The European Space Agency's (ESA) BIOMASS mission is a pioneering Earth observation satellite mission launched on April 29, 2025. Utilizing a P-band synthetic aperture radar (SAR), the objective of BIOMASS is to deliver estimates of above-ground forest biomass, forest height (FH), and forest disturbance (FD), with unprecedented accuracy. The mission's primary scientific goal is to quantify the distribution and changes in forest biomass, thereby reducing uncertainties in carbon flux estimates and informing climate models. The satellite's advanced instrumentation and innovative approach allow it to penetrate dense forest canopies, capturing data even in challenging environments. The mission will operate in two distinct phases: the tomographic phase and the interferometric phase, which will support polarimetric interferometric SAR (Pol-InSAR) and tomographic SAR (TomoSAR) processing. Additionally, BIOMASS will provide valuable observational data for ice sheets, deserts, the ionosphere, below canopy topography, and other domains.

This paper describes time-series backscatter measurements using BorealScat-2, which is a multi-polarization, multi-frequency tomographic radar. It is installed on a 50-m tower at a boreal forest site in northern Sweden. We describe the system and show measurements related to forest water dynamics during summer conditions. The measurements include data at P-, UHF- and L-band. Results show periodic diurnal variations for all frequency bands but with different phases and amplitudes depending on frequency band and polarization. The results indicate the potential of estimating forest water dynamics from radar data.

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

The BorealScat tower radar experiment, in Remningstorp, Sweden, acquired tomographic L-band backscatter time series over a boreal forest stand consisting of Norway spruce (Picea abies). Data from summer 2018 is analysed in this study, where diurnal cycles with variations up to more than 1 dB are identified for HH and VV polarizations. The HH cycle has its minimum at night, its maximum at noon and mainly occurs in the middle layers of the forest. Conversely, the VV cycle has its maximum at night, its minimum at noon and is most apparent in the upper and lower forest layers, especially during June and July. The cycles are compared with vapour-pressure deficit (VPD), an indicator of favourable transpiration conditions, and they are seen to co-vary closely. The VV cycle compares well to that seen for P-band in a previous study and is speculated to originate from stem water content variations. The HH cycle cannot be directly connected to stem water content, but is indicated to follow a currently unknown transpiration related phenomena.

Pairs of fully polarimetric ALOS-2 PALSAR-2 L-band SAR images were used to model biomass on backscatter change over seven growth seasons in a hemi-boreal forest. The biomass change was related to backscatter change via consecutive field surveys of 263 field plots with a 10 m radius. To correct for differences in backscatter not related to biomass abundance, a HV-VV polarization ratio based correction, previously used on airborne L-band data, was applied to the data. The uncertainty of obtained predictions (lowest model mean RMSE 65.1 t/ha, lowest model mean bias 7.1 t/ha) was almost identical whether model fitting and prediction used data from the same scene pair, or different scene pairs. This could possibly attest to the feasibility of the backscatter correction for PALSAR-2 data, but no large backscatter offsets were observed for uncorrected data, and significant variance in predictions, due to the inherent noise in the data and the comparatively small area of evaluation plots, inhibit the analysis.

In this study, spaceborne SAR observations were compared to the tower-based radar observations of a hemiboreal forest site in southern Sweden. BorealScat radar tower observations at L- and C-band are verified using Sentinel-1 and ALOS-2 PALSAR-2 products. For L-band, a 14-month backscatter time series was produced. For C-band, a 3.5 year backscatter time series that includes tree deaths due to a bark beetle infestation was produced. Tomographic capabilities of the tower-based BorealScat allowed both canopy-only and full forest backscatter to be analyzed. For a healthy forest, the agreement of tower-based and spaceborne SAR observations was within 0.9 dB for C-band and within 0.6 dB for L-band. Sentinel-1 backscatter was found to be insensitive to tree deaths, whereas variations were clearly visible in the tomographic tower-based backscatter. These results show that tower-based radar observations agree with those of spaceborne SARs and can be used to understand their shortcomings and identify new mission needs.

This paper describes the development and initial evaluation of the BorealScat-2 radar. It is installed on a 50 m tall tower at a boreal forest site in northern Sweden and acquires tomographic and multi-polarization measurements at P- and L-band every 5 min. It is of the same design as its predecessor BorealScat except that the antenna frame can be moved along a 4 m horizontal track. A moveable antenna position is motivated by the need to acquire independent samples to reduce backscatter fluctuations. It also enables focused 3D imaging by combing tomographic and SAR processing when the backscatter fluctuations are temporally stable. We show results from data acquired in 2022, which demonstrates 3D imaging of a forest as well as the response from a trihedral.

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.

Cross-polarized temporal coherence observations of a boreal forest, acquired using a tower-based radar, are presented in this article. Temporal coherence is analyzed with respect to frequency, temporal baseline, time of day of observation, season, meteorological variables, and biophysical variables. During the summer, P- and L-band temporal coherence exhibited diurnal cycles, which appeared to be due to high rates of transpiration and convective winds during the day. During the winter, freeze-thaw cycles and precipitation resulted in decorrelation. At temporal baselines of seconds to hours, a high temporal coherence was observed even at C-band. The best observation times of the day were midnight and dawn. Temporal coherence is the main limitation of accuracy in interferometric and tomographic forest applications. The observations from this experiment will allow for better spaceborne SAR mission designs for forest applications, better temporal decorrelation modeling, and more accurate forest parameter estimation algorithms using interferometric and tomographic SAR data.

In 2016, the BorealScat radar tower experiment was established in a forest site in southern Sweden. The system, based on a 20-channel vector network analyzer, acquires a dense, multi-annual, multi-frequency, multi-polarization tomographic dataset of a forest scene. In this paper we discuss how the system design relates to two performance metrics: backscatter precision and measurement duration. Speckle variance in the time domain is discussed and an approach for avoiding coherent integration loss is presented. These concepts are relevant for any ground-based imaging radar acquiring time series data of dynamic scenes.

Scheduled for launch in 2023, ESA's seventh Earth Explorer Mission, BIOMASS, will carry the first P-band synthetic aperture radar (SAR) to be flown in space, to gather fully polarimetric acquisitions over forested areas worldwide in interferometric and tomographic modes. This paper presents the algorithms developed to estimate biophysical parameters from BIOMASS measurements and their implementation in the BIOMASS level 2 (L2) prototype processor. The L2 processor will generate global maps of forest Above Ground Biomass (AGB), Forest Height (FH), Forest disturbance (FD). Accurate generation of these products requires the L2 processor to be closely inter-linked with the BIOMASS interferometric processor, in order to produce phase-calibrated interferometric stacks, retrieve sub-canopy terrain topography, and generate a 3D representation of forest structure by use of SAR tomography. AGB estimation results are here shown using BIOMASS-like acquisitions derived from campaign data acquired over six tropical forests in South America and Equatorial Africa.

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

This paper describes the rationale and development of the estimation techniques for the level-2 data products of the European Space Agency's 7th Earth Explorer BIOMASS mission. BIOMASS is planned for launch in 2023 and will carry the first-ever P-band synthetic aperture radar (SAR) onboard a satellite. It has been designed to produce consistent global maps of the Earth's forests during a nominal five-year lifetime. Fully polarimetric SAR data will be collected and the satellite orbit will be selected for repeat-pass interferometry and tomography in separated mission phases. Mission requirements call for three level-2 data products: above-ground biomass, forest height and forest disturbance. The paper also discusses the expected limitations of the estimation techniques and remaining problems to be addressed.

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.

In this study, Synthetic Aperture Radar (SAR) backscatter data from the Swedish airborne CARABAS-II and LORA systems were used to estimate stem density. The analysis were performed at the test site Remingstorp, located in the south of Sweden, consisting mainly of coniferous in hemi-boreal forests. In total, ten 80 m × 80 m forested areas, where all trees were measured in situ, with stem densities in the range of 278-552 stems and stem volumes in the range of 70-550 m3ha-1were analysed. SAR data from CARABAS-II and LORA were acquired in 2006 with nine unique flight headings. Local maxima of the backscatter were used to estimate stem density. The results were compared with in situ data and the accuracy in terms of root mean square error (RMSE) for CARABAS-II and LORA were found to be 81 stems (20.9%) and 82 stems (20.2%), respectively, in the best cases. The accuracy assessment of the stem density were performed after averaging images from each SAR system. This was done in order to suppress noise to a greater extent compared to using single images. The results show a potential to estimate stem density with low-freqency SAR data for the benefit of forest management.

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

The ESA BIOMASS mission will be the 7th Earth Explorer measuring the above-ground biomass (AGB) in the world's forests. The current ESA Level-2 (L2) implementation study focuses on defining and implementing the main algorithms for forest parameter retrieval from BIOMASS data. After the first year of L2 study innovative results were achieved: the development of ground cancellation, in particular, has proved to be huge value, since it removes from the data the effects of environmental variability and contributions unrelated to the forest carried in the ground scattering. In this paper the current processor implementation and validation activities of the L2 team will be described.

In this paper, the capability of Sentinel-1 data to map ocean surface currents in the Skagerrak Sea, with a focus on the Norwegian Coastal Current (NCC), is investigated. Post-processing methods for removing artefacts in the data and improving of the geophysical interpretation are suggested. Scalloping is one major artefact, which significantly degrades the quality of the velocity maps. Two methods, in spatial and spectral domain, for correcting this effect are proposed. It is also found that the radial velocity provided in the Sentinel-1 ocean data is biased, hence land is used as a reference to correct for the absolute and inter-beam bias. Finally, the retrieved (corrected) velocity is compared to a regional ocean circulation model (ROMS). It is shown that there is a good agreement between the ocean model and the retrieved velocity with values of ≈ 0.8 m/s in the core of the NCC.

