Temporal Decorrelation Research Articles

Temporal Decorrelation of C-Band Backscatter Coefficient in Mediterranean Burned Areas

Burned area algorithms from radar images are often based on temporal differences between pre- and post-fire backscatter values. However, such differences may occur long past the fire event, an effect known as temporal decorrelation. Improvements in radar-based burned areas monitoring depend on a better understanding of the temporal decorrelation effects as well as its sources. This paper analyses the temporal decorrelation of the Sentinel-1 C-band backscatter coefficient over burned areas in Mediterranean ecosystems. Several environmental variables influenced the radar scattering such as fire severity, post-fire vegetation recovery, water content, soil moisture, and local slope and aspect were analyzed. The ensemble learning method random forests was employed to estimate the importance of these variables to the decorrelation process by land cover classes. Temporal decorrelation was observed for over 32% of the burned pixels located within the study area. Fire severity, vegetation water content, and soil moisture were the main drivers behind temporal decorrelation processes and are of the utmost importance for areas detected as burned immediately after fire events. When burned areas were detected long after fire (decorrelated areas), due to reduced backscatter coefficient variations between pre- to post-fire acquisitions, water content (soil and vegetation) was the main driver behind the backscatter coefficient changes. Therefore, for efficient synthetic aperture radar (SAR)-based monitoring of burned areas, detection, and mapping algorithms need to account for the interaction between fire impact and soil and vegetation water content.

Differential SAR Tomography Reconstruction Robust to Temporal Decorrelation Effects

Temporal decorrelation is one of the major problems in synthetic aperture radar (SAR) tomography (TomoSAR) of a natural environment that leads to blurring and spreading in focused image space. In the context of spatiotemporal focusing using the multi-temporal multi-baseline (MB) SAR data, a model-based differential TomoSAR is employed. Along this and with the aim of temporal decorrelation-robust focusing, a differential tomography framework based on generalized Capon estimator is investigated. The method can cope with temporal decorrelation of the distributed environment by spatiotemporal focusing with optimal bandwidth of the distributed signal. In addition, the method employs an additional parameter for coherence channel balancing in the model of generalized Capon that benefits from it in characterizing the spatiotemporal backscattering by mitigating the inconsistency between channels. The analysis is performed with a realistic simulation of temporal decorrelation in the presence of different decorrelation sources and taking into account the dependence on the vertical structure of the forested area. Effectiveness of the proposed framework has been assessed on both simulated and real data sets by evaluation and characterization of the canopy and under foliage ground in terms of deviation between the estimated covariance matrix and one of the generalized TomoSAR models.

Fast spatio-temporal decorrelation using FIR filter network with decoupled adaptive step sizes

Blind separation of convolutive mixtures has many applications in the areas of acoustics, communications, biomedical signal processing. Spatio-temporal decorrelation is a useful preprocessing technique that can reduce the blind separation problem into a simpler orthogonal matrix estimation problem. However, it is computationally expensive for its large unknown parameter set. Realtime spatio-temporal decorrelation method remains an open issue for years. In this paper, we focus on accelerating the adaptation process in the FIR filter based decorrelation method. Firstly, the update equation is decoupled into spatial decorrelation and temporal decorrelation. Then, their respective convergence conditions are systematically analyzed using eigenvalue decomposing method. Based on it, a fast algorithm for FIR filter network with spatio-temporal decoupled adaptive step-sizes is proposed. Comprehensive simulations are performed on both synthetic data and real world captured sEMG data. We have compared the proposed algorithm with the fixed step size method, IIR filter with natural gradient, and the annealed step size method. The factors including number of iteration, number of channel, computational time, selection of filter order and window size are elaborately compared and discussed. The results verified the reliable performance of our method on accelerating the adaptation process for spatio-temporal decorrelation simultaneously compared to classical methods.

Comparison of Tomographic SAR Reflectivity Reconstruction Algorithms for Forest Applications at L-band

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.

