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P-band synthetic aperture radar (SAR) is sensitive to above-ground biomass (AGB) but retrieval accuracy has been shown to deteriorate in topographic areas. In boreal forest, the signal penetrates through the canopy to interact with the ground producing variations in backscatter depending on ground topography, forest structure, and soil moisture. Tomographic processing of multiple SAR images Tomographic SAR (TomoSAR) provides information about the vertical backscatter distribution. This article evaluates the use of P-band TomoSAR data to improve AGB retrievals from backscattered intensity by suppressing the backscattered signal from the ground. This approach can be used even when the tomographic resolution is insufficient to resolve the vertical backscatter profile. The analysis is based on P-band data from two campaigns: BioSAR-1 (2007) in Remingstorp, southern Sweden, and BioSAR-2 (2008) in Krycklan (KR), northern Sweden. BioSAR airborne data were also processed to correspond as closely as possible to future BIOMASS TomoSAR acquisitions, with BioSAR-2-based results shown. A power law AGB model using volumetric HV polarized backscatter performs best in KR, with training residual root mean-squared error (RMSE) of 30%–36% (27–33 t/ha) for airborne data and 38%–39% for simulated BIOMASS data. Airborne TomoSAR data suggest that both vertical and horizontal tomographic resolution are of importance and that it is possible to greatly reduce AGB retrieval bias when compared with airborne P-band SAR backscatter intensity-based retrievals. A lack of significant ground slopes in Remningstorp reduces the benefit of using TomoSAR data which performs similar to retrievals based solely on P-band SAR backscatter intensity. [ABSTRACT FROM AUTHOR]

Methods to estimate forest biomass change have been investigated using experimental P-band synthetic aperture radar (SAR) data from the recent airborne campaigns BioSAR 2007 and BioSAR 2010 conducted over a hemiboreal test site in southern Sweden. Regression models based on backscatter change were developed using reference biomass change maps derived from high-density laser scanning data. Different regression models were developed for linear, square root, and logarithmic biomass change scales. The models were compared to the change maps based on laser data using twofold cross-validation, and estimation errors were evaluated using six 80 m by 80 m plots with detailed in situ measurements. The results indicate that the root-mean-square error of biomass change estimates based on P-band SAR backscatter data is about 15% or 20 t/ha. This suggests that not only clear-cuts but also growth and thinning can be measured. Simulations were performed in order to evaluate the possibility of using a spaceborne P-band SAR for measurements of forest biomass change. The simulations show that, with 64 equivalent number of looks (ENL) and a 50% change in biomass, it is possible to correctly indicate whether the forest has gained or lost biomass. Similarly, for a biomass loss of more than 75%, a correct indication of the sign of biomass change can be achieved with only 8 ENL. [ABSTRACT FROM PUBLISHER]

Low-frequency synthetic aperture radar (SAR) is a promising technique for stem volume retrieval, particularly for dense forests, due to the good penetration of forest canopies. However, it is well known that the dominant scattering mechanism, the trunk-ground dihedral interaction, decreases rapidly on sloping terrain. In this paper, we use low VHF-band SAR data, collected with CARABAS over dense coniferous forests in Sweden, to examine the effect of topography. Using flight passes with different headings, the effect of slope and aspect angle on backscatter is characterized. For tall trees (∼ 30 m), on the steepest slopes in the test-site (up to ∼ 12°), differences of up to 8 dB are observed between images acquired with different look directions relative to the slope. A physical model is developed to investigate the different scattering mechanisms and their sensitivity to terrain slopes. The model shows that the trunk-ground scattering still dominates the response for large trees on moderate slopes, and a semiempirical model for the effect of topography on backscatter is proposed. The model shows good agreement with measurements, indicating the possibility of using it to compensate for the effects of sloping terrain when retrieving stem volume in coniferous forest. [ABSTRACT FROM AUTHOR]

Exact synthetic aperture radar (SAR) inversion for a linear aperture may be obtained using fast transform techniques. Alternatively, back-projection integration in time domain can also be used. This technique has the benefit of handling a general aperture geometry. In the past, however, back-projection has seldom been used due to heavy computational burden. We show that the back-projection integral can be recursively partitioned and an effective algorithm constructed based on aperture factorization. By representing images in local polar coordinates it is shown that the number of operations is drastically reduced and can be made to approach that of fast transform algorithms. The algorithm is applied to data from the airborne ultra-wideband CARABAS SAR and shown to give a reduction in processing time of two to three orders of magnitude. [ABSTRACT FROM AUTHOR]

Presents a study which discussed methods for the retrieval of stem volume, dominant tree height and dominant tree diameter values using CARABAS images. Measurements of CARABAS images from a test site in Finland; Development of the texture analysis methods; Discussion on the stem volume estimation accuracy.