Passive synthetic aperture radar using transmitters of opportunity can be used for remote sensing, using frequency bands that are not normally allowed for transmitting radars. Passive radars do not transmit but instead use signals from other transmitting sources. Useful signal modulations for passive radar include OFDM (Orthogonal Frequency Division Multiplexing) signals for digital TV following the standard Digital Video Broadcasting Terrestrial (DVB-T) [1]. In this paper, we simulate the performance with an open software to decode the OFDM signal registered with the airborne synthetic aperture radar LORA. The LORA system does not register measured samples continuously but some percentage of consecutive samples are thrown away periodically. Moreover, the sampling rate of the LORA system gives a non-integer rational number of samples during the OFDM symbol time period. We conclude that the missing data samples can become deleterious for decoding the DVB-T signal and give guidelines to the maximum allowable data gaps.

This study applies the two-level model to predict stem volume (VOL), presented as wall-to-wall rasters. The SAR data were acquired with the TanDEM-X system and 518 scenes covered the entire Sweden. For comparison, a multiple linear regression model is also evaluated. Compared to earlier studies, the model parameters are fitted separately for each satellite scene. The prediction accuracy at the stand-level is evaluated using field inventoried reference stands within one scene, located in Northern Sweden and provided by a Swedish forest company. The results from the two models were similar, with an RMSE of 34.8 m3/ha and 32.9 m3/ha at the stand-level, respectively, and the corresponding biases were 14.3 m3/ha and 12.1 m3/ha. The error is significantly lower, compared to a previous study (52-65 m3/ha) where a universal multiple linear regression model was used for all scenes. It can be concluded, that using model parameters fitted at the local scene appears to improve the prediction performance in terms of RMSE, but no significant difference could be determined between predictions based on the two- level model or multiple linear regression, evaluated in this study.

BorealScat is a tower-based radar which measures multipolarization and tomographic backscatter time series data at a forest site in Southern Sweden. In this paper, we describe a methodology for absolute radiometric calibration of BorealScat and apply it to a set of backscatter measurements at P-band (420-450 MHz). We present radiometric calibration corrections which take into account antenna gain and range variations over the tomographic resolution cell. We also use data acquired by the LORA airborne UHF-band SAR over the BorealScat site to determine the absolute radiometric calibration factor for P-band and HH- polarization. It is shown that the methodology produces consistent results for multiple SAR images.

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.

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.

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

The main problem in wind retrieval using SAR imagery is the lack of the wind direction information. A few methods have been proposed to extract the wind direction from SAR images. The main limitation of these methods is the 180°ambiguity in the direction. Usually, an external source of wind direction is used to remove this ambiguity. This study exploits the Along-track Interferometric SAR (ATI-SAR) phase to demonstrate its usefulness to tackle this problem. A method is proposed to remove the wind direction ambiguity using the ATI-SAR phase information. This is based on the fact that the interferometric phase is related to the sea surface motion direction. Depending on the sign convention, the phase is positive/negative for advancing/receding target respectively. This effect is used to assist the wind extraction algorithm to select the most plausible direction. The results show a very good agreement with atmospheric model and visual investigation.

SAR tomography at P-band allows the separation of scatterers throughout the vertical extent of a forest canopy, offering a SAR observable that can be used for biomass estimation. But the vertical backscattering distribution of forests are sensitive to changes in the weather and seasons, effects which are poorly understood. In this study, a tower-based radar is used to produce fully-polarimetric tomographic images of a boreal forest at P-band which are analysed over a period of one year. The largest variations seen were due to sub-zero temperatures, causing a drop in the effective scattering height. Seasonal changes in soil moisture and temperature caused a drop in ground-level backscatter at HH-polarisation and a drop in canopy-level cross-polarised backscatter during the summer.

This paper presents the first results from model-based TanDEM-X tomography of a structurally complex temperate forest in Tasmania. Two tomographic profiles are shown and heights estimated using three-level model inversion are compared with similar metrics from airborne lidar scanning.

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

The Earth Explorer Biomass mission will provide the scientific community with accurate maps of tropical, temperate and boreal forest biomass, including height and disturbance patterns. This information is urgently needed to improve our understanding of the global carbon cycle and to reduce uncertainties in the calculation of carbon stocks and fluxes associated to the terrestrial biosphere. It is also crucial for approaches to managing climate, such as the UNFCCC initiative known as Reducing Emissions through Degradation and Deforestation (REDD+), aimed at climate change mitigation through conservation and better management of tropical forests The required measurements are forest biomass and forest height at resolution of 200 m, and detection of deforestation at 50 m. Global maps of biomass are required with accuracy of 20% (or l0 t ha-1when above-ground biomass are less than 50 t ha-1). To achieve this Biomass will be implemented as a P-band SAR mission. It will exploit the unique sensitivity of P-band SAR together with advanced retrieval methods including polarimetric interferometry (Pol-InSAR) and SAR tomography to measure biomass, height and disturbances across the entire biomass range every 6 months. The mission will also support important secondary objectives, including sub-surface imaging in arid zones, production of a bare-earth DTM and ice applications.

A tomographic synthetic aperture radar (TomoSAR) represents a possible route to improved retrievals of forest parameters. Simulated orbital L-band TomoSAR data corresponding to the proposed Satellites for Observation and Communications-Companion Satellite (SAOCOM-CS) mission (1.275 GHz) are evaluated for retrieval of above-ground biomass in boreal forest. L-band data and biomass measurements, collected at the Krycklan test site in northern Sweden as part of the BioSAR 2008 campaign, are used to compare biomass retrievals from SAOCOM-CS to those based on SAOCOM SAR data. Both data sets are in turn compared with the corresponding airborne case, as represented by experimental airborne SAR through processing of the original SAR data. TomoSAR retrievals use a model involving a logarithmic transform of the volumetric backscatter intensity, Ivol, defined as the total backscatter originating between 10 and 30 m above ground. SAR retrievals are obtained with slope-compensated intensity γ0using the same model. It is concluded that tomography using SAOCOM-CS represents an improvement over an airborne SAR imagery, resulting in biomass retrievals from a single polarization (HH) having a 26%-30% root-mean-square error with a little to no impact from the look direction or the local topography.

We describe a P-, L- and C-band radar, BorealScat, designed for polarimetric time-series measurements of forests. Radar tomography is implemented with a vertical antenna array, which provides measurements of the vertical scattering distribution. To minimize temporal decorrelation, the radar performs simultaneous measurements of the reflected signals using all array elements. The system is implemented using a 20-port vector network analyzer (VNA) and a stepped-frequency waveform. It has two 20-element arrays: one array optimized for P- and L-bands and one for C-band. The arrays are installed on a 50-m high tower and radar measurements are collected over a hemiboreal forest stand. We discuss several design issues and demonstrate some tomographic imaging capabilities. The multiport VNA tomography results are compared with results from the system operating in the slower 2-port VNA measurement scheme.

It has been demonstrated that Along Track Interferometric (ATI) SAR is a useful tool to retrieve ocean surface currents. The ATI SAR provides an interferometric phase (hereafter called phase) which is directly related to the Line-Of-Sight (LOS) component of the surface velocity. The accuracy of ocean currents retrieval is highly dependent on the phase processing. For instance, a properly processed phase must equal zero over static targets. The measured TanDEM-X phase rarely (if ever) satisfies this condition which indicates a phase offset independent of the surface properties. The offset can be either due to a phase synchronization issue or to using inaccurate orbital and attitude information in the processing. The objective of phase calibration is the estimation and the removal of the offset and possible trends from the measured phase. In this paper, the topographic phase is simulated using a Digital Elevation Model (DEM) and baseline information. The calibration is carried out by estimating the average of the phase over land, after topography correction, and subtracting the estimated value from the measured phase. Finally, the residual phase trend is removed using a second order polynomial fitting.

Three-year forest above-ground biomass change were measured using L- and P-band Synthetic Aperture Radar (SAR) backscatter. The SAR data were collected in the airborne BioSAR 2007 and BioSAR 2010 campaigns over the hemiboreal Remningstorp test site in southern Sweden. Regression models for biomass were developed using reference biomass maps created using airborne laser scanning data and field measurements. The results from regression analysis show that using HV backscatter (or VH) in a model with above-ground biomass and backscatter change on either natural logarithmic or square root, and decibel scale, respectively, explained most of the variation in the biomass change, both for L- and P-band. In the case of L-band, the two best cases showed R2values of 66%, when comparing two SAR images acquired 2007 and 2010. For P-band using the same models, the best cases showed R2values of 62%. In summary, the results look promising using L- and P-band backscattering for mapping biomass change.

SESAME (SEntinel-1 SAR companion Multistatic Explorer) is a passive SAR satellite mission proposed for the ESA Earth Explorer Program. SESAME comprises two receive-only C-band SAR satellites flying in close formation to build a single-pass SAR interferometer (SP-InSAR) using the active signal of the European Sentinel-1 satellite. The SESAME mission addresses applications in geoscience and climate research that require repeat measurements of high precision elevation data over land surfaces including ice covered areas and forests, exploiting the SP-InSAR and multistatic observation geometry of the satellite formation. The objectives, the measurement approach and geo-biophysical products of the mission are described.

