Search Results (54)

Accurate estimation of young forest height is essential for assessing the carbon sequestration potential of vast Siberian boreal forests recovering from wildfires. Satellite radar interferometry, particularly PolInSAR, is a promising tool for this task. However, its application in winter conditions and over sparse young forests remains underexplored. This study proposes a novel method for estimating the height of sparse young pine (Pinus sylvestris) stands using fully polarimetric bistatic TerraSAR-X/TanDEM-X data acquired in winter. The method is based on an analysis of the multimodal distribution of the unwrapped interferometric phase of the surface scattering component, which was isolated via PolInSAR decomposition. We hypothesize that the phase centers correspond to the snow-covered ground (located between tree groups) and the rough surface formed by the upper layer of branches and needles (of the tree groups). The results demonstrate that the difference between the dominant modes of the surface scattering phase distribution correlates with the height of young trees. However, the measurable height difference is limited by the interferometric height of ambiguity. Furthermore, a temporal analysis of the phase and meteorological data revealed a strong correlation between sudden phase shifts and daytime temperature rises around 0 °C. This is interpreted as the formation of a layered snowpack structure with a dense ice crust. This study confirms the potential of X-band PolInSAR for monitoring the structure of young Siberian forests in winter but also highlights a significant limitation: the critical impact of snowpack metamorphism, particularly melt-freeze cycles, on the interferometric phase. The proposed method is only applicable to certain forest regeneration stages where tree height does not exceed the ambiguity limit and snow conditions are stable. Full article

The glaciers of the Nyainqêntanglha Mountains serve not only as sensitive indicators of climate change, but also as important water sources for downstream rivers. In this study, we quantitatively analyzed the glacier mass balance of the entirety of the Nyainqêntanglha Mountains using TerraSAR-X/TanDEM-X and SRTM DEM data and compared the mass balance between glaciers in the western and eastern parts of the range, revealing the spatial heterogeneity in glacier mass loss. Finally, data from nine meteorological stations in the region were used to investigate regional climate changes and their impacts on glacier variation. The results show that from 2000 to 2013, the average annual glacier surface elevation in the Nyainqêntanglha Mountains decreased by 0.48 ± 0.02 m, with a mass balance of −0.55 ± 0.04 m water equivalent per year. The majority of glacier mass loss occurred in areas with slopes between 40° and 70°. The mass loss of clean glaciers in the eastern region was higher than that in the western region, whereas at high elevations, the mass loss of debris-covered glaciers was more severe in the western region than in the east. Overall, the debris cover on the glaciers has not yet reached the critical thickness required to effectively mitigate melting, and mass input in the accumulation zones is uneven, scattered, and limited, resulting in weak replenishment capacity. Against the backdrop of continued warming, regional precipitation is insufficient to provide the necessary accumulation, making glaciers more sensitive to rising temperatures. This study not only reveals pronounced spatial differences in glacier mass loss and their climatic drivers but also provides new scientific evidence for understanding water resource security, hydrological responses and potential snow avalanche hazards on the Tibetan Plateau, offering important implications for regional water management and future climate adaptation. Full article

Forests provide habitat for diverse species and play a key role in mitigating climate change. Remote sensing enables efficient monitoring of many forest attributes across vast areas, thus supporting effective and efficient management strategies. This study aimed to identify an effective combination of remote sensing sensors for estimating biophysical variables in Mediterranean and temperate forests that can be easily translated into an operational context. Aboveground biomass (AGB), canopy height (CH), and forest canopy cover (FCC) were estimated using a combination of optical (Sentinel-2, Landsat) and radar sensors (Sentinel-1 and TerraSAR-X/TanDEM-X), along with records of past forest disturbances and topography-related variables. As a reference, lidar-derived AGB, CH, and FCC were used. Model performance was assessed not only with standard approaches such as out-of-bag sampling but also with completely independent lidar-derived reference datasets, thus enabling evaluation of the model’s temporal inference capacity. In Mediterranean forests, models based on optical imagery outperformed the radar-enhanced models when estimating FCC and CH, with elevation and spectral indices being key predictors of forest structure. In contrast, in denser temperate forests, radar data (especially X-band relative heights) were crucial for estimating CH and AGB. Incorporating past disturbance data further improved model accuracy in these denser ecosystems. Overall, this study underscores the value of integrating multi-source remote sensing data while highlighting the limitations of temporal extrapolation. The presented methodology can be adapted to enhance forest variable estimation across many forest ecosystems. Full article