Presents a physical model describing the backscatter from coniferous boreal forests in the lower very high frequency-band in terms of stem volume. Experimental data; Results and discussion; Conclusion.

Provides information on a study which developed a coherent scattering model to determine the forest radar backscattering at very-high-frequency radio frequencies. Modeling of scattering from dielectric cylinders; Modeling of forest stands.

Ground-based tomographic radar measurements provide valuable knowledge about the electromagnetic scattering mechanisms and temporal variations of an observed scene and are essential in preparation for space-borne tomographic synthetic aperture radar (SAR) missions. Due to the short range between the radar antennas and a scene being observed, the tomographic radar observations are affected by several systematic errors. This article deals with the modelling and calibration of three systematic errors: mutual antenna coupling, magnitude and phase errors and the pixel-variant impulse response of the tomographic image. These errors must be compensated for so that the tomographic images represent an undistorted rendering of the scene reflectivity. New calibration methods were described, modelled and validated using experimental data. The proposed methods will be useful for future ground-based tomographic radar experiments in preparation for space-borne SAR missions. [ABSTRACT FROM AUTHOR]

In this study, spatial separation of the radar transmitter and receiver units is considered, as a means of reducing the masking effect in noise radars. A bistatic radar system is constructed, with emphasis on a lightweight transmitter unit that can be mounted on a commercial Unmanned Aerial Vehicle (UAV). The system uses pseudo‐random noise, generated digitally at the receiver and transmitter units. Correlation losses, due to non‐linearities in the transmitter and receiver units, are measured to 0.1 dB. This study shows that by separating the transmitter and receiver unit the masking effect is significantly reduced, compared to a monostatic setup. This reduction is enough for the system to detect a slow flying UAV. Thus, bistatic separation should be considered as a practical tool to reduce the masking effect. By processing clutter with an extended CLEAN algorithm, the correlation noise floor is further suppressed. [ABSTRACT FROM AUTHOR]

This article describes how to form a SAR image without proper motion quantities. That is within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a fast-factorized back-projection formulation with adjustable geometry parameters. Subapertures are tuned and merged pair-by-pair (base-2) and step-by-step. With this technique, we can correct an erroneous geometry and form a focused image. The FGA algorithm has been applied on two datasets, acquired by the UWB CARABAS 3 system at UHF-band. The tracks are measured accurately by means of a DGPS. We however adopt and modify a geometry model. Equidistant linear tracks at fixed altitudes are assumed. These tracks are then regulated via a two-stage search strategy and a reverseprocessing procedure. As this is a first experiment at UHF-band, we provide GPS-based length values for the subapertures, to simplify the search. Multiple geometry solutions are tested for each subaperture pair, i.e., at each resolution level. Resulting FGA images are compared to reference images and verified to be focused. This indicates that it is feasible to form a focused image with wavelength resolution at UHF-band, i.e., with minimum support from a motion measurement system. [ABSTRACT FROM AUTHOR]

A model for aboveground biomass estimation from single-pass interferometric synthetic aperture radar (InSAR) data is presented. Forest height and canopy density estimates $\Delta h$ and \eta_0$, respectively, obtained from two-level model (TLM) inversion, are used as biomass predictors. Eighteen bistatic VV-polarized TanDEM-X (TDM) acquisitions are used, made over two Swedish test sites in the summers of 2011, 2012, and 2013 (nominal incidence angle: 41 ^{\circ} ; height-of-ambiguity: 32–63 m) . Remningstorp features a hemiboreal forest in southern Sweden, with flat topography and where 32 circular plots have been sampled between 2010 and 2011 (area: 0.5 ha; biomass: 42–242 t/ha; height: 14–32 m) . Krycklan features a boreal forest in northern Sweden, 720-km north–northeast from Remningstorp, with significant topography and where 31 stands have been sampled in 2008 (area: 2.4–26.3 ha; biomass: 23–183 t/ha; height: 7–21 m) . A high-resolution digital terrain model has been used as ground reference during InSAR processing. For the aforementioned plots and stands and if the same acquisition is used for model training and validation, the new model explains 65%–89% of the observed variance, with root-mean-square error (RMSE) of 12%–19% (median: 15%) . By fixing two of the three model parameters, accurate biomass estimation can also be done when different acquisitions or different test sites are used for model training and validation, with RMSE of 12%–56% (median: 17%) . Compared with a simple scaling model computing biomass from the phase center elevation above ground, the proposed model shows significantly better performance in Remningstorp, as it accounts for the large canopy density variations caused by active management. In Krycklan, the two models show similar performance. [ABSTRACT FROM PUBLISHER]