In this paper, three approaches to forest change modeling with the two-level model (TLM) are compared by fitting the TLM to 12 VV-polarized TanDEM-X acquisitions over a hemi-boreal test site in southern Sweden. It is observed that the best inversion results are obtained when rapid forest change (e.g., harvesting) is modeled as change in canopy density, while growth is modeled as change in forest height.

A C-band convoy mission with a receive-only interferometer using Sentinel-1 as the active sensor could cover the needs for an operational satellite mission for forest monitoring, that can clarify the magnitude and geography of the residual land sink of carbon in the global carbon budget; routinely map forest carbon changes in the tropics for REDD+, and routinely provide updated forest resource maps for operational forestry planning. We are about to carry out an airborne campaign in order to demonstrate the technical feasibility of this, and supplement this with analyses of Tandem-X.

Passive SAR data have been registered using the airborne low frequency SAR system LORA. For this purpose, the radar sensor was reconfigured to not transmit any signals but only gather data along the pre-defined synthetic aperture. The receiver unit was tuned to fully accommodate the DVB-T signal centred at 634 MHz (channel #41), acting as the illuminator of opportunity within the ground scene mapped. SAR images have successfully been formed for areas located in the vicinity of the DVB-T transmitter mast but also at distances 40 km away. In the data set processed, the direct and the ground-reflected signals have been registered with the same antenna element.

This paper describes results from BorealScat, which is a tower-based P/L/C-band radar being developed by Chalmers in the forest site Remningstorp, Sweden. The objective is to investigate the radar signatures in varying environmental conditions. The 50-m tower has been built adjacent to a forest stand, with above-ground biomass of 300 tons/ha and dominated by Norway spruce (Picea abies (L.) Karst.). The radar consists of an antenna array at the top of the tower connected to a 20-port vector network analyser (VNA) with low-loss cables. The first version of BorealScat performs polarimetric and tomographic measurements in the frequency range 420-1375 MHz. Meteorological and soil moisture measurements are also available. We present first results from a time series collected 16-27 December 2016 during which air temperature varied in the range -4° to 8°C.

In this letter, the interferometric water cloud model (IWCM) is fit to 87 VV-polarized TanDEM-X acquisitions made between June 2011 and August 2014 over a boreal forest in Krycklan, northern Sweden, using a new method based on nonlinear least-squares optimization. A high-resolution digital terrain model is used as ground reference during interferometric synthetic-aperture radar (InSAR) processing and 26 stands with areas 1.5-22 ha and unaltered during the study period are studied. The dependence of biomass estimation performance, ground and vegetation backscatter coefficients (σgr0and σveg0), canopy attenuation (α), and zero-biomass coherence (Y0) on selected system and environmental parameters is studied. High correlation between the estimated biomass and reference biomass derived from in situ measurements is observed for all 87 acquisitions (r between 0.81 and 0.93), while the root-mean-square difference is between 18% and 32% for all 43 acquisitions made in snow-free conditions and with heights-of-ambiguity (HOAs) between 36 and 150 m. Significant biomass estimation bias is observed for HOAs above 150 m and for some acquisitions over snow-covered forest. It is also observed that σgr0and σve0are the largest for temperatures below 0 °C and with significant snow cover. For temperatures above 0 °C, σgr0appears independent of temperature, while σveg0shows a tendency to increase with temperature. Moreover, γ0decreases from just below 1 for HOAs around 40 m to around 0.8 for HOAs above 150 m.

Along-Track Interferometric (ATI) SAR has demonstrated through several studies a capability to detect ocean surface currents. One of the most challenging problems in ocean surface current retrieval using SAR is the removal of the wind-wave contribution. The phase difference provided by ATI-SAR technique is directly related to the radial velocity of the moving ocean surface. In order to infer the current-only velocity from the total phase the wind-wave contribution need to be removed. This is achieved by simulation of SAR Doppler spectra from given wind fields. This paper investigates the effect of the local wind on ATI-SAR phase. A study case, where the backscatter modulation is dominated by the wind variation, is illustrated using TanDEM-X data over the Baltic Sea. It is shown that retrieving high resolution winds from SAR data using an empirical wind model and using the retrieved winds as input to the SAR imaging model improves the simulated SAR signatures.

A first evaluation of ALOS-2 PALSAR-2 data for forest stem volume estimation has been performed at a coniferous dominated test site in southern Sweden. Both the Fine Beam Dual (FBD) polarization and the Quad-polarimetric mode were investigated. Forest plots with stem volume reaching up to a maximum of about 620 m3ha−1(corresponding to 370 tons ha−1) were analyzed by relating backscatter intensity to field data using an exponential model derived from the Water Cloud Model. The estimation accuracy of stem volume at plot level (0.5 ha) was calculated in terms of Root Mean Square Error (RMSE). For the best case investigated an RMSE of 39.8% was obtained using one of the FBD HV-polarized images. The corresponding RMSE for the FBD HH-polarized images was 43.9%. In the Quad-polarimetric mode the lowest RMSE at HV- and HH-polarization was found to be 43.1% and 66.1%, respectively.

This paper describes BorealScat, a tower-based radar campaign for acquiring multitemporal polarimetric, tomographic and Doppler radar measurements at P-, L- and C-band over a hemi-boreal forest site in Remningstorp, Sweden. The facility consists of a 50-m high tower equipped with a radar system including an array of 30 antennas. The site will also be equipped with meteorological instruments and moisture sensors. The aim of the experiment is the temporal survey of radar signatures over time scales ranging from sub-seconds to years in varying environmental conditions. This experiment will provide fundamental information about the electromagnetic scattering mechanisms in boreal forests at P-, L- and C-band.

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.

A model for retrieval of boreal forest biomass from polarimetric P-band SAR images developed using the BioSAR 2007 and BioSAR 2008 data sets is revisited and evaluated using data from BioSAR 2010. Incorporating the HV backscatter component as well as the HH/VV ratio and the ground slope, the model is noteworthy as performing well when retrieving biomass values in Remningstorp using parameters trained in Krycklan. These two Swedish test sites are separated by 720 km and represent two different types of boreal forest as well varying topography. SAR images and biomass estimates obtained from Remningstorp in 2010 provides an opportunity to test the model further. This dataset results in a qualitative reproduction of the previous result, showing the expected changes due to forest management, but with a relative overestimation of biomass. A large part of this can be explained by the timing as the new acquisitions took place during early autumn instead of spring with the associated changes in moisture conditions.

Interferometric TanDEM-X data from 2011 and 2014 were used to create biomass maps over the Swedish test site Remningstorp. These maps were used to compute the biomass change for four classes; pre-commercial thinning, thinning, clear-cutting, and untouched forest. Field inventory and ALS data from the corresponding years were used as reference data. The biomass change was compared on 12 subjectively chosen plots with 40 m radius for each class. It was found, that pre-commercial thinning was difficult to detect, as the biomass loss was less than the biomass growth during the four vegetation seasons investigated. Thinning could be detected from the biomass change being about zero or slightly negative, while clear-cut plots were obvious to notice, with the biomass withdrawal being several hundreds of tons ha-1. The untouched plots had a biomass growth of about 4 to 6 tons ha-1year-1. It was concluded, that annual TanDEM-X images can be used to detect also smaller silviculture activities such as thinning, but further research with shorter time periods would be desired.

In this paper, forest change detection and forest height estimation are studied using two-level model (TLM) inversion of multi-temporal TanDEM-X (TDM) data. Parameter Ah, describing the distance between ground and vegetation levels, is kept constant for all acquisitions, whereas parameter ¡jl, the area-weighted backscatter ratio, changes with acquisition. Two multi-temporal sets of TDM data, acquired over the hemi-boreal test site Remningstorp, situated in southern Sweden, are studied: one consisting of 12 acquisitions made in the summers of 2011, 2012, 2013, and 2014 with heights-of-ambiguity (HOAs) between 32 m and 63 m, and one consisting of 33 acquisitions made between August 2013 and August 2014 with HOAs between 38 m and 195 m. The first dataset is used to show that commercial thinnings and clear-cuts can be detected by studying the canopy density estimate r/o = 1/(1 + /x). The second dataset is used to show that seasonal change can be observed in r/o for deciduous plots, but not for coniferous plots. Moreover, it is shown that 1.3Ah is a good estimate of the basal area-weighted (Lorey's) height, with a correlation coefficient equal to 0.98 and a root-mean-square error of 0.9 m.

In this paper, the potential of mono- and bistatic HH-polarized UHF-band SAR imagery for mapping of a hemi-boreal forest is studied. SAR data have been acquired with the two airborne SAR sensors LORA and SETHI during a joint FOI-ONERA campaign conducted in 2010. Three acquisition modes are compared: monostatic, quasi-monostatic (difference in elevation angle around 0°) and bistatic (difference in elevation angle around 6°). Images acquired at two perpendicular flight headings are used, i.e. 178° and 268°, to evaluate the influence of topography, which often has an aggravating effect on forest variable estimation. It is observed that for the quasi-monostatic and bistatic acquisitions, the influence of ground topography is lower compared to the monostatic acquisition. A linear regression model is used to explain the dependence of the backscattering coefficient on the logarithm of biomass, and it is observed that the estimated intercept and slope are similar for the two headings only in the case of quasi-monostatic and bistatic acquisitions, of which the latter features the lowest error and the highest coefficient of determination (0.73 and 0.70, respectively, for headings 178° and 268°).