In this study, we investigate the usefulness of the spectral whitening procedure, devised by one of the authors as a preprocessing stage of envelope-detected single-look synthetic aperture radar (SAR) images, in application contexts where phase information is relevant. In the first experiment, each of the raw datasets of an interferometric pair of COSMO-SkyMed images, representing industrial buildings amidst vegetated areas, was individually (1) synthesized by the SAR processor without Fourier-domain Hamming windowing; (2) synthesized with Hamming windowing, used to improve the focalization of targets, with the drawback of spatially correlating speckle; and (3) processed for the whitening of complex speckle, using the data obtained in (2). The interferograms were produced in the three cases, and interferometric coherence and phase maps were calculated through 3 × 3 boxcar filtering. In (1), coherence is low on vegetation; the presence of high sidelobes in the system’s point-spread function (PSF) causes the spread of areas featuring high backscattering. In (2), point targets and buildings are better defined, thanks to the sidelobe suppression achieved by the frequency windowing, but the background coherence is abnormally increased because of the spatial correlation introduced by the Hamming window. Case (3) is the most favorable because the whitening operation results in low coherence in vegetation and high coherence in buildings, where the effects of windowing are preserved. An analysis of the phase map reveals that (3) is likely to be facilitated also in terms of unwrapping. Results are presented on a TerraSAR-X/TanDEM-X (TSX-TDX) image pair by processing the interferograms of original and whitened data using a non-local filter. The main results are as follows: (1) with autocorrelated speckle, the estimation error of coherence may attain 16% and inversely depends on the heterogeneity of the scene; and (2) the cleanness and accuracy of the phase are increased by the preliminary whitening stage, as witnessed by the number of residues, reduced by 24%. Benefits are also expected not only for differential InSAR (DInSAR) but also for any coherent analysis and processing carried out performed on SLC data. Full article

The Arctic is experiencing the greatest increase in air temperature on Earth. This significant climatic change is leading to a significant positive trend of increasing wave heights and greater coastal erosion. This in turn effects local economies and ecosystems. Increasing wave energy is one of the main drivers of this alarming trend. However, the data on spatial and temporal patterns of wave heights in the Arctic are either coarse, interpolated or limited to point measurements. The aim of this study is to overcome this shortcoming by using remote sensing data. In this study, the Synthetic Aperture Radar (SAR) satellite TerraSAR-X (TS-X) and TanDEM-X (TD-X) imagery are used to obtain sea state information with a high spatial resolution in Arctic nearshore waters in the Canadian Beaufort Sea. From the entire archive of the TS-X/TD-X StripMap mode with coverage around 30 km × 50 km acquired between 2009 and 2020 around Herschel Island, Qikiqtaruk (HIQ), all the ice-free scenes were processed. The resulting dataset of 175 collocated scenes was used to map the significant wave height ($H_s$) and to link spatial and temporal patterns to local coastal processes. Sea state parameters are estimated in raster format with a 600 m step using the empirical algorithm CWAVE_EX. The statistics of the $H_s$ were aggregated according to spatial variability, seasonality and wind conditions. The results show that the spatial wave climate is clearly related to the dominant wind regime and seasonality. For instance, the aggregation of all the scenes recorded in July between 2009 and 2020 results in an average of 0.82 m $H_s$, while in October the average $H_s$ is almost 0.40 m higher. The analysis by wind direction shows that fetch length and wind speed are likely the most important variables influencing the spatial variability. A larger fetch under NW conditions results in a mean wave height of 0.92 m, while waves generated under ESE conditions are lower at 0.81 m on average. Full article

