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We propose a novel method for quantifying and correcting phase errors in interferometric synthetic aperture radar (InSAR) data associated with signal decorrelation. This proposed method relates the observed phase nonclosure (referred to as the closure phase) of triplet combinations of any three individual SAR scenes to the decorrelative phase signal in individual interferograms (pairs of SAR scenes). A singular value decomposition (SVD) method is applied to solve the minimum-norm least-squares best fitting estimate of the decorrelation phase for any arbitrary collection of SAR images. This decorrelative phase is then removed from individual interferograms; these corrected interferograms can then be used with existing InSAR time-series analysis algorithms. We demonstrate this method on the Advanced Land Observation Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) scenes of a groundwater pumping subsidence feature in the Central Valley of California and briefly discuss potential future applications of this algorithm to study a variety of environmental and surface physical processes that contribute to InSAR signal decorrelation.

The accuracy of geophysical parameter estimation made with interferometric synthetic aperture radar (InSAR) time-series techniques can be improved with rapidly increasing available data volumes and with the development of noise covariance matrices applicable to joint analysis of networks of interferograms. In this article, we present a new decorrelation phase covariance model and discuss its role in noise reduction in unwrapped interferometric phase stacks. We demonstrate with an example in which we average unwrapped interferogram phase stacks that span over a transient event how a noise covariance model can aid in noise reduction. Our model suggests that, for rapidly decorrelating surfaces (i.e., surfaces with much shorter correlation time than SAR acquisition intervals), it is preferable to incorporate all available interferograms from long observation windows. For slowly decorrelating surfaces (i.e., surfaces with longer correlation time than SAR acquisition intervals), our model suggests that a small subset of interferometric pairs is sufficient. We validate our model and three existing models of decorrelation phase covariance matrices in both Cascadia, a region with heavy vegetation cover, and Death Valley, a desert region with C-band Sentinel-1 A observations. Our proposed model matches observations with the smallest average discrepancy between theory and observations.

Frequency-domain beamforming has become increasingly popular for fast processing of large synthetic aperture data in medical ultrasound. Here, we modify the Range Doppler Algorithm (RDA) to focus ultrasound signals from multistatic acquisitions. RDA, which was first proposed for fast beamforming of monostatic data in radar remote sensing, is suitable for fast processing of large datasets because all operations are done in one dimension at a time, allowing for an efficient and intuitive implementation. We demonstrate through simulation that multistatic RDA achieves similar image quality as traditionally used, multistatic delay-and-sum (DAS), while increasing the reconstruction speed by approximately a factor of three. We also show that the RDA and DAS images from the multistatic acquisition show reduced sidelobe levels compared to their counterparts from the monostatic acquisition. Demonstrated version of the multistatic RDA might be applicable beyond ultrasound medical imaging, such as for processing of synthetic aperture radar (SAR) data from satellite constellations.

The Permafrost Dynamics Observatory (PDO) combines L-band interferometric synthetic aperture radar (InSAR) and P-band polarimetric synthetic aperture radar (PolSAR) to simultaneously estimate the seasonal thaw depth and soil moisture profile of the active layer in permafrost regions. L-band InSAR can measure seasonal subsidence due to thawing of the active layer and P-band PolSAR backscatter is sensitive to subsurface soil moisture. A joint retrieval scheme is developed as both subsidence and soil moisture are essential to accurate active layer thickness (ALT) estimation. The PDO joint retrieval has been applied to airborne L- and P-band SAR data acquired over Arctic-boreal region during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign. In this paper, we describe the forward models and joint inversion used in the PDO retrievals and compare the results with in-situ ALT and soil moisture data estimated from ground-penetrating radar (GPR).

In permafrost regions, active layer thickness (ALT) observations measure the effects of climate change and predict hydrologic and elemental cycling. Often, ALT is measured through direct ground-based measurements. Recently, synthetic aperture radar (SAR) measurements from airborne platforms have emerged as a method for observing seasonal thaw subsidence, soil moisture, and ALT in permafrost regions. This study validates airborne SAR-derived ALT estimates in three regions of Alaska, USA using calibrated ground penetrating radar (GPR) geophysical data. The remotely sensed ALT estimates matched the field observations within uncertainty for 79% of locations. The average uncertainty for the GPR-derived ALT validation dataset was 0.14 m while the average uncertainty for the SAR-derived ALT in pixels coincident with GPR data was 0.19 m. In the region near Utqiaġvik, the remotely sensed ALT appeared slightly larger than field observations while in the Yukon-Kuskokwim Delta region, the remotely sensed ALT appeared slightly smaller than field observations. In the northern foothills of the Brooks Range, near Toolik Lake, there was minimal bias between the field data and remotely sensed estimates. These findings suggest that airborne SAR-derived ALT estimates compare well with in situ probing and GPR, making SAR an effective tool to monitor permafrost measurements.