Temporal speckle-averaging of optical coherence tomography volumes for in-vivo cellular resolution neuronal and vascular retinal imaging

.It has been recently demonstrated that structures corresponding to the cell bodies of highly transparent cells in the retinal ganglion cell layer could be visualized noninvasively in the living human eye by optical coherence tomography (OCT) via temporal averaging. Inspired by this development, we explored the application of volumetric temporal averaging in mice, which are important models for studying human retinal diseases and therapeutic interventions. A general framework of temporal speckle-averaging (TSA) of OCT and optical coherence tomography angiography (OCTA) is presented and applied to mouse retinal volumetric data. Based on the image analysis, the eyes of mice under anesthesia exhibit only minor motions, corresponding to lateral displacements of a few micrometers and rotations of a fraction of 1 deg. Moreover, due to reduced eye movements under anesthesia, there is a negligible amount of motion artifacts within the volumes that need to be corrected to achieve volume coregistration. In addition, the relatively good optical quality of the mouse ocular media allows for cellular-resolution imaging without adaptive optics (AO), greatly simplifying the experimental system, making the proposed framework feasible for large studies. The TSA OCT and TSA OCTA results provide rich information about new structures previously not visualized in living mice with non-AO-OCT. The mechanism of TSA relies on improving signal-to-noise ratio as well as efficient suppression of speckle contrast due to temporal decorrelation of the speckle patterns, enabling full utilization of the high volumetric resolution offered by OCT and OCTA.

Comparision of Methods for Polarimetric SAR Tomography with Small Number of Baselines in Forested Areas

Synthetic aperture radar Tomography (TomoSAR) provides scene reflectivity estimation of vegetation along elevation coordinates. However, the more multi-baselines acquisition, the longer the time span of acquisition, which will result in serious temporal decorrelation in forested area. In this way, we expect to use as smaller number of baselines as possible to obtain high estimation accuracy in elevation direction. We thus investigate the performance of Polarimetric SAR tomography (Pol-TomoSAR) with small number of baselines in forested areas. The results show that compressive sensingbased Pol-TomoSAR has higher estimation accuracy in elevation direction than conventional Pol-TomoSAR with small number of baselines.

Detecting Land Subsidence Due to Groundwater Withdrawal in Aliabad Plain, Iran, Using ESA Sentinel-1 Satellite Data

In the present study, ground subsidence in the Aliabad plain (central Iran) was investigated using differential synthetic aperture radar interferometry. The data used for this purpose were Sentinel 1 images acquired during the time range from 24/03/2015 to 8/09/2016. Four interferogram pairs with high coherence were selected to minimize temporal decorrelation. The final analysis was performed in an area where there is sufficient hydrological and geological information. The results revealed that subsidence is a continuous phenomenon in the study area. The vertical displacement rate during the investigated period was estimated to be 178 mm/year. It was also noticed that the subsidence rate in the western part of the plain was higher than in other parts. Moreover, the effects of groundwater level decline, alluvium thickness, and transmissivity on the subsidence level were investigated. Overall, this research provides a correlation between the amount and distribution of land subsidence and effective factors for accurate detection of this phenomenon.

Space scanning FMCW‐based two‐dimensional frequency diverse array radar

The frequency-modulated continuous wave (FMCW)-based frequency diverse array (FDA) radar concept is extended to two dimensions (2D). The radar operates as a linear pulsed FMCW/FDA in the transmission (TX) mode while it operates as a pulsed FMCW/phased array (PA) in the receiving mode. It is shown that the FDA has the capability of scanning a 2D angular sector in a single pulse TX. It is shown that local instantaneous frequency bandwidth is much smaller than the radiofrequency (RF) frequency deviation of linear frequency modulation. Positive and negative slope TX/RF locations offer frequency diversity. The low signal-to-noise ratio of FDA is well compensated due to target temporal decorrelation diversity in the observation time and by the cumulative detection scheme used. Time domain and frequency domain signal processings are described. A Ku-band direct digital synthesis-based FDA radar design is compared by a corresponding equivalent PA radar.