Wind vector fields derived from synthetic aperture radar (SAR) sensors show variations at smaller scales than most other globally available surface wind sources. However, few studies have been devoted to the investigation of the accuracy of SAR-derived wind fields at different scales and how they compare with other wind data. In order to investigate these issues, an algorithm for the retrieval of SAR-derived wind vectors has been developed, and a quality assessment between the retrievals and in situ, scatterometer, and numerical weather model (NWM) wind data has been performed. The implemented wind retrieval algorithm detects streak features in the SAR image to estimate wind directions and inverts wind speeds using CMOD-IFR2, CMOD5, or CMOD5.N geophysical model functions. In addition, a regularization method for filtering outliers in the wind direction retrievals is used. Retrievals compared with in situ data indicated better performance at offshore locations for wind speed inversions with CMOD5.N. The bias and standard deviation for offshore regularized wind directions and CMOD5.N speeds are 9° and 25° and -0.1 and 1.4 m/s, respectively. The comparison with the scatterometer and NWM wind data has been performed for retrievals at 5-, 10-, and 20-km resolution. The results indicate a better agreement of the coarser retrievals with the reference data. Nevertheless, mapping of smaller scale features requires wind directions from the SAR image itself. [ABSTRACT FROM AUTHOR]

The recent observed thinning of the glacier ice shelves in the Amundsen Sea (Antarctica) has been attributed to warm deep currents, possibly induced by along-coast winds in the vicinity of the glacial ice sheet. Here, high resolution maps of wind fields derived from Synthetic Aperture Radar (SAR) data have been studied and correlated with subsurface measurements of the deep water velocities in the Amundsen Sea area. Focus is on periods with low ice coverage in 2010 and 2011. In 2010, which had comparatively low ice coverage, the results indicate a more rapid response to wind forcing in the deep currents than in 2011. The SAR wind speed maps have better spatial resolution than available reanalysis data, and higher maximum correlation was obtained with SAR data than with reanalysis data despite the lower temporal resolution. The maximum correlation was R = 0.71, in a direction that is consistent with wind-driven Ekman theory. This is significantly larger than in previous studies. The larger correlation could be due to the better spatial resolution or the restriction to months with minimum ice coverage. The results indicate that SAR is a useful complement to infer the subsurface variability of the ocean circulation in remote areas in polar oceans. [ABSTRACT FROM AUTHOR]

One of the challenges in ocean surface current retrieval from synthetic aperture radar (SAR) data is the estimation and removal of the wave-induced Doppler centroid (DC). This article demonstrates empirically the relationship between the dc derived from spaceborne X-band InSAR data and the ocean surface wind and waves. In this study, we analyzed over 300 TanDEM-X image pairs. It is found that the general characteristics of the estimated dc follow the theoretically expected variation with incidence angle, wind speed, and wind direction. An empirical geophysical model function (GMF) is fit to the estimated dc and compared to existing models and previous experiments. Our GMF is in good agreement (within 0.2 m/s) with other models and data sets. It is found that the wind-induced Doppler velocity contributes to the total Doppler velocity with about 15% of the radial wind speed. This is much larger than the sum of the contributions from the Bragg waves (~0.2 m/s) and the wind-induced drift current (~3% of wind speed). This indicates a significant (dominant) contribution of the long wind waves to the SAR dc. Moreover, analysis of dual-polarized data shows that the backscatter polarization ratio ($PR=\sigma ^{0}_{VV}/\sigma ^{0}_{HH}$) and the dc polarization difference ($PD={|dc_{VV}|-|dc_{HH}|}$) are systematically larger than 1 and smaller than 0 Hz, respectively, and both increase in magnitude with incidence angle. The estimated PR and PD are compared to other theoretical and empirical models. The Bragg scattering theory-based (pure Bragg and composite surface) models overestimate both PR and PD, suggesting that other scattering mechanisms, e.g., wave breaking, are involved. In general, it is found that empirical models are more consistent with both backscatter and Doppler data than theory-based models. This motivates a further improvement of SAR dc GMFs. [ABSTRACT FROM AUTHOR]

