In this study, we assess the performance of the three state-of-the-art ice drift retrieval algorithms for Synthetic aperture radar (SAR) images. The algorithms were selected by their difference in underlying technique to reveal their advantages and limitations based on C- and X-band data in the Arctic. The results suggest that area-based algorithms are applicable in most cases, while feature-tracking algorithm demonstrates better precision but with fewer produced drift vectors. The hybrid algorithm provides the best data density compared to the other two algorithms but suffers from generating artificial vectors in the case of strong ice speed gradients such as at the edge between fast and drift ice.

A known and challenging effect in the retrieval of ocean surface currents from synthetic aperture radar (SAR), is the so called wave-induced velocity bias. This effect is due to the correlation between the normalized radar cross section (NRCS) and Doppler shift modulations, which are generated by the long modulating waves. This paper analyses two collocated NRCS and Doppler frequency shift images acquired by the along-track interferometric SAR TanDEM-X at two polarizations VV and HH. These images capture a swell traveling nearly in the range direction. First, it is shown that the NRCS and Doppler shift modulations, due to the modulating swell wave, are highly correlated. Second, it is shown that this correlation affects the mean Doppler shift. Consequently, the ocean current estimation can be biased by approximately 0.2 m/s, which can be significant at low current magnitudes and when high-accuracy current retrievals are required.

This paper discusses the alignment of Synthetic Aperture Radar (SAR) image pairs with one image acquired at L- and the other at C-band. For our study we used data from ALOS-2 PALSAR-2 and Sentinel-1 taken over sea ice in the Fram Strait. The use of multifrequency SAR data is beneficial for sea ice characterization and classification because it combines the advantages of the frequency dependence of signal penetration depths and backscattering characteristics due to small-scale ice properties. For drifting sea ice, however, an immediate combination of image pairs acquired with a time gap is usually not possible. Such cases require to consider the effects of ice drift. In this study we investigate the possibility to compensate for sea ice drift for separation in acquisition time ranging from a few hours to several days. The first results are promising and suggest that alignment of SAR image pairs obtained at different frequencies is possible even for larger time gaps between acquisitions if drift and deformation can be estimated reliably.

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.

This paper presents a direct comparison of the sea surface radial velocity (RVL) derived from the two satellite SAR systems Sentinel-1 and TanDEM-X, operating at different frequencies and imaging modes. The RVL is derived from the Doppler centroid (Dc) provided in the Sentinel-1 OCN product and from the along-track interferometric phase of the TanDEM-X, respectively. The comparison is performed using an opportunistic collocated acquisition over the Pentland Firth strait, known for its strong tidal stream. This comparison shows that the two SAR systems observe similar sea surface circulation patterns with high spatial correlation coefficient (r ~10.8). It is also shown that, provided a common calibration reference is available, the two independently derived RVL are quantitatively in good agreement with a negligible bias and reasonable RMSE (~10.3 m/s). This encourages use of the synergy between different C- and X-band SAR systems, measuring sea surface velocity.

In this paper near co-incidental Sentinel-1 C-band SAR imagery and Sentinel-3 SRAL Ku-band altimeter data are compared for their capabilities of sea ice type discrimination. Knowledge of sea ice type is important for climate research and safety in Arctic offshore operations.First-year ice is characterised by a low SAR backscatter intensity in both HH and HV polarisation compared to multi-year ice, while the altimeter waveform parameters show high pulse peakiness and peak power compared to multi-year ice.Thus SAR imagery and altimetry can principally discriminate different ice types. The complexity of the backscattered radar signal however impedes a clear separation of the two types for all cases. Cross comparison of the two sensors offers an opportunity of high resolution validation data, which is often lacking for sea ice studies.

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.

We investigated the correlation between backscatter and soil moisture considering precipitation and crop effects using dual polarized Sentinel-1A data. The analyzed data consist of a time-series of 38 Sentinel-1A GRD images acquired on a 12-days repeat cycle from July 2017 to October 2018 over Sapone in Burkina Faso. We show that the temporal change of backscatter corresponds to the soil moisture content rather than crops.

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.

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.

The EONav ship routing service uses near real time observations of ocean surface currents, waves, wind and sea ice conditions, in conjunction with forecasts from numerical weather and ocean models, to plan the optimal route for a vessel. Products from the Copernicus Marine Environment Monitoring Service (CMEMS) and several national weather services are used together with in-house products developed for Synthetic Aperture Radar (SAR) data from satellites such as Sentinel-1, Radarsat-2 and COSMO-SkyMed. A novel data selection algorithm automatically ranks the various data sets and combines them to provide the most reliable met-ocean information. A sail plan optimized e.g. to reduce fuel consumption is determined based on the met-ocean information and is communicated to the ships to assist captains in selecting the best route and speed pattern to their destination.