Interferometric synthetic aperture radar (InSAR) has been used to quantify a range of surface and near surface physical properties in permafrost landscapes. Most previous InSAR studies have utilized spaceborne InSAR platforms, but InSAR datasets over permafrost landscapes collected from airborne platforms have been steadily growing in recent years. Most existing algorithms dedicated toward retrieval of permafrost physical properties were originally developed for spaceborne InSAR platforms. In this study, which is the first in a two part series, we introduce a series of calibration techniques developed to apply a novel joint retrieval algorithm for permafrost active layer thickness retrieval to an airborne InSAR dataset acquired in 2017 by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar over Alaska and Western Canada. We demonstrate how InSAR measurement uncertainties are mitigated by these calibration methods and quantify remaining measurement uncertainties with a novel method of modeling interferometric phase uncertainty using a Gaussian mixture model. Finally, we discuss the impact of native SAR resolution on InSAR measurements, the limitation of using few interferograms per retrieval, and the implications of our findings for cross‐comparison of airborne and spaceborne InSAR datasets acquired over Arctic regions underlain by permafrost., Key Points We develop and present several calibration and postprocessing methods for seasonal subsidence estimation from interferometric synthetic aperture radar deformationNovel methods for phase referencing and uncertainty quantification due to nonergodicity within the multilook window are proposedResidual sources of uncertainty in active layer thickness estimation are discussed and quantified

In addition to spaceborne Interferometric Synthetic Aperture Radar (InSAR), airborne data such as those obtained by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) have also been utilized to measure surface subsidence in permafrost areas in recent years. Motivated by the integration of multiplatform InSAR data, we generated two UAVSAR interferograms and one Advanced Land Observing Satellite (ALOS)‐2 L‐band interferogram over a permafrost area near Yellowknife, Canada, then compared the surface subsidence in the thaw seasons of 2017. The correlation coefficient and the root mean square error (RMSE) of subsidence difference are calculated to compare the airborne and spaceborne InSAR measurements. The results demonstrate that the two UAVSAR measurements are self‐consistent, with the correlation coefficient between independent airborne measurements ∼0.7. While the RMSE of the difference between surface subsidence measured by UAVSAR and ALOS2 is ∼2.0 cm, and the correlation coefficients are less than 0.41, that is, a noticeable deviation exists between the UAVSAR and ALOS2 results possibly due to different spatial resolution and the calibration processing of airborne and spaceborne InSAR data. In addition, both UAVSAR and ALOS2 interferograms show larger surface subsidence within taiga needleleaf forest regions than in regions of other biome types (including needleleaf forest, shrubland, and grassland). The results demonstrate that a scheme for the elimination of systematic differences needs to be developed before merging multisource InSAR results. This intercomparison will provide valuable insights for narrowing the gap between radar‐based measurements and planning the integration of airborne and satellite InSAR measurements in permafrost environments., Key Points We compare the seasonal subsidence derived from airborne and satellite InSAR measurementsTwo UAVSAR interferograms are self‐consistent while a significant deviation exists between the UAVSAR and ALOS2 resultsWe discuss the difference and the potential combination use of spaceborne and airborne InSAR to improve subsidence measurements over permafrost regions

Radar sounding reflectometry is a powerful method of inferring subsurface geophysical properties of planetary bodies. The upcoming Europa Clipper Mission will employ a dual frequency radar sounder to image and characterize Europa's subglacial environment. In terrestrial subglacial radar sounding, characteristic Doppler signatures of radar returns have been used to discriminate between different subglacial features (Peters et al., 2007). We propose that analogous techniques can be used in conjunction with traditional reflectometry methods to discriminate between different proposed models of subglacial and englacial water distribution within Europa's ice shell. We introduce the synthetic aperture radar (SAR) processing considerations that are relevant for such a technique, propose a simple hypothesis test for Doppler-based subglacial target discrimination, and briefly discuss the implications and applicability of such a technique for planetary radar sounding.

We use Ice, Cloud, and land Elevation Satellite 2 (ICESat‐2) laser altimetry crossovers and repeat tracks collected over the North Slope of Alaska to estimate ground surface‐height change due to the seasonal freezing and thawing of the active layer. We compare these measurements to a time series of surface deformation from Sentinel‐1 interferometric synthetic aperture radar (InSAR) and demonstrate agreement between these independent observations of surface deformation at broad spatial scales. We observe a relationship between ICESat‐2‐derived surface subsidence/uplift and changes in normalized accumulated degree days, which is consistent with the thermodynamically driven seasonal freezing and thawing of the active layer. Integrating ICESat‐2 crossover estimates of surface‐height change yields an annual time series of surface‐height change that is sensitive to changes in snow cover during spring and thawing of the active layer throughout spring and summer. Furthermore, this time series exhibits temporal correlation with independent reanalysis datasets of temperature and snow cover, as well as an InSAR‐derived time series. ICESat‐2‐derived surface‐height change estimates can be significantly affected by short length‐scale topographic gradients and changes in snow cover and snow depth. We discuss optimal strategies of post‐processing ICESat‐2 data for permafrost applications, as well as the future potential of joint ICESat‐2 and InSAR investigations of permafrost surface‐dynamics., Key Points ICESat‐2 altimetry can resolve surface subsidence that is related to changes in snow‐cover depth and seasonal thawing of the active layerICESat‐2 measurements of surface‐height change are affected by along‐track topographic gradients and complex surface roughnessComplementary ICESat‐2 and InSAR datasets can be jointly leveraged for future studies in periglacial environments