Bistatic-Like Differential SAR Tomography

Motivated by prospective synthetic aperture radar (SAR) satellite missions, this paper addresses the problem of differential SAR tomography (D-TomoSAR) in urban areas using spaceborne bistatic or pursuit monostatic acquisitions. A bistatic or pursuit monostatic interferogram is not subject to significant temporal decorrelation or atmospheric phase screen and, therefore, ideal for elevation reconstruction. We propose a framework that incorporates this reconstructed elevation as deterministic prior to deformation estimation, which uses conventional repeat-pass interferograms generated from bistatic or pursuit monostatic pairs. By means of theoretical and empirical analyses, we show that this framework is, in the pursuit monostatic case, both statistically and computationally more efficient than the standard D-TomoSAR. In the bistatic case, its theoretical bound is no worse by a factor of 2. We also show that reasonable results can be obtained by using merely six TerraSAR-X add-on for digital elevation measurements (TanDEM-X) pursuit monostatic pairs, if additional spatial prior is introduced. The proposed framework can be easily extended for multistatic configurations or external sources of scatterer’s elevation.

Determining hydrogeological parameters of an aquifer in Sirjan Basin using Envisat ASAR interferometry and groundwater modelling

ABSTRACT Excessive groundwater exploitation in Sirjan plain, located in south of Iran, has caused severe land subsidence. The main purpose of this paper is to determine the hydrogeological parameters of the aquifer system in Sirjan plain. To this end, the groundwater flow was simulated in both steady and transient states using the United States Geological Survey Modular Three-Dimensional Finite-Difference Groundwater Flow Model, MODFLOW. The hydraulic conductivity parameter of the aquifer system was first estimated and calibrated in the steady state by simulating the hydraulic head at 63 piezometric wells. The specific yield and recharge parameters were then calibrated in the transient state by simulating the drawdown within a period of interest, i.e. 23 September 2004 to 22 September 2005. The main innovation of this paper, however, is to use the potential of Synthetic Aperture Radar (SAR) interferometry time-series analysis in the last step of the proposed algorithm. Small Baseline Subset (SBAS) time-series analysis was applied using Envisat Advanced SAR (ASAR) images acquired from 1 June 2004 to 28 September 2010. The merit of SBAS time series is that it enables us to calculate the amount of subsidence in each period of interest while minimizing the temporal decorrelation effect. In the last step, the SBAS time-series analysis results were obtained to extract the accumulated subsidence from 19 October 2004 to 30 August 2005. The aquifer compaction due to this period was calculated in the Interbed Storage Package (IBS1) for MODFLOW in order to calibrate storage coefficient in a trial-and-error manner so as the calculated subsidence and the observed one by SAR interferometry be in a good agreement. The Root Mean Square Error (RMSE) between the simulated subsidence and the observed one is calculated as 0.019 m which is an indication of the high performance of modelling.

RELATIONSHIP BETWEEN SAR/SENTINEL-1 POLARIMETRIC AND INTERFEROMETRIC DATA WITH BIOPHYSICAL PARAMETERS OF AGRICULTURAL CROPS

Abstract. The use of SAR (Synthetic Aperture Radar) data in agricultural applications has not yet been adequately explored, due to the complexity of the processing required, the lower diversity and availability of SAR data, and the difficulty in interpreting this data. The interactions between microwave energy and vegetation are influenced by factors related to plant structure, dielectric properties of the canopy, planting density and line orientation, and the angle of incidence and polarization of the wave. These differences between the recorded phases are used in data analysis techniques such as polarimetry and interferometry. Thus, the objective of this research is to analyse the relationships between the biophysical attributes of two agricultural crops (soybean and wheat) and the polarimetric and interferometric parameters of the SAR/Sentinel-1 data. The backscatter coefficients sigma and gamma in the VV polarization have inversely direct relation with the height of the crops, that is, as cultures grow, the interaction of energy in this polarization increases and the return signal decreases. For the cross polarization VH, the behaviour is the opposite, the larger the canopy height, the greater the interaction of vertical polarization and the greater the return on horizontal polarization. The interferometric coherence had small values, characterising a temporal decorrelation between the image pairs, due the canopy development. This preliminary study serves as a basis for future research with SAR/Sentinel-1 data focused on crops.