A new biomass retrieval model for boreal forest using polarimetric P-band synthetic aperture radar (SAR) backscatter is presented. The model is based on two main SAR quantities: the HV backscatter and the HH/VV backscatter ratio. It also includes a topographic correction based on the ground slope. The model is developed from analysis of stand-wise data from two airborne P-band SAR campaigns: BioSAR 2007 (test site: Remningstorp, southern Sweden, biomass range: 10–287 tons/ha, slope range: 0–4^\circ) and BioSAR 2008 (test site: Krycklan, northern Sweden, biomass range: 8–257 tons/ha, slope range: 0–19^\circ). The new model is compared to five other models in a set of tests to evaluate its performance in different conditions. All models are first tested on data sets from Remningstorp with different moisture conditions, acquired during three periods in the spring of 2007. Thereafter, the models are tested in topographic terrain using SAR data acquired for different flight headings in Krycklan. The models are also evaluated across sites, i.e., training on one site followed by validation on the other site. Using the new model with parameters estimated on Krycklan data, biomass in Remningstorp is retrieved with RMSE of 40–59 tons/ha, or 22–33% of the mean biomass, which is lower compared to the other models. In the inverse scenario, the examined site is not well represented in the training data set, and the results are therefore not conclusive. [ABSTRACT FROM PUBLISHER]

A limiting factor that has been identified for stem-volume retrieval in coniferous forests using VHF synthetic aperture radar is that the backscatter varies depending on ground topography. On sloping ground, the backscatter from a forest is reduced, since the dominant ground—trunk double-bounce scattering mechanism is changed. This leads to underestimation of stem volume, and the variations caused by topography can obscure real variations in stem volume. By using multiple images acquired with different flight headings and combining the image information with ground-topography data in a model-based inversion method, we are able to compensate for the ground-topography influence on the backscatter. The inversion method is based on image segmentation and the optimal estimation method. Using four or more images from the CARABAS-II system and a coarse digital elevation model with 50-m horizontal grid, the stem volume can be retrieved with an average root-mean-square error (rmse) of less than 60 m³ha-1 for stem volumes in range of 80-700 m³ha-1 (in terms of above-ground biomass, this is equivalent to an rmse of less than 40 ton · ha-1 over the range of 50-400 ton · ha-1). The retrieval accuracy is similar to that previously obtained for similar forests standing on flat and horizontal ground. [ABSTRACT FROM AUTHOR]

In this paper, a model for prediction of radar backscatter from coniferous forests in the VHF and UHF band is proposed. The model includes the double-bounce scattering originating from vertical stems standing on an undulating ground surface and is based on a physical-optics approach. The model can be used to assess the importance of ground topography in synthetic aperture radar (SAR) imagery of forests, and it is applicable to SAR systems using horizontally transmit and receive polarization (HH). The model was validated against data from the airborne SAR systems CARABAS-II and LORA. Precision measurements of ground topography and forest characterization at a single tree level were used as model input to simulate SAR images. The simulated images were compared to radar data in the frequency bands 22-82 and 225- 470 MHz, and it was found that the model could predict much of the variation in backscatter observed in images (R² = 0.44 and 0.65 at best, for the lower and higher frequency band, respectively), which should be compared to R² ≈ 0.1 if the same model, but assuming a flat ground, was used. The results thus indicate that ground topography must be considered when predicting the variations in backscatter in the SAR images studied. The model did, however, fail to predict the absolute values of the backscattered intensity. The reason for the discrepancy is believed to be the value chosen for stem dielectric constant and unmodeled effects due to wave attenuation, tilting stems, and small-scale surface roughness. [ABSTRACT FROM AUTHOR]