A two-level model (TLM) is introduced and investigated for the estimation of forest height and canopy density from a single ground-corrected InSAR complex correlation coefficient. The TLM models forest as two scattering levels, namely, ground and vegetation, separated by a distance Δh and with area-weighted backscatter ratio μ. The model is evaluated using eight VV-polarized bistatic-interferometric TanDEM-X image pairs acquired in the summers of 2011, 2012, and 2013 over the managed hemi-boreal test site Remningstorp, which is situated in southern Sweden. Ground phase is removed using a highresolution digital terrain model. Inverted TLM parameters for thirty-two 0.5-ha plots of four different types (regular plots, sparse plots, seed trees, and clear-cuts) are studied against reference lidar data. It is concluded that the level distance Δh can be used as an estimate of the 50th percentile forest height estimated from lidar (for regular plots: r > 0.95 and root-mean-square difference (σ)0.59 and σ ≈ 10%, or 0.07).

A model for aboveground biomass estimation from single-pass interferometric synthetic aperture radar (InSAR) data is presented. Forest height and canopy density estimates Δh and η0, 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°; 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.

Presents corrections to the paper, "Estimation of forest biomass from two-level model inversion of single-pass InSAR data" (Soja, M.J., et al.,Trans. Geosci. Remote Sens., vol. 53, no. 9, pp. 5083–5099, Sep. 2015).

A fully polarimetric model is implemented to simulate backscatter from boreal forest. The aim is to correct for topography on a sub-stand level during the recovery of forest properties from P-band SAR data, specifically directed at the upcoming BIOMASS mission. The model incorporates the direct, double-bounce and triple-bounce scattering from tree stems on a sloping ground. Topography is introduced by assigning an independent and arbitrarily oriented local ground plane to each tree. Simulated SAR images are produced from in-situ measurements and a high resolution digital topography model (DTM) based on LiDAR data. These were obtained during BioSAR 2010 together with the corresponding SAR images, which are used for validation.

A new model for aboveground biomass estimation from forest height and canopy density estimates obtained from the inversion of a two-level model (TLM) is presented and studied using data from the hemi-boreal test site Remningstorp, situated in southern Sweden. Three bistatic-interferometric TanDEM-X acquisitions from the summers of 2011, 2012, and 2013 and with heights-of-ambiguity (HOAs) 49 m, 32 m, and 63 m, respectively, are used. An external, high-resolution digital terrain model (DTM) is used as ground reference during interferogram flattening. Model parameters are estimated for each acquisition separately, and the model is evaluated on all three acquisitions, to examine both its explanatory and predictive values. Residual root-mean-square errors (RMSEs) are 14%-19% and the model explains 67%-84% of the variance in the data. Prediction RMSE is 20% for the two images with the highest HOA, but much higher for the third image.

A polarimetric-interferometric forward model (FM) for extended covariance matrix modeling is presented. The FM has been designed to be used within the end-to-end simulator for BIOMASS, a new ESA satellite mission aiming at the global mapping of above-ground forest biomass with P-band synthetic aperture radar (SAR). The FM uses linear regression models for prediction of backscatter intensity and HH-VV correlation coefficient, and the random volume over ground (RVoG) model for the prediction of the interferometric correlation coefficients. For boreal forest, parameter values for these sub-models have been derived using polarimetric-interferometric SAR data acquired within the BioSAR 2007 campaign over the Swedish test site Remningstorp. The FM is evaluated qualitatively in a boreal forest scenario through a side-by-side comparison with BioSAR 2007 data. The general agreement is good, although there are regions with structures which cannot be reproduced by the model, probably due to insufficient forest description by the input parameters.

In the frame of the Biomass mission activities, this paper presents the challenges and recent results in the retrieval of forest biomass from polarimetric (PolSAR) and interferometric (PolInSAR) P-band SAR data. During the mission Phase A, critical issues in the biomass retrieval algorithms in boreal and tropical forests have been identified and addressed. In boreal forest, multi polarization backscatter data can be used to mitigate much of the variability due to environment effects. In high biomass tropical forest, because of the low sensitivity of the backscatter to biomass, appropriate correction methods were developed to mitigate the disturbing effects. Also to enhance the retrieval results, a combination of PolSAR and PolInSAR methods was proposed.

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.

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.

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.

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.

The understanding of the relationship between surface currents derived from weather models and remote sensing data is essential in order to produce an improved and integrated surface current information of high quality and resolution. The large availability of satellite derived infrared radiometer data at the high latitudes of the coastal waters surrounding Sweden makes the Maximum Cross Correlation (MCC) method a feasible alternative to produce real time measurements of surface currents. This work compares current retrievals from the MCC method and model data around Sweden. Our results indicate a similar magnitude for both sources of current fields in most of the locations. However, there exist small discrepancies in the localization of the larger current values. Also, the MCC retrievals generally present more features than the modeled ones. Possible reasons for these discrepancies might be the MCC detection of circulation patterns not predicted by the model, or the depreciation in the MCC performance due to the influence of diurnal variability of the sea surface temperature, wind driven mixing due to upwelling or tides.

Synthetic Aperture Radar (SAR) backscatter data from the Swedish airborne CARABAS-II and LORA systems were used to estimate stem volume at stand level. The study was performed in hemi-boreal forests at the Remningstorp test site, located in southern Sweden. In total, ten 80 m × 80 m stands, where all trees were measured in situ, with stem volumes in the range of 70-530 m3ha-1(on average 347 m3ha-1) were analyzed. SAR data from CARABAS-II and LORA were acquired from two different years, with nine unique flight headings that were repeated for each system and year. Regression analysis was used to estimate stem volume and the accuracy was assessed in terms of Root Mean Square Error (RMSE). As a first step, stem volume was estimated for each flight heading separately. The accuracy assessment was then performed by weighting the separate estimates for each system and year inversely proportionally to the variance about the regression function. The best results for CARABAS-II and LORA showed a relative RMSE of 7% and 24% of the mean stem volume, respectively. In a previous study, stem volume was estimated using LiDAR data and the same forest stands, resulting in an RMSE of about 12%. In conclusion, the estimation accuracy of stem volume using combined low-frequency CARABAS SAR images was found to be superior to that from using LiDAR data for the stands investigated.

Interferometric TanDEM-X data are used together with high-resolution, airborne lidar-derived digital elevation models (DEMs) to produce digital canopy models (DCMs) for the boreal forests of Remningstorp and Krycklan, situated in southern and northern Sweden, respectively. An overview of interferometric data processing is given. First results showing the potential of TanDEM-X-based forest canopy mapping are presented. It is concluded that baselines giving height-of-ambiguity values in the order of 50-80 meters are preferable, although factors such as angle of incidence and along-track baseline are also of importance. Clear-cuts can easily be detected thanks to the high resolution of TanDEM-X imagery. Seasonal variations of scattering height are most visible for deciduous trees, where the scattering height is significantly lower in the winter, probably due to the lack of leaves.

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.

Low frequency synthetic-aperture radar (SAR) in combination with change detection techniques can be used to search for stationary ground targets. In particular, the method has shown a great potential when vehicle-size objects are obscured by foliage. However. one possibility is to improve the detection capabilities to increase the aperture angle of the radar data acquisition to make sure that the strong cardinal responses of a typical vehicle are registered. This implies an angle of at least 180° to include the strongest (broadside) response when the target orientations are unknown. HF-VHF SAR data (20-90 MHz) have earlier successfully been exploited on this and now tests have also been conducted with the airborne VHF-UHF SAR system LORA (220-430 MHz) using the maximum angle 360°, i.e. a full circle. A first look on this data set indicates a possibility to obtain an extended response signature from the hidden targets compared to the corresponding images generated from the linear tracks made during the same flight mission. The image processing of circular tracks becomes more complex and precise processing of the imaging geometry is necessary, i.e. both accurate navigation data as well as a dense digital elevation model (DEM) of the illuminated ground segment.

Airborne bistatic SAR data have been collected at VHF- and UHF-band to investigate clutter suppression in forested and urban areas. The synchronization between the SAR systems is accomplished using the 1-PPS signal provided by the GPS system. The same signal is also used as input to a disciplined 10 MHz master oscillator integrated in both radar systems to maintain sufficient phase stability. Images have successfully been generated using the time domain fast factorized backprojection algorithm, modified for the bistatic case. Clutter suppression has been observed when comparing the monostatic and bistatic images acquired simultaneously by the two SAR sensors. Work is in progress to quantify and compare the obtained results.

This paper provides an overview of the BIOMASS Mission End-to-End simulator (BEES) and of the mission performance analysis performed with it. The end-to-end performance, in terms of biomass estimates error, is close to the 20% error goal set for the mission. The main sources of errors are temporal decorrelation and the limited available bandwidth, while system induced errors have a negligible impact on the final performance.

The BIOMASS mission is designed to provide unique information on the biomass in the world's forests at spatial and temporal resolutions suitable for characterizing their dynamics and their contribution to carbon cycle estimates. To achieve this it combines biomass estimates from direct inversion of polarimetric backscattering coefficients with Pol-InSAR forest height estimates. The mission will also support important secondary objectives, including sub-surface imaging in arid zones, production of a bare-earth DTM and ice applications, and is optimized to be robust against environmental and ionospheric disturbances.

Using data from the recent BioSAR 2007 and BioSAR 2010 campaigns, it has for the first time been possible to measure forest biomass change using P-band SAR data. Regression models based on backscatter change have been developed using reference data derived from high density laser scanning data. The models were evaluated for six areas with detailed in-situ measurements, for which the maximum biomass loss and growth was 30% and 20%, respectively. For the best model the coefficients of determination was 55-89%. This result suggests that not only clear cuts but also forest growth and thinning can be measured using P-band SAR backscatter.

