another stack actually gathered by a real acquisition system. Through the procedure here ...proposed, the simulated system can be evaluated according to its capability to image complex natural media rather than reference point targets. This feature is particularly important whenever the biophysical properties of the target of interest must be preserved and cannot be easily modeled. The system to be simulated may be different from the original one concerning resolution, off-nadir angles, bandwidth and central frequency. The algorithm here proposed handles these differences by properly taking into account the wavenumbers of the target illuminated by the real survey and requested by the simulated one. The complex images constituting the synthetic stack are associated with the effective vertical interferometric wavenumber peculiar of the geometry to be simulated, regardless of the original data. Furthermore, the three-dimensional resolution cell of the simulated tomographic system is consistent with the simulated geometry concerning size and spatial orientation. These two latter features cannot be guaranteed by simply filtering the original stack. The simulator here proposed has been used to simulate the tomographic stack expected from the forthcoming European Space Agency (ESA) BIOMASS mission. The relationship between baseline distribution and 3D focusing capability was explored; special attention has been paid to the robustness of tomographic power at being a good proxy for the above ground biomass in tropical regions.
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