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.

In this paper we present an algorithm for sea ice concentration estimation in the Arctic from C-band dual polarization Sentinel-1A SAR images. The algorithm is based on spatial autocorrelation and utilizes an artificial neural network to map the image information to sea ice concentration. The cross-polarization channel facilitates the improvement of concentration estimates of images with high backscatter over open water in the normally used co-polarization channel. Ice charts from the Norwegian meteorological institute are used for the training of the network and as a reference. A mean absolute error of 14.55 (ice concentration is given in the range from 0 to 100) of a test data set consisting of 20 images underlines the capabilities of the proposed algorithm.

Estimation of surface currents still presents a challenge. In this work validates surface current estimates from the Maximum Cross Correlation (MCC) method, that uses spaceborne radiometer data, against ground-based retrievals from a High Frequency (HF) radar system. Moreover, these datasets have been compared with surface current data from two assimilated satellite products and four weather prediction models. The comparison shows large differences in the spatial resolution and the location of specific features. It is concluded that the variation of the observations may be due to the difference between the measuring or estimated method used in each case and the forces driving them.

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.

Detailed mapping of fast-ice deformation can be used to characterize the rheological behavior of fast ice and subsequently improve sea ice modeling. This study uses interferometric synthetic aperture radar to map fast-ice deformation with unprecedented spatial resolution (meter range) and sensitivity (cm-mm range). Two interferometric acquisitions, each with a temporal baseline of 24 h, were performed by the X-band SAR satellite constellation Cosmo-SkyMed over the northeast Bay of Bothnia in the middle of the 2012 ice season. The first interferogram shows deformation of the fast ice due to force from impinging drift ice, and the normal strain within the fast ice is measured. Complementary intensity correlation measurements reveal a slow movement of the drift ice toward the fast ice. The second interferogram exhibits a low fringe rate over the fast ice with fringes being aligned along the coastline. Deformation appears to be stronger around leads, skerries, and grounded ice ridges. It is also observed that the coherence images provide information that is complementary to the information in the backscatter images.

There are different parameters inherent to coastal areas that can affect the backscattering of the ocean surface detected by Synthetic Aperture Radar (SAR). The parameters include the influence of land, the influence of the SAR acquisition geometry, and the influence of backscattering features not directly related to wind variations. This work focuses on the study of the influence of those parameters for the performance of surface wind retrieval with C-band SAR data in coastal areas.

Areal matching by phase correlation and feature tracking are two complementary methods used to measure sea ice drift between synthetic aperture radar images. This paper evaluates a new algorithm that combines the two methods. Areal matching is improved by new methods to handle large motions and rotated ice. It is shown that areal rotation can be resolved using a frequency-domain approach. Image segmentation is a prerequisite for feature tracking and achieved by a new method that performs better than Otsu's method for two-component Gaussian mixture distributions. A circular weighted median filter is found to be suitable for the filtering of the motion field. The algorithm is evaluated through a thorough analysis of the response and sensitivity to various algorithm settings. The accuracy of the algorithm varies by up to 50% for one image pair within the studied range of parameter settings, thus indicating the need for a proper initialization of the algorithm.

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.

The purpose of this paper is to compare measurements of sea ice displacement from SAR imagery with ice floe drift trajectories modeled by the operational ocean circulation model HIROMB. The study examines the ice movement in the Fram Strait during a two-week period in April, 2011. The results indicate that the HIROMB model overestimates the drift speed by a factor 1 - 2.5, which may be attributed to an underestimated thickness of the ice. The model data also exhibit a directional offset in the positive clockwise direction of 10 - 30 degrees over the whole study region. The results of this study may be used to direct the model development and improve the model initialization.

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.

Two field experiments have been conducted in Sweden to allow an evaluation of the backscatter signatures of wind-thrown forest from L-band, C-band and X-band Synthetic Aperture Radar. When the trees are felled the backscattered signal from TerraSAR-X (X-band) increase with about 1.5 dB, while for ALOS PALSAR (L-band) a decrease with the same amount is observed. Radar images with fine spatial resolution also show shadowing effects that should be possible to use for identification of storm felled forest.

A new sea ice concentration algorithm has been developed for C-band synthetic aperture radar data. Detailed autocorrelation statistics are derived and adopted by the algorithm, and a neural network is utilized for training against 41 sea ice charts. The charts are produced by ice analysts at the Swedish Ice Service and cover the Baltic Sea. The classification of open water pixels is accurate to 94% on average, and the classification of sea ice pixels has an accuracy of 87%. This results in a root-mean-square error of 6.7 percentage points in estimating the sea ice concentration.

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.

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.