Above-ground biomass change accumulated during four growth seasons in a hemi-boreal forest was predicted using airborne L- and P-band synthetic aperture radar (SAR) backscatter. The radar data were collected in the BioSAR 2007 and BioSAR 2010 campaigns over the Remningstorp test site in southern Sweden. Regression models for biomass change were developed from biomass maps created using airborne LiDAR data and field measurements. To facilitate training and prediction on image pairs acquired at different dates, a backscatter offset correction method for L-band data was developed and evaluated. The correction, based on the HV/VV backscatter ratio, facilitated predictions across image pairs almost identical to those obtained using data from the same image pair for both training and prediction. For P-band, previous positive results using an offset correction based on the HH/VV ratio were validated. The best L-band model achieved a root mean square error (RMSE) of 21 t/ha, and the best P-band model achieved an RMSE of 19 t/ha. Those accuracies are similar to that of the LiDAR-based biomass change of 18 t/ha. The limitation of using LiDAR-based data for training was considered. The findings demonstrate potential for improved biomass change predictions from L-band backscatter despite varying environmental conditions and calibration uncertainties. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The main challenging problems in ocean current retrieval from along-track interferometric (ATI)-synthetic aperture radar (SAR) are phase calibration and wave bias removal. In this paper, a method based on differential InSAR (DInSAR) technique for correcting the phase offset and its variation is proposed. The wave bias removal is assessed using two different Doppler models and two different wind sources. In addition to the wind provided by an atmospheric model, the wind speed used for wave correction in this work is extracted from the calibrated SAR backscatter. This demonstrates that current retrieval from ATI-SAR can be completed independently of atmospheric models. The retrieved currents, from four TanDEM-X (TDX) acquisitions over the Öresund channel in the Baltic Sea, are compared to a regional ocean circulation model. It is shown that by applying the proposed phase correction and wave bias removal, a good agreement in spatial variation and current direction is achieved. The residual bias, between the ocean model and the current retrievals, varies between 0.013 and 0.3 m/s depending on the Doppler model and wind source used for wave correction. This paper shows that using SAR as a source of wind speed reduces the bias and root-mean-squared-error (RMSE) of the retrieved currents by 20% and 15%, respectively. Finally, the sensitivity of the sea current retrieval to Doppler model and wind errors are discussed. [ABSTRACT FROM AUTHOR]

The structure of forests is important to observe for understanding coupling to global dynamics of ecosystems, biodiversity, and management aspects. In this paper, the sensitivity of X-band to boreal forest stem volume and to vertical and horizontal structure in the form of forest height and horizontal vegetation density is studied using TanDEM-X satellite observations from two study sites in Sweden: Remningstorp and Krycklan. The forest was analyzed with the Interferometric Water Cloud Model (IWCM), without the use of local data for model training, and compared with measurements by Airborne Lidar Scanning (ALS). On one hand, a large number of stands were studied, and in addition, plots with different types of changes between 2010 and 2014 were also studied. It is shown that the TanDEM-X phase height is, under certain conditions, equal to the product of the ALS quantities for height and density. Therefore, the sensitivity of phase height to relative changes in height and density is the same. For stands with a phase height >5 m we obtained an root-mean-square error, RMSE, of 8% and 10% for tree height in Remningstorp and Krycklan, respectively, and for vegetation density an RMSE of 13% for both. Furthermore, we obtained an RMSE of 17% for estimation of above ground biomass at stand level in Remningstorp and in Krycklan. The forest changes estimated with TanDEM-X/IWCM and ALS are small for all plots except clear cuts but show similar trends. Plots without forest management changes show a mean estimated height growth of 2.7% with TanDEM-X/IWCM versus 2.1% with ALS and a biomass growth of 4.3% versus 4.2% per year. The agreement between the estimates from TanDEM-X/IWCM and ALS is in general good, except for stands with low phase height. [ABSTRACT FROM AUTHOR]

This paper leads a discussion on how to form a Synthetic Aperture Radar (SAR) image without knowing the relative track. That is, within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a base-2 fast factorized back-projection (FFBP) formulation with six free geometry parameters (per subaperture pair). These are tuned step by step until a sharp image is obtained. This innovative autofocus concept can compensate completely for an erroneous geometry. The FGA algorithm has been applied successfully on two ultrawideband (UWB) data sets, acquired by the CARABAS II system at very high frequency (VHF)-band. The relative tracks are known (measured accurately). We, however, adopt and modify a basic geometry model. A linear equidistant track at fixed altitude is initially assumed. Apart from deviations due to linearization, a ~2.5-m/s along-track velocity error is also introduced. Resulting FGA images are compared to reference images and verified to be focused. This indicates that it is feasible to form a wavelength-resolution SAR image at VHF-band without support from a motion measurement system. The execution time for the examples in this paper is about five times longer with autofocus than without. Hence, the FGA algorithm is now fit for use on a regular basis. [ABSTRACT FROM AUTHOR]