Forest height plays a crucial role in various fields, such as forest ecology, resource management, natural disaster management, and environmental protection. In order to obtain accurate and efficient measurements of forest height over large areas, in this study, Terra Synthetic Aperture Radar-X and the TerraSAR-X Add-on for Digital Elevation Measurement (TerraSAR-X/TanDEM-X), Sentinel-2A, and Shuttle Radar Topography Mission (SRTM) data were used, and various feature combinations were established in conjunction with measurements from Light Detection and Ranging (LiDAR). Classification and regression tree (CART), gradient-boosting decision tree (GBDT), random forest (RF), and support vector machine (SVM) algorithms were employed to estimate forest height in the study area. Independent validation on the basis of LiDAR forest height samples showed the following results: (1) Regarding feature combinations, the combination of coherence and decorrelation of volume scattering provided by TerraSAR-X/TanDEM-X data outperformed the combination of backscatter coefficient and local incidence angle, as well as the combination of coherence, decorrelation of volume scattering, backscatter coefficient, and local incidence angle. The best results (R² = 0.67, RMSE = 2.89 m) were achieved with the combination of coherence and decorrelation of volume scattering using the GBDT and RF algorithms. (2) In terms of machine learning methods, the GBDT algorithm proved suitable for estimating forest height. The most effective approach for forest height mapping involved combining the GBDT algorithm with coherence, decorrelation of volume scattering, and a small amount of LiDAR forest height data, used as training data. Full article

Glaciers experience periodic variations in flow velocity called surges, each of which influences the glacier’s characteristics and the occurrence of downstream disasters (e.g., ice-dammed lake outburst floods). The Karakoram region contains many surging glaciers, yet there are few comprehensive studies of multiple surge cycles. In this work, Landsat, topographic map, Shuttle Radar Topography Mission (SRTM), TerraSAR-X/TanDEM-X, ITS_LIVE, and Sentinel-1 glacier velocity data were used to systematically analyze the characteristics of Kyagar Glacier since the 1970s. Three surging events were identified, with active phases in 1975–1978, 1995–1997, and 2014–2016. The timing of these surges was similar, with a cycle of 19–20 years, an active phase of 3–4 years, and a quiescent phase of 16–17 years. During the quiescent phase, a large amount of ice accumulates in the lower part of the accumulation zone, and the terminal of the tongue thins significantly. According to the most recent surge event (2014–2016), glacier flow accelerated suddenly in the active phase and reached a maximum velocity of 2 ± 0.08 m d⁻¹. Then, the glacier terminal thickened sharply, the reservoir zone thinned by 12 ± 0.2 m, and the terminal receiving zone thickened by 28 ± 0.2 m. The glacier may have entered a quiescent phase after July 2016. The glacier surge causes a large amount of material to transfer from upstream to downstream, forming an ice dam and creating conditions for a glacial lake outburst flood (GLOF). At the termination of the active phase, the subglacial drainage channel became effective, triggering the GLOF. For a period of the quiescent phase, the glacier ablation intensifies and the GLOF repeats constantly. One surge caused 7–8 GLOFs, and then a continuous reduction in the ice dam elevation. Eventually, the ice dam disappeared, and the GLOF no longer continued before the next glacier-surging event. Full article

In this study, we investigated the quality of Interferometric Synthetic Aperture Radar (InSAR) data to measure surface displacements in upstate New York, an area with dense vegetation, snowy winters, and strong seasonal signals. We used data from the German Space Agency’s TerraSAR-X and TanDEM-X satellites (X-band, 3.1 cm radar wavelength) as well as the European Space Agency’s Sentinel-1 satellite (C-band, 5.6 cm radar wavelength); both datasets covered a ~3-year time period from 2018 to 2021. Using persistent scatterer interferometry (PSI), we were able to observe several deforming features in the region with sub-centimeter/year deformation rates. We also examined a version of the X-band data that we spatially averaged to the same pixel size as the Sentinel-1 imagery in order to separate out the effects of wavelength and pixel size on PSI accuracy and coverage. Overall, the largest number of stable PS points was found in the full-resolution X-band data, which was followed by the C-band data and then by the downsampled X-band data. Our analysis also included a subset of snow-free imagery so that we could assess the effect that snow-covered images had on the distribution and accuracy of PS points and the resulting time series. This analysis revealed that PS populations increased by 50–60% for the snow-free data when compared with analyses using the full datasets. The average deformation rates inferred from the time series generated using only snow-free images were nearly identical to those estimated from the full time series. We assessed the accuracy of the inferred rates through comparisons between the results of different datasets and with limited ground survey data. We found that all of the inferred deformation rates from each of the datasets agreed with in situ measurements in an area of known ground subsidence above an underground salt mine in Lansing, NY. The S1 datasets, however, had higher levels of noise. Full article