Repeat-pass SAR interferometry for land cover classification: A methodology using Sentinel-1 Short-Time-Series

In this paper we explore the potential of repeat-pass interferometric SAR (InSAR) for land cover classification purposes. We introduce a novel approach for the generation of large-scale thematic maps, based on the use of multi-temporal data, acquired over short observation intervals (short-time-series). A larger interferometric coherence loss is expected with the increasing time difference between two interferometric acquisitions. This phenomenon is normally indicated as temporal decorrelation whose amount differs depending on the type of imaged target on ground. The basic idea is therefore to accurately model the evolution in time of the temporal decorrelation and use the estimated parameters, together with backscatter, as input features for the Random Forest machine learning classification algorithm. The work has been carried out on the case study of land cover mapping over central Europe, considering Sentinel-1 C-band interferometric stacks, acquired over a time span of about one month. Three different land cover classes have been considered: artificial surfaces as e.g. urban areas, forests, and non-forested areas as the ensemble of low vegetation, bare soil, and agricultural areas. The results show a level of agreement above 91%, when compared to the CORINE land cover map product of 2012, which has been used as external reference for both training and testing of the classification algorithm.

On the Interpretation of Parker Solar Probe Turbulent Signals

Abstract In this Letter we propose a practical methodology to interpret future Parker Solar Probe (PSP) turbulent time signals even when Taylor’s hypothesis is not valid. By extending Kraichnan’s sweeping model used in hydrodynamics we derive the Eulerian spacetime correlation function in magnetohydrodynamic (MHD) turbulence. It is shown that in MHD, the temporal decorrelation of small-scale fluctuations arises from a combination of hydrodynamic sweeping induced by large-scale fluid velocity and by the Alfvénic propagation along the local magnetic field. The resulting temporal part of the spacetime correlation function is used to determine the field-perpendicular wavenumber range of the turbulent fluctuations that contribute to the power of a given frequency ω of the time signal measured in the spacecraft frame. Our analysis also shows that the shape of frequency power spectrum P sc(ω) of the time signal will follow the same power law of the reduced power spectrum in the plasma frame, where α is the spectral index. The proposed framework for the analysis of PSP time signals entirely relies on two simple dimensionless parameters that can be empirically obtained from PSP measurements, namely, (where V ⊥ is the perpendicular velocity of PSP seen in the plasma frame) and the spectral index α.

Early soil consolidation from magnetic extensometers and full resolution SAR interferometry over highly decorrelated reclaimed lands

Reclaimed lands account for a large portion of the developable territories in Hong Kong. Towards better construction planning for the follow-up civil works, stability monitoring is usually required at these artificial sites. The Synthetic Aperture Radar Interferometry (InSAR) technique can provide bi-weekly updates of high resolution (up to 1 m) and high precision (millimeter level) ground motion maps at low costs, which overcomes the limitations of ground-based instruments. However, rapid settlement during the early stage of soil consolidation can result in significant temporal decorrelation to phase signals and impact InSAR detection, especially over newly reclaimed areas. Here, we give a first demonstration on how the introduction of in-situ extensometer measurements can help improve InSAR capabilities for signal recovery of the early consolidation process. We integrate persistent scatterers (PS) and distributed scatterers (DS) in our processing chain to establish a two-tier monitoring network. Magnetic extensometers are used to estimate local consolidation models, which are then utilized to replace the linear part in the conventional functional phase model. For nonlinear deformation, both hyperbolic and exponential models were considered. The proposed method was applied to 61 TerraSAR-X images covering the Penny's Bay Reclamation Stage 2 (PBR2) in Hong Kong. The consolidation history of the new reclamation site has been successfully extracted, with cumulative subsidence exceeding 1.6 m between May 2008 and Dec. 2011. Approximately 84% of the settlement of the non-dredged region was found to be from compaction of underlying soft marine deposits, not the filling materials. In addition to highlighting the spatiotemporal characteristics of the deformation, InSAR also helps reveal the compaction evolution of the underlying deposit. The results benefit our understanding of the early consolidation process in PBR2 and inform extra reinforcement plans if necessary.