Forest growth estimation is important in forest research and forest management, but complex to analyze in diverse forest stands. Twelve summertime TanDEM-X acquisitions from the boreal test site, Krycklan, in Sweden, with a known digital terrain model, DTM, have been used to study phase height and aboveground biomass change over 3.2 years based on the Interferometric Water Cloud Model, IWCM. The maximum phase height rate was determined to 0.29 m/yr, while the mean phase height rate was 0.16 m/yr. The corresponding maximum growth rate of the aboveground dry biomass, AGB, was 4.0 Mg/ha/yr with a mean rate of 1.9 Mg/ha/yr for 27 stands, varying from 23 to 183 Mg/ha. The highest relative AGB growth was found for young stands and high growth rates up to an age of 150 years. Growth rate differences relative a simplified model assuming AGB to be proportional to the phase height were studied, and the possibility to avoid a DTM was discussed. Effects of tree species, thinning, and clear cutting were evaluated. Verifications using in situ data from 2008 and a different in situ dataset combined with airborne laser scanning data from 2015 have been discussed. It was concluded that the use of multi-temporal TanDEM-X interferometric synthetic aperture radar observations with AGB estimates of each individual observation can be an important method to derive growth rates in boreal forests. [ABSTRACT FROM AUTHOR]

This paper report experiences from the processing and mosaicking of 518 TanDEM-X image pairs covering the entirety of Sweden, with two single map products of above-ground biomass (AGB) and forest stem volume (VOL), both with 10 m resolution. The main objective was to explore the possibilities and overcome the challenges related to forest mapping extending a large number of adjacent satellite scenes. Hence, numerous examples are presented to illustrate challenges and possible solutions. To derive the forest maps, the observables backscatter, interferometric phase height and interferometric coherence, obtained from TanDEM-X, were evaluated using empirical robust linear regression models with reference data extracted from 2288 national forest inventory plots with a 10 m radius. The interferometric phase height was the single most important observable, to predict AGB and VOL. The mosaics were evaluated on different datasets with field-inventoried stands across Sweden. The root mean square error (RMSE) was about 21%-25% (27-30 tons/ha and 52-65 m3/ha) at the stand level. It was noted that the most influencing factors on the observables in this study were local temperature and geolocation errors that were challenging to robustly compensate against. Because of this variability at the scene-level, determinations of AGB and VOL for single stands are recommended to be used with care, as an equivalent accuracy is difficult to achieve for all different scenes, with varying acquisition conditions. Still, for the evaluated stands, the mosaics were of sufficient accuracy to be used for forest management at the stand level. [ABSTRACT FROM AUTHOR]

This paper describes a new search strategy within the scope of factorized geometrical autofocus (FGA) and synthetic-aperture-radar processing. The FGA algorithm is a fast factorized back-projection formulation with six adjustable geometry parameters. By tuning the flight track step by step and maximizing focus quality by means of an object function, a sharp image is formed. We propose an efficient two-stage approach for the geometrical variation. The first stage is a low-order (few parameters) parallel search procedure involving small image areas. The second stage then combines the local hypotheses into one global autofocus solution, without the use of images. This method has been applied successfully on ultrawideband CARABAS II data. Errors due to a constant acceleration are superposed on the measured track prior to processing, giving a 6-D autofocus problem. Image results, including resolution, peak-to-sidelobe ratio and magnitude values for point-like targets, finally confirm the validity of the strategy. The results also verify the prediction that there are several satisfying autofocus solutions for the same radar data. [ABSTRACT FROM PUBLISHER]