Climate change in the Arctic region is more significant than in other parts of our planet. One of the manifestations of these changes is crater creation with blowouts of a gas, ice and frozen soil mixture. In this context, dynamics studies of long-term heaving mounds that turn into craters as a result are relevant. A workflow for detecting and assessing anomalous dynamics of heaving mounds in the Arctic regions is proposed. Areas with anomalous increase of ALOS-2 PALSAR-2 synthetic aperture radar (SAR) backscattering intensity are detected in the first stage. These increases take place due to sudden changes in local terrain slopes when the scattering surface (mound slope) turns toward the radar. Radar backscattering intensity also rises due to depolarization at newly formed frost cracks. Validation of the detected anomaly is carried out at the second stage through a comparison of multi-temporal digital elevation models obtained from bistatic radar interferometry TerraSAR-X/TanDEM-X data. At the final stage, the deformations are assessed within the detected areas using differential SAR interferometry (DInSAR) technique by ALOS-2 PALSAR-2 data. The magnitude of the heaving along the line of sight (LOS) was 22–24 cm in the period from January 2019 to January 2020. In general, effectiveness for detecting the perennial heaving mounds and the rate assessment of their increase were demonstrated in the suggested workflow. Full article

The hybrid interferometric synthetic aperture radar system is a combination of an along-track configuration and cross-track configuration. Based on linear ocean wave theory, an ocean wave inversion algorithm for a hybrid interferometric synthetic aperture radar system is proposed in this work. Using the interferometric synthetic aperture radar images acquired by the TerraSAR-X and TanDEM-X satellites and the interferometric synthetic aperture radar images acquired by an airborne interferometric radar altimeter with a certain degree of squint, the profile of ocean waves and the corresponding orbital velocities were retrieved by combining the new inversion algorithm with the cross-spectra. Meanwhile, key parameters of ocean waves, such as the significant wave height, significant wave orbital velocity, propagation direction, and wavelength of the dominant waves, were also extracted from the ocean wave spectra retrieved in this study. In order to evaluate the reliability of the new inversion algorithm, the retrieved significant wave heights were compared with those provided by the European Centre for Medium-Range Weather Forecasts and measured by a Global Navigation Satellite System buoy. The results showed that for the ocean waves retrieved from the spaceborne hybrid interferometric synthetic aperture radar images, the differences between the retrieved significant wave heights of the four subareas selected in this paper and those provided by European Centre for Medium-Range Weather Forecasts were approximately 0.01, –0.17, –0.55, and –0.37 m, respectively, and for the ocean waves retrieved from the airborne interferometric radar altimeter images, the differences between the retrieved significant wave heights corresponding to the M920 and M3120 images used in this paper and those measured by the Global Navigation Satellite System buoy were approximately –0.05 and –0.09, respectively. Therefore, the method proposed in this work could retrieve the ocean wave spectra well when the velocity bunching had a small influence; however, as the nonlinear influence of the velocity bunching increased, the difference between the significant wave heights retrieved using this method and provided by the European Centre for Medium-Range Weather Forecasts also increased. Full article