The BIOMASS mission is designed to map the full range of the world's above-ground forest biomass, for the needs of national scale inventory and global carbon flux calculations. This objective is achieved with advanced P-band SAR techniques. The P-band biomass measurement concept was based on previous work over the past two decades. During the preparatory phase, new campaigns have been conducted to address critical issues on the biomass retrieval algorithms, over tropical and boreal forests. The collected datasets comprise accurate and complete sets of in situ data and advanced P-band SAR data. This paper presents the retrieval algorithms developed using the collected datasets.

We present results from the LORAMbis bistatic VHF/UHF-band SAR experiment conducted in September 2010. The SAR flights were performed with the French SETHI system and the Swedish LORA system installed in two aircraft. Frequency band was 222-460 MHz and polarization was HH. Results from two tests sites (Kvarn and Remningstorp, both in southern Sweden) show that forest clutter generally decreases for increasing bistatic elevation angles. This observation is explained by reduction of the ground-trunk double-bounce scattering mechanism. Results also indicate that vehicles in forest concealment are often better discriminated in bistatic compared to monostatic SAR images. Examples of signal-to-clutter-ratio measurements for vehicles show an increase 7-17 dB when the bistatic elevation angles increased from 0° (quasi-monostatic) up to 10°. These show the potential for improved target detection using VHF/UHF-band bistatic SAR.

Circular-aperture synthetic aperture radar (SAR) imaging has been evaluated using the airborne very high frequency (VHF) band Coherent All RAdio BAnd Sensing (CARABAS)-II system (20-90 MHz). Images, as well as results, from detection of vehicles in dense forest concealment have been compared with linear-aperture SAR. Circular-aperture SAR imaging provides higher image resolution and increased object information, but complexity of signal processing and requirements on imaging geometry accuracy increases. The latter is, however, partly mitigated by using low frequencies in the VHF band. A high-quality digital elevation model is used to ensure high-quality image focusing and to avoid distorting object shape. Contrast optimization is used to reduce global focusing errors. The image resolution is observed to be about 1 m2in agreement with theoretical predictions. Detection performance has been evaluated using image data from a full circular synthetic aperture, i.e., 360° of aspect angle variation. Results, both for single-pass detection (SPD) and change detection (CD), show a considerable advantage compared with detection based on linear-aperture SAR. The detection probability for SPD increases from 0.4 to 0.8 at a false-alarm rate (FAR) of 30/km2. For CD, the detection probability increases from 0.7 to 0.9 at a FAR of 2/km2.

Biomass estimation performance using polarimetric interferometric synthetic aperture radar (PolInSAR) data is evaluated at L- and P-band frequencies over boreal forest. PolInSAR data are decomposed into ground and volume contributions, retrieving vertical forest structure and polarimetric layer characteristics. The sensitivity of biomass to the obtained parameters is analyzed, and a set of these parameters is used for biomass estimation, evaluating one parametric and two non-parametric methodologies: multiple linear regression, support vector machine, and random forest. The methodology is applied to airborne SAR data over the Krycklan Catchment, a boreal forest test site in northern Sweden. The average forest biomass is 94 tons/ha and goes up to 183 tons/ha at forest stand level (317 tons/ha at plot level). The results indicate that the intensity at HH-VV is more sensitive to biomass than any other polarization at L-band. At P-band, polarimetric scattering mechanism type indicators are the most correlated with biomass. The combination of polarimetric indicators and estimated structure information, which consists of forest height and ground-volume ratio, improved the root mean square error (rmse) of biomass estimation by 17%-25% at L-band and 5%-27% at P-band, depending on the used parameter set. Together with additional ground and volume polarimetric characteristics, the rmse was improved up to 27% at L-band and 43% at P-band. The cross-validated biomass rmse was reduced to 20 tons/ha in the best case. Non-parametric estimation methods did not improve the cross-validated rmse of biomass estimation, but could provide a more realistic distribution of biomass values.

Wind vector fields are currently available from different sources at mesoscale resolutions (2 km to 200 km). The commonly provided wind resolution on 25 km imposes a limit in coastal areas and in the study of small-scale phenomena occurring in the ocean surface. Since wind is the driving force of the ocean, the study of its behavior in sub-mesoscale (<;10 km), improves the understanding of the ocean state. This paper presents a description and assessment of a wind velocity algorithm implemented for C-band (frequency 5.3 GHz) Synthetic Aperture Radar (SAR) data to detect sub-mesoscale wind fields. Results are obtained with the algorithm applied on 14 different SAR images. The quality assessment is performed by the comparison with wind velocity estimates from a numerical weather model and a scatterometer sensor. The statistics of the wind speed retrievals show a bias of about 0.5 m/s, a root mean square (rms) error of 2.6 m/s, and correlation of 79%. For the wind direction, the bias is lower than 8°, with a rms error of about 40° and a correlation of about 85%. The large magnitude of the rms error in the direction is attributed to the differences in variability and resolutions of the data.

This paper discusses the implementation of an end- to-end simulator for the BIOMASS mission. An overview of the system architecture is provided along with a functional description of the modules that comprise the simulator.

Biomass estimation performance from model-based polarimetric SAR interferometry (PolInSAR) using generic parametric and non-parametric regression methods is evaluated at Land P-band frequencies over boreal forest. PolInSAR data is decomposed into ground and volume contributions, estimating vertical forest structure, and using a set of obtained parameters for biomass regression. The considered estimation methods include multiple linear regression, support vector machine and random forest. The biomass estimation performance is evaluated on DLR's airborne SAR data at L- and P-bands over Krycklan Catchment, a boreal forest test site in Northern Sweden. The combination of polarimetric indicators and estimated structure information has improved the root mean square error (RMSE) of biomass estimation up to 28% at L-band and up to 46% at P-band. The cross-validated biomass RMSE was reduced to 20 tons/ha.

P-band SAR backscatter has been proven to be useful for forest biomass prediction. However, there is a need for further studies on effects of topography on P-band backscatter. In this paper, two prediction models for backscatter are evaluated, one using only biomass as predictor and one which also includes topographic corrections. Data from the BioSAR 2007 and BioSAR 2008 campaigns are used to evaluate the models. A multi-scale error model which is able to handle data from several imaging directions is used. For HH, the slope correction on stand level used in this paper is unable to correct for topographic effects. This is consistent with previous results that within stand topographic variability has a significant impact on HH P-band backscatter. For HV and VV, the model which considers topography gives lower prediction errors than the model which does not include topography. Moreover, for these polarizations topographic the correction strongly reduce the variability in backscatter measurements between imaging directions for stands with ground slopes larger than about 5 degrees.

The ESA funded campaign BioSAR 2010 was carried out at the forestry test site Remningstorp in southern Sweden, in support to the BIOMASS satellite mission under study. Fully polarimetric SAR data were successfully acquired at Land P-band using ONERA's multi-frequency system SETHI. In addition with other data types gathered, e.g. LiDAR and in-situ measurements, the compiled data set will be used for analyses and comparisons with biomass estimation results obtained at the same test site in the campaign BioSAR 2007, in which DLR's E-SAR made the SAR imaging. Detection of forest changes, robustness of biomass retrieval algorithms and long-term P-band coherence will be in focus as well as cross-validations between the two SAR sensors.

A new biomass retrieval algorithm based on P-band multi- polarization backscatter has been developed and evaluated based on SAR and ground data over boreal forest. SAR data collections were conducted on three dates at a test site in southern Sweden (Remningstorp, biomass <; 300 tons/ha; late winter to early summer 2007) and on a single date at a test site in northern Sweden (Krycklan, biomass <; 200 tons/ha; fall 2008). The retrieval algorithm is a multiple linear regression model including the HV-polarized backscatter coefficient, the VV/HH backscatter ratio and the ground slope. Regression coefficients were determined from Krycklan data followed by algorithm evaluation using Remningstorp data. The results from the latter show that RMS errors vary in the range 29-42 tons/ha depending on date and stand type. The new algorithm is also compared with alternative algorithms and found to give significantly better performance. The developed model is a significant step towards an algorithm which gives consistent results across multiple sites and dates, i.e. when forest structure, topography and moisture conditions is expected to vary.

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.

Radar imaging of tropical vegetation at VHF- and UHF-band has been performed using the airborne SAR sensors CARABAS-II and LORA, respectively. The acquired data set is limited to HH-polarized registrations only. The area mapped exhibits a rough terrain with dramatic topographic variations, mostly covered by dense tropical rain forests. Multiple illumination directions spanning 360° were adopted in the data collection for both sensors to overcome the shadowing due to the high relief topography. For each heading, the SAR images generated, adjacent in azimuth and from all imaging passes, were calibrated and geocoded separately and then merged into a mosaic representing the full ground coverage. A first output from the forest backscatter analysis indicates a 12 dB lower level at VHF-band at an incidence angle of about 70°. However, this preliminary result is based on one sample point only, where the investigated forested area was located on a fairly flat ground surface.

The European Space Agency (ESA) released a Call for Proposals for the next Earth Explorer Core Mission in March 2005, with the aim to select the 7thEarth Explorer (EE-7) mission for launch in the next decade. Twenty-four proposals were received and subject to scientific and technical assessment. Six candidate missions were selected and further investigated in the preliminary feasibility studies (Phase 0). One of these missions is BIOMASS, which has recently been selected to proceed to Phase-A. BIOMASS is a response to the urgent need for greatly improved mapping of global biomass and the lack of any current space systems capable of addressing this need.