Estimating tree height from TanDEM-X data at the northwestern Canadian treeline

The circum-Arctic transitional zone between forest and tundra, i.e. the treeline zone, is shifting northward due to current Arctic warming and, therefore, requires systematic monitoring. Up to now, radar remote sensing was hardly possible in the treeline zone due to spatial resolution and/or temporal decorrelation constraints of preceding satellite missions. The unique constellation of the TanDEM-X satellites with its bistatic mode and very high spatial resolution opens up opportunities for monitoring small (≥0.01 km2) and isolated patches of very sparse forest which are typical for the transitional zone. We focused on an area at the northern edge of the treeline zone in the Northwest Territories, Canada, and evaluated the potential of TanDEM-X bistatic data to characterize the tree height in the forest patches in this region. TanDEM-X data were acquired during the TanDEM-X Science Phase in 2015, when the perpendicular baseline was large (corresponding to the height of ambiguity of approximately 14.6 m) and kept constant. We employed TanDEM-X backscatter, bistatic coherence, and interferometric height from the stack of seven multitemporal bistatic pairs and compared them to maximum vegetation height obtained from full-waveform airborne LiDAR data. We found strong linear relationships between all TanDEM-X metrics and LiDAR vegetation height within the forest patches with r = 0.67, r = −0.69, and r = 0.78 for the backscatter, coherence, and interferometric height, respectively. Furthermore, we extracted the position of individual trees from the LiDAR data and estimated tree density as the number of trees per unit area. The linear relationships between all TanDEM-X metrics and the tree density were very weak. The relationships between all TanDEM-X metrics and tree height differentiated for three tree density classes (low, medium, and high) remained strong. Random forests regression using all three TanDEM-X metrics predicted the tree height with a mean absolute error of 0.7 m (mean forest height in the study area was 2.5 m). CoSSC pairs were generally consistent with each other and the multitemporal averaging slightly improved the performance compared to single pairs. Taking into account the global coverage of bistatic TanDEM-X data acquired for the global digital elevation model, our results show a potential for quantifying the tree height in small forest patches along the circum-Arctic treeline zone.

A New Single-Pass SAR Interferometry Technique with a Single-Antenna for Terrain Height Measurements

One of the prospective research topics in radar remote sensing technology is the methodology for designing an optimal radar system for high-precision two-dimensional and three-dimensional image acquisition of the Earth’s surface with minimal hardware requirements. In this study, we propose a single-pass interferometric synthetic aperture radar (SAR) imaging technique with only a single antenna for the estimation of the terrain height. This technique enabled us to obtain terrain height information in one flight of the carrier, on which only one receiving antenna was mounted. This single-antenna single-pass interferometry required a squint angle look geometry and additional image synthesis processing. The limiting accuracy of the terrain height measurement was approximately 1.5 times lower than that of the conventional two-pass mode and required a longer baseline than two-pass interferometry to have an equivalent accuracy performance. This imaging method could overcome the temporal decorrelation problem of two-pass interferometry due to a short time gap in the radar echo acquisitions during two sub-aperture intervals. We compared the accuracy performance of the terrain height measurements of our method with the conventional two-pass interferometry. This comparison was carried out at various spectral bandwidths, degrees of surface roughness, and baseline lengths. We validated our idea with numerical simulations of a digital elevation map, and showed real extracted data of the terrain heights in the Astrakhan and Volga regions of the Russian Federation, obtained from airborne SAR with our single-antenna single-pass interferometry technique.

Integration of Corner Reflectors for the Monitoring of Mountain Glacier Areas with Sentinel-1 Time Series

Glacier flow and slope instabilities in Alpine mountain areas represent a hazard issue. Sentinel-1 satellites provide regular Synthetic Aperture Radar (SAR) acquisitions that are potentially useful to monitor these areas, but they can be affected by temporal decorrelation due to rapid changes in the surface. The application of interferometric synthetic aperture radar (InSAR) therefore seems difficult due to loss of coherence. On the other hand, Corner Reflectors (CR) can be used as coherent targets in SAR images for accurate displacement measurement thanks to their strong backscattering property and temporal stability. The use of CRs in multi-temporal InSAR analysis in Alpine mountain areas can thus be beneficial. In this study, we present a comparison between triangular and rectangular CRs, based on Radar Cross Section (RCS) measurements in an anechoic chamber and on long-term experiments over the Argentière glacier and the surrounding slopes and moraine. The visibility in both summer and winter of 10 CRs installed on the test site was investigated. As this area is exposed to heavy precipitation including snow falls, two perforated CRs were tested. The amplitude stability and the phase error of each CR were estimated. A precise tracking of two CRs installed at the glacier surface was also able to measure the displacement of the Argentière glacier, giving results close to previous GPS measurements. Furthermore, a Persistent Scatterer Interferometry (PSI) study was conducted, using the most stable CR as reference point to estimate slope instabilities, which led to the identification of an area corresponding to a tectonic fault called “Faille de l’angle”. The precise absolute locations of the CRs were successfully estimated and PS heights were compared with a LiDAR-based (Light Detection And Ranging) digital elevation model (DEM) and GPS measurements.