Digital elevation models (DEMs) are widely used across a range of fields. Several open-source global DEMs have been released, including the advanced land observing satellite world 3D 30 m DEM (AW3D30DEM), advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM), shuttle radar topography mission DEM (SRTMDEM), and TerraSAR-X for digital elevation measurement (TanDEM-X). ASTER and SRTM are the most widely used DEMs, while the newer models AW3D30DEM and TanDEM-X are becoming increasingly popular. Many studies have evaluated the qualities of these DEMs; however, few multi-regional studies have been conducted in China. To comprehensively and systematically evaluate the qualities of these DEMs in China, the vertical accuracies of AW3D, ASTER, STRM (all 30 m), and TanDEM-X (90 m) were tested across 16 regions in China. Using high-precision global positioning system control points for reference, error values were determined by subtracting these reference values from corresponding global DEM elevation values. As the study only covered flat areas (slope < 5°), slope was treated as a controlled variable. After assessing the impacts of the slope aspect and land cover type, variations in vertical accuracy were examined with respect to longitude and latitude. Overall, TanDEM-X exhibited the highest stability and accuracy, AW3D30 and SRTM also performed well, while ASTER exhibited the worst accuracy. The DEMs showed relationships with the slope aspect and land cover type, assuming that slope had no influence on vertical accuracy. In general, vertical accuracy in high latitudes was slightly better than that in low latitudes, and no evident variations were observed with respect to longitude. This study is the first to conduct DEM analysis across many regions in China from open sources. Since most of the users rely on public domain DEM datasets, this work contributes to their analysis in academic and engineering fields. Full article

Phase unwrapping (PU) is a key program in data processing in the interferometric synthetic aperture radar (InSAR) technique, and its accuracy directly affects the quality of final SAR data products. However, PU in regions with large gradient changes and high noise has always been a difficult problem. To overcome the limitation, this article proposes an adaptive square-root unscented Kalman filter PU method. Specifically, a modified phase gradient estimation (PGE) algorithm is proposed, in which a Butterworth low-pass filter is embedded, and the PGE window can be adaptively adjusted according to phase root-mean-square errors of pixels. Furthermore, the outliers of the PGE results are detected and revised to obtain high-precision vertical and horizontal phase gradients. Finally, the unwrapped phase is calculated by the adaptive square-root unscented Kalman filter method. To the best of our knowledge, this article is the first to combine the modified PGE with an adaptive square-root unscented Kalman filter for PU. Two sets of simulated data and a set of TerraSAR-X/TanDEM-X real data were used for experimental verification. The experimental results demonstrated that the various improvement measures proposed in this article were effective. Additionally, compared with the minimum-cost flow algorithm (MCF), statistical-cost network-flow algorithm (SNAPHU) and unscented Kalman filter PU (UKFPU), the proposed method had better accuracy and model robustness. Full article

The TerraSAR-X add-on for Digital Elevation Measurements (TanDEM-X) bistatic system provides high-resolution and high-quality interferometric data for global topographic measurement. Since the twin TanDEM-X satellites fly in a close helix formation, they can acquire approximately simultaneous synthetic aperture radar (SAR) images, so that temporal decorrelation and atmospheric delay can be ignored. Consequently, the orbital error becomes the most significant error limiting high-resolution SAR interferometry (InSAR) applications, such as the high-precision digital elevation model (DEM) reconstruction, subway and highway deformation monitoring, landslide monitoring and sub-canopy topography inversion. For rugged mountainous areas, in particular, it is difficult to estimate and correct the orbital phase error in TanDEM-X bistatic InSAR. Based on the rigorous InSAR geometric relationship, the orbital phase error can be attributed to the baseline errors (BEs) after fixing the positions of the master SAR sensor and the targets on the ground surface. For the constraint of the targets at a study scene, the freely released TanDEM-X DEM can be used, due to its consistency with the TanDEM-X bistatic InSAR-measured height. As a result, a parameterized model for the orbital phase error estimation is proposed in this paper. In high-resolution and high-precision TanDEM-X bistatic InSAR processing, due to the limited precision of the navigation systems and the uneven baseline changes caused by the helix formation, the BEs are time-varying in most cases. The parameterized model is thus built and estimated along each range line. To validate the proposed method, two mountainous test sites located in China (i.e., Fuping in Shanxi province and Hetang in Hunan province) were selected. The obtained results show that the orbital phase errors of the bistatic interferograms over the two test sites are well estimated. Compared with the widely applied polynomial model, the residual phase corrected by the proposed method contains little undesirable topography-dependent phase error, and avoids unexpected height errors ranging about from −6 m to 3 m for the Fuping test site and from −10 m to 8 m for the Hetang test site. Furthermore, some fine details, such as ridges and valleys, can be clearly identified after the correction. In addition, the two components of the orbital phase error, i.e., the residual flat-earth phase error and the topographic phase error caused by orbital error, are separated and quantified based on the parameterized expression. These demonstrate that the proposed method can be used to accurately estimate and mitigate the orbital phase error in TanDEM-X bistatic InSAR data, which increases the feasibility of reconstructing high-resolution and high-precision DEM. The rigorous geometric constraint, the refinement of the initial baseline parameters, and the assessment for height errors based on the estimated BEs are investigated in the discussion section of this paper. Full article