This paper describes a factorized geometrical autofocus (FGA) algorithm, specifically suitable for ultrawideband synthetic aperture radar. The strategy is integrated in a fast factorized back-projection chain and relies on varying track parameters step by step to obtain a sharp image; focus measures are provided by an object function (intensity correlation). The FGA algorithm has been successfully applied on synthetic and real (Coherent All RAdio BAnd System II) data sets, i.e., with false track parameters introduced prior to processing, to set up constrained problems involving one geometrical quantity. Resolution (3 dB in azimuth and slant range) and peak-to-sidelobe ratio measurements in FGA images are comparable with reference results (within a few percent and tenths of a decibel), demonstrating the capacity to compensate for residual space variant range cell migration. The FGA algorithm is finally also benchmarked (visually) against the phase gradient algorithm to emphasize the advantage of a geometrical autofocus approach. [ABSTRACT FROM PUBLISHER]

In this paper, the results of moving-target detection in multichannel UHF-band synthetic aperture radar (SAR) data are shown. The clutter suppression is done using finite-impulse response (FIR) filtering of multichannel SAR in combination with a two-stage fast-backprojection algorithm to focus the moving target using relative speed. The FIR filter coefficients are chosen with the use of space-time adaptive processing filtering. Two parameters are used for target focusing, target speed in range and in azimuth. When the target is focused, both speed parameters of the target are found. In the experimental results, two channels were used in order to suppress clutter. In the resulting SAR images, it is obvious that very strong scatterers and the forest areas have been suppressed in comparison to the moving target in the image scene. The gain obtained can be measured using signal-to-clutter-and-noise-ratio gain, which is about 19 dB. Another way to measure the signal processing gain is the ability to suppress the strongest reflecting object in the SAR scene. The gain of the target in relation to this object is 25 dB. This shows that using UHF-band SAR ground moving target indication (GMTI) for suppressing forest and increasing the target signal can work. [ABSTRACT FROM PUBLISHER]

Above-ground forest biomass is a significant variable in the terrestrial carbon budget, but is still estimated with relatively large uncertainty. Remote sensing methods can improve the characterization of the spatial distribution and estimation accuracy of biomass; in this respect, it is important to examine the potential offered by new sensors. To assess the contribution of the TanDEM-X mission, eighteen interferometric Synthetic Aperture Radar (SAR) image pairs acquired over the hemi-boreal test site of Remningstorp in Sweden were investigated. Three models were used for interpretation of TanDEM-X signatures and above-ground biomass retrieval: Interferometric Water Cloud Model (IWCM), Random Volume over Ground (RVoG) model, and a simple model based on penetration depth (PD). All use an allometric expression to relate above-ground biomass to forest height measured by TanDEM-X. The retrieval was assessed on 201 forest stands with a minimum size of 1 ha, and ranging from 6 to 267 Mg/ha (mean biomass of 105 Mg/ha) equally divided into a model training dataset and a validation test dataset. Biomass retrieved using the IWCM resulted in a Root Mean Square Error (RMSE) between 17% and 33%, depending on acquisition date and image acquisition geometry (angle of incidence, interferometric baseline, and orbit type). The RMSE in the case of the RVoG and the PD models were slightly higher. A multitemporal estimate of the above-ground biomass using all eighteen acquisitions resulted in an RMSE of 16% with R2 = 0.93. These results prove the capability of TanDEM-X interferometric data to estimate forest aboveground biomass in the boreal zone. [ABSTRACT FROM AUTHOR]

This paper analyzes the statistical properties of the very high frequency (VHF)-band radar backscattering from coniferous trees by incorporating forest ground truth data into a physical-optics (PO) model that assumes horizontally transmit and receive polarizations and dominant double-bounce scattering from vertical stems standing on an undulating ground surface. The analysis shows that a statistically adequate model for the tree backscattering amplitude can be presented as a mixture of generalized gamma or lognormal distribution, and the mixture model can be reduced to a single density model if the trees with trunk volumes exceeding an appropriate threshold are to be taken into account. The generalized gamma density is shown to provide an appreciably better fit to the exceedance functions associated with the PO model data than that for the lognormal density. The results can be used to design statistically adequate models of forest clutter for VHF synthetic aperture radar systems. [ABSTRACT FROM AUTHOR]