The influence of the ground slope on radar backscatter has been proven to be greater for lower radar frequencies due to deeper canopy penetration. In this study, multiple heading, P-band SAR data of boreal forest in Sweden was used to find a model for topographic correction for improved biomass retrieval. Eleven models were tested and the best model was selected. The selected model was then used for biomass retrieval. Even by means of the most simplified approach, forest biomass could be established with a root-mean-square error of approximately 50 t/ha for HV and 66 t/ha for HH.

In this letter, we propose an approach to suppress radio-frequency interference (RFI) in ultrawideband (UWB) low-frequency synthetic aperture radar (SAR). According to the proposal, RFI is suppressed by using an adaptive line enhancer controlled by the normalized least mean square algorithm. The approach is tested successfully on real UWB low-frequency SAR data. In order to keep the computational burden down, possible ways to integrate the RFI suppression approach into SAR imaging algorithms are also suggested.

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.

This study presents results for observing forest changes m Sweden using multi-temporal L-band satellite data and is a part of the JAXA's ALOS Kyoto and Carbon Initiative. An extensive dataset of images acquired by the Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) is investigated for clear-cut detection m boreal forests m northern Sweden (Lat. 64°14' N, Long. 19°50' E). Strong forest/non-forest contrast and temporal consistency were found for the Fine Beam Dual HV-polanzed backscatter during unfrozen conditions. Thus, a simple thresholding algorithm that exploits the temporal consistency of pair-wise HV-backscatter measurements has been developed for clear-cut detection. When applied to an image pair acquired during favorable weather conditions, the detection algorithm identified 76% of the clear-cut pixels within a reference layer, with zero erroneously detected pixels. With further refinement the developed methodology can be an option to present operational alternatives for clear-cut detection.

With the continued threat of global warming, the need to obtain consistent and accurate measurements of the carbon stored in forests is strong. L- and P-band SAR backscatter data have shown to be sensitive to forest biomass, which in turn is coupled to the stored carbon. In this paper a biomass retrieval method is developed for L- and P-band using data from the BioSAR campaign conducted in Sweden during the spring 2007 over hemi-boreal forest. The results show that the use of L-band data gives an underestimation of biomass for stands with high biomass; while for P-band no such underestimation is seen. RMSEs are found to be 30-40% of the mean biomass for L-band and about 25% for P-band for stands with biomass ranging from 10 to 290 tons/ha.

The objective of this paper is to assess the accuracy of an autofocus method developed for the Fast Factorized Back-Projection (FFBP) algorithm in simulated scenarios. We specifically address the question whether correlation measurements between subimages will suffice in the focusing process in one arbitrary merging step. A forest clutter model is used together with a model of the impulse responses to simulate two SAR sub-images of a forest. Correlation is used for sub-image matching and residual displacement errors are compiled using simulation. We conclude that the matching error increases with increased number of trees per resolution cell but can be restored with a larger image size in the correlation measurements. We also conclude that the autofocus method will be successful.

For spaceborne synthetic aperture radar (SAR) systems operating at L-band frequencies or lower, the ionosphere may have a significant impact on the SAR images. The largest effect at L-band is caused by Faraday rotation (FR). Several studies have modeled the effect of FR and/or devised models to measure and correct FR. With the launch of the fully polarimetric L-band system Phased Array-type L-band SAR (PALSAR), it has become possible to test both models and measurement techniques on real SAR data. In this letter, the quality of calibrated polarimetric PALSAR data is assessed, and FR is measured. It is found that residual crosstalk and channel imbalance are small in the PALSAR data. Two methods are used to measure FR, the first using in-scene distributed targets and the second using large trihedrals. The two methods show very good agreement. The measurements are compared with values of the total electron content using a linear model. It is found that the model and measurements are in good agreement, with a root-mean-square error of 0.3degor 15% of the mean FR angle.

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-1for 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 ldr ha-1over the range of 50-400 ton ldr ha-1). The retrieval accuracy is similar to that previously obtained for similar forests standing on flat and horizontal ground.

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. 58deg30' N, Long. 13deg40' E) in the south and Krycklan (Lat. 64deg14' N, Long. 19deg50' 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 34.3deg was 8-9 dB for the HV polarization and 6-7 dB for the HH polarization. At 21.5deg, 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 34.3deg. 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 presented 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 41.5deg 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) did not have any effect on the backscatter signatures in Krycklan, whereas in Remningstorp, the smallest stands were affected.

Global warning is now known to be the major environmental issue mankind will have to face in the next decade. Monitoring of vegetation and biomass is clearly an essential piece of information required at all levels ranging from the scientific studies to understand and forecast, to the political world responsible for drafting remediation policies and evaluating their impact. Microwave remote sensing with the low-frequency SAR technique can provide a useful characterization of forest (spatial coverage, species, density, height...) at a global scale, relying on the all-weather imaging capabilities of SAR linked with the significant penetration of the low-frequency EM wave in the canopy. In this paper, we will review the potential polarimetric indicators and evaluate their performance over several types of forest. We will particularly focus on the impact of the topography and the influence of the weather conditions.

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.

SAR interferometry, requires the sensor separation to be below a critical baseline above which the coherency is lost as the ground projected frequency ranges do not overlap (frequency band shifting of one sensor -the delta-k system- is not addressed here). Indeed, as critical baseline increases with both wavelength and bandwidth, low frequency and/or wide band SAR systems have less stringent constraint for interferometric coherence, which is especially worthy for airborne acquisitions. However, as mentioned in earlier publications, the number of fringes apparent on an interferogram is (roughly) limited to twice the inverse of the relative bandwidth. Hence, wide band interferometry requires range migration evaluating for maintaining coherency, this range migration evaluation is similar to a stereogrammetric measure. As relative bandwidth grows, the two techniques merge, which can be illustrated from FOI Carabas VHF SAR data (of which the relative bandwidth is 111%).

In 2006 calibration activities for ALOS PALSAR were conducted in Sweden. Four five-metre trihedral corner reflectors and three smaller dihedral reflectors were deployed and operated during eight months. 23 PALSAR scenes were acquired over the calibration site allowing an evaluation of the quality and temporal stability of the data. Results show that the co-polarized data have been stable during the whole calibration period with variations in the trihedral responses lower than 0.7 dB. The measured resolution in azimuth was 4.4 m and in slant range 4.7 m for single polarization images and 9.5 m for polarimetric data. For the cross-polarized data large variations in the dihedral responses were found. It is assumed that this is caused by a larger sensitivity to pointing errors. For the polarimetric data, estimation of Faraday rotation gave values ranging from 0.1deg to 3deg.

SAR images from the Swedish airborne CARABAS-II and LORA systems have been visually analyzed over simulated wind-thrown forest at both single tree and stand level. In ideal conditions, the results show that LORA is more accurate than CARABAS-II at detecting wind-thrown trees, regardless of tree size and direction of the fallen trees relative to flight heading. Furthermore, the visible single trees in the LORA images appeared more distinct than in the CARABAS-II images, which could be explained by the high resolution in the LORA images. Based on visual interpretation, it is likely that the detection of wind-thrown forests could be improved using VHF/UHF SAR images acquired both prior to and after a storm event.

A controlled experiment has been performed to quantify the ability to detect clear-cuts using ALOS PALSAR data. The experiment consisted of 8 old spruce dominated stands, each with a size of about 1.5 ha, located at a test site in southern Sweden. Four of the stands were clear-felled and the remaining stands were left untreated for reference. A time series of PALSAR images was acquired prior to, during, and after treatment, including 7 fine beam single polarization (FBS, look angle 34.3deg, HH-polarization) SAR images. The results clearly show that the clear-felled stands could be separated from the reference stands. The drop in backscattering coefficient between the reference and the clear-felled stands was on average 2.1 dB. This implies that ALOS PALSAR data potentially can be used for large-scale mapping of changes in forest cover.

A first evaluation of ALOS PALSAR data for forest stem volume estimation has been performed at a coniferous dominated test site in Sweden. In total, 7 Fine Beam Single polarization (FBS, look angle 34.3°, HH-polarization) and 7 Polarimetric (PLR, look angle 21.5°, HH-, HV-, VH-, and VVpolarization) SAR images were used. In total, 56 forest stands with stem volume in the range of 45-650 m3 ha-1 (average 325 m3 ha‒1) were analyzed by relating backscatter intensity to field data. The estimation accuracy of stem volume at stand level was calculated in terms of root mean square error (RMSE). For the best case investigated an RMSE of 30% was obtained using one of the FBS images acquired in the winter season. The corresponding RMSEs for the PLR images with HH-, HV-, VH-, and VV-polarization were 65%, 65%, 62%, and 81%, respectively. The better results for FBS compared to PLR mode could be explained by particularly favorable weather conditions at image acquisition, or by the higher ground resolution in the FBS images, which makes small stands less sensitive to errors in geo- coding.

In previous studies, P-band synthetic aperture radar (SAR) has shown potential for biomass retrieval in forests. However, while measurements show a general agreement that backscatter increases with increasing biomass, different studies show that the backscatter from stands of similar biomass can significantly vary depending on forest structure, hence making biomass retrieval more challenging. In this letter, we show that, while biomass may be the single most important parameter determining the backscatter from a forest, the number density of trees has also a major impact. This can be explained using simple arguments, leading us to propose the use of the biomass-consolidation index to describe P-band HV-polarized backscatter. This is supported by electromagnetic-modeling studies and by a few measurements from boreal forest made with the AIRSAR system over the BOREAS test site in Canada.

This paper describes the Swedish activities to support calibration and validation of the Japanese satellite ALOS. Data over three test sites from the instruments PALSAR and AVNIR-2 will be provided by JAXA for evaluation purposes. The main activity during 2006 is a PALSAR calibration experiment using four 5-m radar reflectors, which will be deployed at the test site in southern Sweden. The ALOS data will also be used for developing forest applications, e.g. detection of clear-cuts and storm damages.