The study focuses on investigation and evaluation of wind-thrown forest mapping using satellite remotely sensed data from three synthetic aperture radar (SAR) sensors. The study is carried out at Remningstorp, a test site in the south of Sweden dominated by coniferous forest, where trees were manual felled to simulate wind-thrown forest. The satellite data consisted of time series of HH polarized SAR images acquired by the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR), Radarsat-2 (C-band) and TerraSAR-X (X-band). The results from visual interpretation of SAR images acquired before and after the simulated wind-throw together with corresponding ratio images show that ALOS PALSAR HH polarized intensity images are not able to detect wind-thrown forest, probably due to too coarse spatial resolution. In contrast, the wind-thrown forest is clearly visible in the Radarsat-2 and TerraSAR-X HH polarized images, implying that it may be possible to develop a new application using these SAR data for mapping of wind-thrown forests.

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.

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.

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.

Interferometric coherence from nine image pairs acquired by the Japanese satellite ALOS over a forest area in northern Sweden have been analyzed. Coherence levels for sparse and dense forest are compared. The results are in line with previous studies for JERS-1 and confirm that in most cases the temporal decorrelation is a severe problem for L-band SAR with repeat cycles on the order of six weeks. However, frozen conditions can give relatively high coherence for sparse forest and thereby allow good separation between dense and sparse forest.

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.

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.

This paper presents results from estimation of stem volume in boreal forest using backscatter and interferometric coherence from the L-band SAR on the Japanese Earth Resources Satellite (JERS-1). Five test areas in Siberia and one in Sweden have been included in the study. Data from 14 JERS-1 44-day pairs from Siberia and 12 pairs covering the Swedish test area have been evaluated. The best multitemporal combinations of the measurements give relative RMSE values ranging from 33% to 48%. When considering one of the two observables only, the lowest retrieval errors are obtained under frozen conditions when inverting the coherence and under unfrozen conditions when inverting the backscatter.

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.

In this paper retrieval of stem volume from JERS-1 repeat-pass interferometric coherence is demonstrated for five large forest areas in central Siberia. A method for multi-temporal combination of the retrieved stem volumes from several coherence images is applied. Compared to the best results from single coherence images the retrieval accuracy is in most cases significantly improved by the multi-temporal combination. The obtained multi-temporal relative retrieval accuracy is in the range 35 - 39% for four of five areas. The best RMSE is 54 m 3 /ha.

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.

To assess the possibility of using L-band synthetic aperture radar (SAR) backscatter for forest stem volume mapping in the boreal zone, a comparative analysis was carried out at test sites located in Sweden, Finland and Central Siberia from which an extensive set of Japanese Earth Resources Satellite (JERS-1) images and ground data was available. The backscatter showed clear seasonal dynamics, increasing by 3-4 dB in dense forests and 1-2 dB in sparse forests when going from frozen to unfrozen conditions. To retrieve stem volume a simple L-band Water Cloud-related scattering model was used. Model training performed well in all cases, the model parameters estimates being affected by weather conditions at acquisition and test site-specific forest stand structure. At each test site the retrieval performed best under unfrozen conditions and worst under frozen conditions. The highest retrieval accuracy was achieved at the small and intensively managed test site of Kattbole in Sweden with a 25% relative RMS error. For the other test sites the much larger retrieval error could be explained as a consequence of heterogeneities in the forest stand structure, as well as differences in the ground dielectric properties and inaccuracy in the ground data

Multitemporal radar data from the Japanese Earth Resources Satellite (JERS) satellite from the period 1993 to 1998 have been used to investigate if L-band interferometric coherence with a 44-day temporal baseline is suitable for estimations of growing-stock volume in boreal forest. Two forest regions north of Krasnoyarsk in Siberia have been used as test areas. Seasonal variations in the repeat-pass coherence have been studied, and a comparison with C-band coherence from the European Remote sensing Satellite 1 and 2 (ERS-1/2) tandem missions in 1997 and 1998 has been done. JERS coherence from the winter shows a clear correlation with the forest growing-stock volume. For the summer scenes, the spread in the values is too large to give reliable results. Acquisitions from the spring and fall show large problems with decorrelation caused by temporal changes. The results indicate potential of repeat-pass interferometric L-band coherence in winter, as will be provided by the forthcoming Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) to map growing-stock volume in Siberia and boreal forests.

This paper presents the first results from a study of multi-temporal JERS repeat pass coherence. Two test areas in a forest region north of Krasnoyarsk in Siberia have been used to investigate if L-band coherence with a 44-day temporal baseline can be used for estimations of growing stock volume in boreal forest. The available data show promising results for winter images, but for the summer scenes the standard deviations are too large to give reliable results. A comparison with ERS tandem coherence has also been done.