Moving-target detection in ultrawideband (UWB) synthetic aperture radar (SAR) is associated with long integration time and must accommodate azimuth focusing for reliable detection. This paper presents the theory on detection of moving targets by focusing and experimental results on single-channel SAR data aimed at evaluating the detection performance. The results with respect to both simulated and real data show that the ability to detect moving targets increases significantly when applying the proposed detection technique. The improvement in signal-to-clutter noise ratio, which is a basic requisite for evaluating the performance, reaches approximately 20 dB, using only single-channel SAR data. This gain will be preserved for the case of multichannel SAR data. The reference system for this study is the airborne UWB low-frequency SAR Coherent All RAdio BAnd Sensing II. [ABSTRACT FROM AUTHOR]

The Phased Array type L-band Synthetic Aperture Radar onboard the Advanced Land Observing Satellite has, since its launch, been acquiring an extensive data set of images over two forest test sites in Sweden. The sites of Remningstorp (Lat. 58°30′ N, Long. 13°40′ E) in the south and Krycklan (Lat. 64°14′ N, Long. 19°50′ E) in the north of Sweden are characterized by hemiboreal and boreal forests, respectively. In this paper, we have investigated the signatures of standwise backscatter measurements from forests with different growth stages in relation to polarization, environmental conditions, image viewing geometry, and spatial resolution. The HV backscatter presented stronger sensitivity to the forest growth stage than the HH and VV backscatter. Under unfrozen conditions, the dynamic range of fine-beam data acquired at 34.3° was 8-9 dB for the HV polarization and 6-7 dB for the HH polarization. At 21.5°, in the polarimetric mode, the dynamic range was 6, 7, and 9 dB at VV, HH, and HV polarizations, respectively. Regardless of the specific polarization, the backscatter was temporally consistent under unfrozen conditions, with a small increase of backscatter in regrowing young forest for wet conditions. Under thawing and frozen conditions, repeated measurements were available only for the HH backscatter at 34.3°. For thawing conditions, the backscatter level was similar to the unfrozen conditions even though the signatures differed depending on temperature dynamics, snow-cover properties, and precipitation. Under frozen conditions, the signatures varied depending on temperature. For images acquired when the temperature was well below the freezing point, the backscatter was low, and the dynamic range was small (2-4 dB); nonetheless, the measurements were consistent. Images acquired when temperature was close to the freezing point pre- sented a behavior similar to unfrozen conditions. The sensitivity of the backscatter to the image viewing geometry for different growth stages was studied for data acquired under dry unfrozen conditions. The backscatter difference increased for increasing look angle because of the increase in volume scattering and the decrease of ground-surface backscatter. The largest difference was observed at 41.5° with 2.5-4.dB difference for the HH and 4-5-dB difference for the HV case. Loss of spatial resolution (20-50 m) lid not have any effect on the backscatter signatures in Krycklan, vhereas in Remningstorp, the smallest stands were affected. [ABSTRACT FROM AUTHOR]

Presents a study on the relationships between very high frequency (VHF) data and biomass using data acquired by the Airborne Imaging Radar Coherent All-Radio Band Sensing (CARABAS) over two different pine plantation forests in southern France. Information on the test site and the CARABAS system; Description of the modeling work; Comparison between theoretical and experimental results; Use of VHF synthetic aperture radar for forest biomass mapping.

Mapping of tree height is of great importance for management, planning, and research related to agroforestry parklands in Africa. In this paper, we investigate the potential of spotlight-mode data from the interferometric synthetic aperture radar (InSAR) satellite system TanDEM-X (TDM) for mapping of tree height in Saponé, Burkina Faso, a test site characterised by a low average canopy cover (~15%) and a mean tree height of 9.0 m. Seven TDM acquisitions from January–April 2018 are used jointly to create high-resolution (~3 m) maps of interferometric phase height and mean canopy elevation, the latter derived using a new, model-based processing approach compensating for some effects of the side-looking geometry of SAR. Compared with phase height, mean canopy elevation provides a more accurate representation of tree height variations, a better tree positioning accuracy, and better tree height estimation performance when assessed using 915 trees inventoried in situ and representing 15 different species/genera. We observe and discuss two bias effects, and we use empirical models to compensate for these effects. The best-performing model using only TDM data provides tree height estimates with a standard error (SE) of 2.8 m (31% of the average height) and a correlation coefficient of 75%. The estimation performance is further improved when TDM height data are combined with in situ measurements; this is a promising result in view of future synergies with other remote sensing techniques or ground measurement-supported monitoring of well-known trees. [ABSTRACT FROM AUTHOR]