Space- and airborne SAR have a potential for providing timely information of forest storm damage. In this paper, we compare Envisat, Radarsat and CARABAS with aerial photography and field observations after a severe storm event. The spaceborne C-band images were not able to detect the storm- damaged areas due to unfavorable frequency band and coarse resolution. The airborne CARABAS VHF SAR, on the other hand, detects most storm-damaged forest areas and even partly damaged which are often not detected in the aerial photography.

Multiple VHF-band radar images from the airborne CARABAS-II system, retrieved with varying look direction to the imaged area, are coregistered and combined to improve spatial and radiometric resolution. Combined images over boreal forest in southern Sweden are used to identify and make backscatter measurements of individual trees. A coregistration scheme is proposed, and backscatter is compared to ground measurements of individual stem volume. It is found that the spatial resolution and radiometric precision could be significantly improved by combining the images coherently. A nearly linear relation between backscattered amplitude and individual stem volume for trees with a stem volume over 0.2 m/sup 3/ was found, which is in agreement with previous results at stand level.

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 (/spl sim/30 m), on the steepest slopes in the test-site (up to /spl sim/12/spl deg/), 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.

Ground slope effects have been identified as a limiting factor for stem volume retrieval from VHF-band SAR images since the ground-trunk dihedral scattering, which dominates the measured signal, is highly affected by surface relief and slope. To mitigate this problem coregistered SAR images from different flight headings have been acquired. These images are segmented to find regions with homogenous backscatter amplitude that are used with additional topography data to correct for the ground slope

This paper evaluates the use of a spaceborne low-frequency synthetic aperture radar (SAR) for forest biomass retrieval. Airborne radar data are used as input to a SAR simulator in which SAR system parameters of the assumed spaceborne system and propagation effects in the ionosphere (primarily scintillation and Faraday rotation) are modelled. The simulations are performed for different ionospheric perturbation states. Some simulated spaceborne low-frequency SAR images over boreal forest are shown and their usefulness for forest biomass retrieval are studied and discussed The results indicate that it is possible to separate boreal forest into three classes assuming a moderate distorted ionosphere

In this paper the ground slope effect on stem volume retrieval from VHF-band SAR images has been studied using multiple co-registered images acquired from different flight headings. Accurate measurements of the topography were used as additional input data to a model of the backscatter amplitude variation with ground slope and aspect angle. Modeling this topographical effect on the radar backscatter provides a base for improvement of the stem volume retrieval.

This paper presents an example showing how VHF SAR images acquired over the same area, but with different look directions, can be combined in order to improve signal-to-noise ratio and spatial resolution. It is demonstrated that when combining images with 360o of aspect variation, the spatial resolution approaches the theoretical limit set by diffraction. Results are presented showing that it is possible to resolve individual trees in VHF SAR images over reasonably dense coniferous forests, and that there is good correlation between stem volume of individual trees and amplitude in combined SAR images.

LORA (low-frequency radar) is a new airborne VHF/UHF-band radar which has both synthetic-aperture radar (SAR) and ground moving target indication (GMTI) modes. The main motivation for the system is to facilitate detection of man-made objects in a variety of conditions, i.e. stationary or moving, located in open terrain or in concealment under foliage. The LORA system will operate in several configurations extending from 20 MHz to 800 MHz. Initial flight trials during 2002 were successfully conducted using the 200-400 MHz band. SAR image examples are shown including both forested areas and man-made objects. A second band, 400-800 MHz, has also been completed but not yet flight tested. A third band, 20-90 MHz, is being added and will be completed during 2003.

Retrieval of forest stem volume has been the main civilian application investigated for VHF SAR data during recent years. Based on promising results obtained from previous studies, a project was defined with the objective to develop a fully integrated system for retrieval of stem volume at high spatial resolution from CARABAS-II VHF SAR images. Using the developed production line, stem volume can easily be retrieved within predefined forest stands or within homogeneous areas defined by segmentation of optical satellite images. In order to evaluate the accuracy and efficiency of the production line, CARABAS-II images have been collected and analyzed over a test area covering 25/spl times/25 km/sup 2/. The major part of the area is owned by the Swedish forest company Holmen Skog AB. For coniferous forest stands, exhibiting normal forest production conditions, the accuracy in terms of root mean square error (RMSE) for estimation of forest stem volume is about 44 m/sup 3/ ha/sup -1/ (22% of the average stem volume) in the range of 70-400 m/sup 3/ ha/sup -1/, using the developed production line. In comparison to earlier research tools, the developed production line speeds up the analyses approximately 10 times.

Presents a comparison of remote sensing of forests using two complementary, high-resolution sensors; namely the TopEye lidar and CARABAS VHF SAR systems. The lidar data are from a small footprint configuration, allowing discrimination between pulses reflected from the tree crowns, and those penetrating through gaps in the canopy. From these data, measurements of tree height and crown size can be made for individual trees, and the tree volume calculated through empirical relationships. The CARABAS VHF SAR provides a more direct measurement of tree volume, since the long wavelengths penetrate the forest canopy and are scattered by the trunk-ground dihedral. Results of stem volume retrieval for individual trees using data from the two systems are presented, and the possibility of using the complementary measurements discussed.

Thinning cuttings constitute a considerable part of the annually harvested forest stem volume in Scandinavia. The interest to detect thinning cuttings is in the areas of global biomass monitoring in accordance with international treaties, annual local scale measurements of thinnings, forestry law enforcement, and commercial planning of the forest resource. This paper presents results from a study using the airborne CARABAS-II VHF SAR system for detection of thinning cuttings in coniferous forest stands. SAR data were acquired prior to and after thinning cuttings over 25 stands located at a test site in the southwest of Sweden. For the analysis another 24 stands were selected for reference measurements. The results from the statistical analysis show a significant difference between the reference stands and the thinning cuttings for one out of three flight paths examined. A decrease in backscatter due to thinning was found for all image pairs analyzed. Factors influencing the results such as variations in radio frequency environment, image noise variations, and removal of image artifacts have to be further investigated. Nevertheless, the proposed change detection method indicates a possibility to map thinning cuttings using CARABAS-II VHF SAR data.

Strong winds cause severe damage worldwide to forested land every year. The devastating storms that struck large parts of Europe in late 1999 destroyed the equivalent of several years of normal forest harvesting, amounting to very large economical sums. Therefore, rapid mapping of damaged areas is of major importance for assessment of short-term actions as well as for long-term reforestation purposes. In this paper, the use of airborne CARABAS-II very high frequency (VHF) (20-90 MHz) synthetic aperture radar (SAR) imagery for high spatial resolution mapping of wind-thrown forests has been investigated and evaluated. The investigation was performed at a test site located in southern Sweden and dominated by Norway spruce forests. A regression model estimating radar backscattering amplitude prior to the storm was developed. The estimated amplitudes were compared to measured amplitudes after the storm. The results clearly show that the backscattering amplitude, at a given stem volume, is considerably higher for wind-thrown forests than for unaffected forests. Furthermore, the backscattering from fully harvested storm-damaged areas was, as expected, significantly lower than from unaffected stands. These findings imply that VHF SAR imagery has potential for mapping wind-thrown forests. However, to prevent ambiguities in increased backscattering caused by normal stem volume growth or wind-fellings, multitemporal change detection techniques using VHF SAR images acquired prior to and after wind-fellings would be preferable.

The paper investigates digital elevation model (DEM) generation based on data from the ultra wideband coherent all radio band sensing (CARABAS) very high frequency (VRF)-band synthetic aperture radar (SAR). The results show excellent capability to penetrate forest areas, i.e., the generated DEMs are found to be close to the true ground height. A conventional DEM, based on stereo photography and surveying, and additional phase differential Global Positioning System (GPS) measurements have been used for comparison. The results in heavily vegetated areas (stem volume up to 600 m/sup 3//ha) show a mean height difference of less than 1.5 m and a root-mean-square (rms) error of less than 1.0 in compared to the conventional DEM. Stable backscattering properties allows us to use large baselines in order to obtain high height sensitivity. However, the amount of poor data due to low coherence increases with the increase of the baseline. The optimum baseline which balances these two effects is found to correspond to an incidence angle difference of 4/spl deg/-8/spl deg/.

Methods for retrieval of the stem volume, dominant tree height, and dominant tree diameter values using CARABAS images are presented. Both intensity and its texture can be used, but texture detects sparse, low stem volume forests overlooked by the intensity. The texture parameters used are the zero and first-order constants of the log-log regression of the standard deviation of the intensity and the distance over which it is determined. The accuracy of the stem volume estimates is of the order of the ground truth. The dominant diameter and height values are less accurate.

Investigates the relationships between VHF data and forest biomass using data acquired by the airborne imaging radar CARABAS over two different pine plantation forests in southern France. Data are analyzed using detailed ground truth measurements available on both sites. The backscattering coefficient is strongly correlated to characteristics of the tree trunk. Signal saturation is not observed up to 900 m/sup 3//ha. However, the sensitivity to the volume is high in the range of 0-500 m/sup 3//ha (e.g. 1 to 1.5 dB for 50 m/sup 3/ /ha), whereas it is reduced beyond 500 m/sup 3//ha (<0.5 dB for 50 m/sup 3//ha). The experimental analysis is supported by theoretical modeling using a coherent backscatter model based on the distorted Born approximation coupled with a tree growth model giving a fine and precise description of the trees at both sites. The modeling results show that the trunk is the main scatterer, but that, when the branch dimensions are not insignificant compared to trunk dimension, branch scattering needs to be accounted for. However, since the two species under study are both coniferous, branch dimensions are relatively small compared to trunk dimension. This explains no significant differences observed in the backscatter behavior between both sites, except for mature stands with low stem density. Finally, the effect of topography is investigated both experimentally, using a digital elevation model, and theoretically with the coherent model. The loss of sensitivity to stem volume due to slope is clearly demonstrated and explained by the decrease of the dihedral trunk-ground interaction as the slope increases.