The interferometric synthetic aperture radar (InSAR) data set, acquired by the TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) mission (TDM), represents a unique data source to derive geo-information products at a global scale. The complete Earth’s landmasses have been surveyed at least twice during the mission bistatic operation, which started at the end of 2010. Examples of the delivered global products are the TanDEM-X digital elevation model (DEM) (at a final independent posting of 12 m × 12 m) or the TanDEM-X global Forest/Non-Forest (FNF) map. The need for a reliable water product from TanDEM-X data was dictated by the limited accuracy and difficulty of use of the TDX Water Indication Mask (WAM), delivered as by-product of the global DEM, which jeopardizes its use for scientific applications, as well. Similarly as it has been done for the generation of the FNF map; in this work, we utilize the global data set of TanDEM-X quicklook images at 50 m × 50 m resolution, acquired between 2011 and 2016, to derive a new global water body layer (WBL), covering a range from −60${}^{\circ }$ to +90${}^{\circ }$ latitudes. The bistatic interferometric coherence is used as the primary input feature for performing water detection. We classify water surfaces in single TanDEM-X images, by considering the system’s geometric configuration and exploiting a watershed-based segmentation algorithm. Subsequently, single overlapping acquisitions are mosaicked together in a two-step logically weighting process to derive the global TDM WBL product, which comprises a binary averaged water/non-water layer as well as a permanent/temporary water indication layer. The accuracy of the new TDM WBL has been assessed over Europe, through a comparison with the Copernicus water and wetness layer, provided by the European Space Agency (ESA), at a 20 m × 20 m resolution. The F-score ranges from 83%, when considering all geocells (of 1${}^{\circ }$ latitudes × 1${}^{\circ }$ longitudes) over Europe, up to 93%, when considering only the geocells with a water content higher than 1%. At global scale, the quality of the product has been evaluated, by intercomparison, with other existing global water maps, resulting in an overall agreement that often exceeds 85% (F-score) when the content in the geocell is higher than 1%. The global TDM WBL presented in this study will be made available to the scientific community for free download and usage. Full article

Due to the remote location and the extreme climate, monitoring stations in Arctic rivers such as Lena in Siberia have been decreasing through time. Every year, after a long harsh winter, the accumulated snow on the Lena watershed melts, leading to the major annual spring flood event causing heavy transport of sediments, organic carbon, and trace metals, both into as well as within the delta. This study aims to analyze the hydrodynamic processes of the spring flood taking place every year in the Lena Delta. Thus, a combination of remote sensing techniques and hydrodynamic modeling methodologies is used to overcome limitations caused by missing ground-truth data. As a test site for this feasibility study, the outlet of the Lena River to its delta was selected. Lena Delta is an extensive wetland spanning from northeast Siberia into the Arctic Ocean. Spaceborne Synthetic Aperture Radar (SAR) data of the TerraSAR-X/TanDEM-X satellite mission served as input for the hydrodynamic modeling software HEC-RAS. The model resulted in inundation areas, flood depths, and flow velocities. The model accuracy assessed by comparing the multi-temporal modeled inundation areas with the satellite-derived inundation areas ranged between 65 and 95%, with kappa coefficients ranging between 0.78 and 0.97, showing moderate to almost perfect levels of agreement between the two inundation boundaries. Modeling results of high flow discharges show a better agreement with the satellite-derived inundation areas compared to that of lower flow discharges. Overall, the remote-sensing-based hydrodynamic modeling succeeded in indicating the increase and decrease in the inundation areas, flood depths, and flow velocities during the annual flood events. Full article