Polarization Analysis of the Impact of Temporal Decorrelation in Synthetic Aperture Radar (SAR) Tomography

After almost two decades of long investigations into 3D imaging of natural environments, synthetic aperture radar (SAR) tomography (TomoSAR) is now at an operational level. Yet, a major problem that limits the potential of TomoSAR is related to the temporal decorrelation of natural scatterers during multitemporal multibaseline data acquisition. In this paper, a comparative investigation into the effect of temporal decorrelation between employed polarizations is presented. A particular focus is put on practical and statistical analysis of the dispersion of polarimetric vertical reflectivity in the presence of temporal decorrelation. The analysis is based on the synthesis of all feasible polarimetric responses of a given scatterer from its measurements of a linear orthonormal basis. Such an analysis offers a comprehension of the expected level of temporal decorrelation in TomoSAR focusing with respect to employed polarization. The analysis was performed by simulating temporal decorrelation with different terms, depending on the vertical structure and polarization, which are important aspects in a forest scenario. Moreover, the experiment was extended to a P-band dataset relative to the forest site of Remningstorp, Sweden, which was acquired through the German Aerospace Center’s experimental SAR (E-SAR) airborne system in the framework of the European Space Agency (ESA) campaign BioSAR.

Coherence-based SAR tomography for spaceborne applications

Future SAR missions will provide three-dimensional images of semi-transparent media, such as vegetation and ice, through SAR tomography. Access to information on the internal structure of these volume scatterers is a key factor for a better understanding of ecosystem dynamics and climate change. Because of this, several concepts are nowadays examined to implement SAR tomography in a spaceborne framework.In order to do that, it is necessary to gather different observations of the area of interest. Unfortunately, a consequence of the time that elapses between acquisitions is that the electromagnetic properties of the medium may vary. This implies that, there may be inconsistencies in the acquired data, leading to errors in the final inversion. A solution to partially cope with this temporal decorrelation, is to acquire data employing two or more sensors operating with a reduced (or even absent) temporal gap and then to collect several acquisitions at different time instants. By means of this imaging concept, the required line-of-sight diversity is granted and the desired resolution in the height direction ensured. In this way, sets of temporal decorrelation-free interferometric coherences can be built and the vertical scattering profile can be retrieved via coherence-based tomography.This contribution analyzes a two-sensor system like TanDEM-X (Krieger et al., 2007), Tandem-L (Moreira et al., 2015), or SAOCOM-CS (Davidson et al., 2014). In particular, the potential of coherence-based tomography are shown with data acquired with the TanDEM-X sensors for boreal and Amazon forest. In addition, a technique to partially cope with temporal decorrelation through covariance matrix filtering is also presented in the paper.

Generalized-Capon Method for Diff-Tomo SAR Analyses of Decorrelating Scatterers

In synthetic aperture radar (SAR) remote sensing, Differential Tomography (Diff-Tomo) is developing as a powerful crossing of the mature Differential SAR Interferometry and the emerged 3D SAR Tomography. Diff-Tomo produces advanced 4D (3D+Time) SAR imaging capabilities, extensively applied to urban deformation monitoring. More recently, it has been shown that, through Diff-Tomo, identifying temporal spectra of multiple height-distributed decorrelating scatterers, the important decorrelation-robust forest Tomography functionality is possible. To loosen application constraints of the related main experimented full model-based processing, and develop other functionalities, this work presents an adaptive, just semi-parametric, generalized-Capon Diff-Tomo method, first conceived at University of Pisa in 2013, for joint extraction of height and dynamical information of natural distributed (volumetric) scatterers, with its formalization and a series of insights. Particular reference is given to the important functionality of the separation of different decorrelation mechanisms in forest layers. Representative simulated and P-band forest data sample results are also shown. The new Diff-Tomo method is getting a flexible and rich decorrelation-robust Tomography functionality, and is able to profile height-varying temporal decorrelation, for significantly distributed scatterers.