The use of airborne CARABASII VHF (20-90 MHz) SAR data for retrieval of forest parameters has been investigated. The investigation was performed at a test site located in the southwest of Sweden consisting mainly of Norway spruce forests. Regression models predicting forest parameters from radar backscattering amplitude were developed and evaluated. The results showed a linear relationship between backscattering amplitude and forest stem volume, stem diameter, and tree height. The analysis also showed that the radar signal is strongly affected by ground slope conditions. The root mean square errors from the regression analysis, restricted to forest stands on near-horizontal ground, were found to be 66 m/sup 3/ ha/sup -1/, 3.2 cm, and 2.3 m for stem volume, stem diameter, and tree height respectively. No saturation of the backscattered signal was observed up to the maximum stem volume of 625 m/sup 3/ ha/sup -1/, corresponding to a biomass of 375 tons ha/sup -1/. The results imply that VHF SAR data have significant potential for operational use in forestry.

A coherent scattering model to determine the forest radar backscattering at VHF frequencies (20-90 MHz) has been developed. The motivation for studying this frequency band is the recent development of the CARABAS Synthetic Aperture Radar (SAR). In order to model the scattering from branches and trunks, homogeneous dielectric cylinders placed above a semi-infinite di-electric ground have been analyzed. An analytical approach, where the theoretically exact currents induced in an infinite cylinder are truncated, has been compared to a numerical solution using the finite difference time domain (FDTD) method. If the first-order coherent ray tracing is included in the analytical approach, the results match well with the numerically exact FDTD solution. The results show that, in order to determine the VHF-backscattering from a forest stand, the coherent ground interaction is an important part and has to be considered. In this paper, modeling results are in good agreement with CARABAS measurements.

A physical model is presented describing the backscatter from coniferous boreal forests in the lower VHF-band in terms of stem volume. By using measurements of mean amplitude in high-resolution SAR images (rather than intensity), a linear dependence on stem volume can be obtained. The model fits well with the measurements made using the coherent all radio band sensing (CARABAS) SAR in the southern boreal forest, indicating the possibility of retrieving stem volume, and hence biomass, with an accuracy similar to that reached by standard ground-based measurements. No saturation of the scattering is seen up to biomasses of 550 m/sup 3//ha.

The authors introduce ultra-wideband synthetic aperture radar (SAR) interferometry as a new technique for topographic height retrieval. It is based on using a SAR system with large relative bandwidth that acquires data along two parallel tracks with a separation of the same order of magnitude as the flight altitude. The complex SAR image data are resampled onto a common reference surface, filtered, and followed by a Hermitian multiplication. The resulting interferogram is shown to have a finite depth-of-focus (DOF) in terms of phase coherence. The achieved height precision is controlled by the ambiguity height, which is shown to scale to the DOF as the relative bandwidth. This means that only one fringe is within the DOF as the resolution approaches the fundamental wavelength limit; i.e., the phase is unambiguously related to topographic height. The topography may thus be determined by changing the reference surface and retrieving the height at each step. The technique is successfully demonstrated to generate fringes based on VHF-band data acquired by the CARABAS airborne SAR system. Temporal decorrelation is not a problem due to the long wavelengths nor is the effect of tropospheric delay on the retrieved height.

Properties of ERS-1 C-band repeat pass interferometric SAR information for a forested area are studied. The intensity information is rather limited but, including coherence and effective interferometric SAR (INSAR) height, more information about the forest parameters can be obtained via satellite. Such information is also important for correction of INSAR derived topographic maps. Coherence properties have been used to identify forested/nonforested areas and the interferometric effective height of the forest determined by comparison to a DEM of the area. The authors have developed a model to relate basic forest properties to INSAR observations. These show that the coherence and interferometric effective height of a forested area change between image pairs. The model demonstrates how these properties are related to the temporal decorrelation and the scattering from the vegetation canopy and the ground surface. Gaps in the vegetation are found to be important in the characterization of boreal forests.

This paper focuses on the spatially varying backscattering signature of an area of refrozen brash ice observed by a ship based scatterometer. The measurements were carried out as part of the Baltic Experiment for ERS-1 in 1994. The scatterometer was operated at 5.4 GHz at different incidence angles and polarizations. By analysing the scatterometer data over azimuth scans, it was found that the backscattering variabilities are not only due to fading but also contain a textural component. Surface height profiles were measured using a laser. The observed ice surface roughness was nonstationary over the measurement area. The ice surface can be approximated by adjacent patches of stationary roughness with patch dimensions of about 4.5 m. From the roughness spectra of different stationary patches, two roughness classes can be distinguished. The implications of estimating the roughness parameters from relatively short profile lengths is discussed and the effect on theoretical predictions of the backscattering coefficient is investigated. The texture variance is evaluated theoretically on the basis of the simulated backscattering coefficients of the two observed roughness classes and is found to compare with the scatterometer data.

The ability to retrieve forest stem volume using CARABAS (coherent all radio band sensing) SAR images (28-60 MHz) has been investigated. The test site is a deciduous mixed forest on the island of Oland in southern Sweden. The images have been radiometrically calibrated using an array of horizontal dipoles. The images exhibit a clear discrimination between the forest and open fields. The results show that the dynamic range of the backscattering coefficient among the forest stands is higher than what has been found with conventional SAR using microwave frequencies. The backscatter increases with increasing radar frequency. This work shows an advantage compared to higher frequencies for stem volume estimation in dense forests.

The brightness in a SAR image is affected by topographic height variations due to (1) the projection between ground and image coordinates, and (2) variations in backscattering coefficient with the local scattering geometry. This paper derives a new equation for (1), i.e. the radiometric slope correction, based on a calibration equation which is invariant under a coordinate transformation. An algorithm is described to obtain the slope correction from a SAR interferogram, which also enables retrieval of the full scattering geometry. Since the SAR image and interferogram are derived from the same data set, there is no need to match the image with the calibration data. There is also no need for phase unwrapping since the algorithm only uses the fringe frequencies. A maximum-likelihood estimator for the fringe frequency is analyzed and the algorithm is illustrated by processing ERS-1 SAR data. The example demonstrates that the spatial resolution and calibration error are adequate for most applications.

Repeat-pass synthetic aperture radar (SAR) interferometry provides the possibility of producing topographic maps and geocoded as well as radiometrically calibrated radar images. However, the usefulness of such maps and images depends on our understanding of how different types of terrain affect the radar measurements. It is essential that the scene coherence between passes is sdcient. In this paper, we derive a general system model including both radar system and scene scattering properties. The model is used to interpret measurements over a forested area where the scene coherence varies between 0.2 and 0.5. The coherence is found to be sensitive to temperature changes around 0°C but surprisingly insensitive to wind speed. The interferometric height discontinuity at the forest to openfield boundary shows good agreement with in situ tree height measurements for a dense boreal forest, but is observed to decrease for a less dense forest. This suggests the possibility of estimating bole volume from the interferometric tree height and a ground DEM. The decrease of scene coherence over a dense forest with increasing baseline is also used to estimate the effective scattering layer thickness.

Radar backscatter signatures of old sea ice in the central Arctic have been measured and analyzed. A ship-mounted scatterometer was used to acquire backscattering coefficients at 5.4 GHz in the four linear polarization states and at incidence angles between 20 degrees and 60 degrees . Detailed in situ characterizations of the snow and ice were also made to enable comparison with theoretical backscatter models. Freeze-up conditions were prevalent during the experiment. The average backscattering coefficient was found to increase when the temperature of the ice surface layer decreased. The semi-empirical backscatter model is used to evaluate the measurements and shows that the backscatter increase is due to an increasing penetration depth, causing the volume scattering to increase. Model predictions also show that both surface and volume scattering contribute significantly at incidence angles of 20 degrees to 26 degrees . At these incidence angles, the dominating scattering mechanism changes from surface to volume scattering as the ice surface temperature decreases.>

Spaceborne synthetic aperture radar (SAR) provides the possibility of producing topographic maps and cartographically corrected radar images using an interferometric method. The technique requires two SAR images of the same area gathered from slightly separated positions. The interferometric baseline may be optimized to minimize the topographic altitude error. The altitude error caused by the radar system and the topography is discussed. The simulation of an interferometric measurement based on ERS-1 SAR parameters is presented. It is found that the terrain topography has a significant effect on the height error, which in many cases is more severe than baseline decorrelation.>

Determining the radar scattering coefficients from SAR (synthetic aperture radar) image data requires absolute radiometric calibration of the SAR system. The authors describe an internal calibration methodology for the airborne Canada Centre for Remote Sensing (CCRS) SAR system, based on radar theory, a detailed model of the radar system, and measurements of system parameters. The methodology is verified by analyzing external calibration data acquired over a six-month period in 1988 by the C-band radar using HH polarization. The results indicate that the overall error is +or-0.8 dB (1 sigma ) for incidence angles +or-20 degrees from antenna boresight. The dominant error contributions are due to the antenna radome and uncertainties in the elevation angle relative to the antenna boresight.>