Seasonal subsidence measured by repeat-pass interferometric synthetic aperture radar (InSAR) can be used to infer the active layer thickness (ALT) in permafrost regions. The differential volume of soil water undergoing the phase change over the thaw season is one of the factors impacting the seasonal subsidence and is a function of both soil moisture profile and thaw depth. Without the information about soil moisture, this InSAR approach can have large biases in the ALT estimates when soil moisture profile is below saturation. Soil moisture and ALT can also be estimated from polarimetric synthetic aperture radar (PolSAR) backscatter observations but the sensing depth of the PolSAR approach is limited when deep ALT is present. In this paper, we integrated these two approaches and applied a joint retrieval method to estimate the soil moisture profiles and ALT from the L-band InSAR and P-band PolSAR data acquired over the Arctic-boreal region during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign.

Phase inconsistencies, or closure phase, in interferometric synthetic aperture radar (InSAR) images are associated with the lack of phase closure for any given triplet of SAR scenes. While nonzero phase closure is fundamentally due to signal decorrelation between SAR scenes within a triplet, there has been particular interest in relating closure phase to temporal variations in surface scattering properties, namely surface and near-subsurface soil moisture state. In this manuscript, we will provide a brief overview of closure phase, and propose a methodology for retrieving soil moisture information from closure phase observations. We will briefly discuss implementation of this methodology, and then discuss the degree to which the assumed interferometric soil moisture model, and the assumed statistics of suface scatterers impacts the sensitivity of closure phase observations to surface soil moisture.

Here we present a physics-based decorrelation phase covariance model and discuss its role in effective decorrelation noise reduction in interferogram stacks. We test our model in both Cascadia - a rapidly decorrelating region, and Death Valley - a slowly decorrelating region, with observations collected by Sentinel-1. We find that in Cascadia, including redundant interferograms in the stack reduces phase variance from 0.28 rad2 to 0.04 rad2, while in Death Valley, both redundant and independent interferogram stacking yield phase variances of 0.10 rad2. Both observations are consistent with predictions from our model. Comparing with three existing decorrelation phase covariance models, our proposed model matches observations with the smallest average discrepancy between theory and observations - 0.017 rad2 in Cascadia and 0.066 rad2 in Death Valley.

Software implementation of frequency-domain beamforming has become increasingly popular for fast imaging using ultrasound arrays. Stolt migration, which focuses aperture data in a 2-D frequency domain, has been adapted to ultrasound imaging, and can reduce beamforming time by up to two orders of magnitude compared to conventional delay-and-sum (DAS) beamforming. However, processing data in a 2-D frequency domain can require more memory to achieve sufficient accuracy and avoid interpolation errors. Here, we describe and apply the Range Doppler Algorithm (RDA) to focus ultrasound signals. RDA was first proposed for fast beamforming of monostatic data in radar remote sensing. RDA achieves image-reconstruction speed similar to Stolt migration, while all operations are done in one dimension at a time, allowing for efficient and intuitive implementation. Through simulation and phantom experiments, we show that RDA achieves similar image quality as DAS, while increasing the reconstruction speed by approximately a factor of 10.

We use repeat synthetic aperture radar (SAR) observations and complementary altimetry passes acquired by the Cassini spacecraft to study the scattering properties of Titan’s empty lake basins. The best-fit coefficients from fitting SAR data to a quasi-specular plus diffuse backscatter model suggest that the bright basin floors have a higher dielectric constant, but similar facet-scale rms surface facet slopes, to surrounding terrain. Waveform analysis of altimetry returns reveals that nadir backscatter returns from basin floors are greater than nadir backscatter returns from basin surroundings and have narrower pulse widths. This suggests that floor deposits are structurally distinct from their surroundings, consistent with the interpretation that some of these basins may be filled with evaporitic and/or sedimentary deposits. Basin floor deposits also express a larger diffuse component to their backscatter, which is likely due to variations in subsurface structure or an increase in roughness at the wavelength scale (Hayes, A.G. et al. [2008]. Geophys. Res. Lett. 35, 9). We generate a high-resolution altimetry radargram of the T30 altimetry pass over an empty lake basin, with which we place geometric constraints on the basin’s slopes, rim heights, and depth. Finally, the importance of these backscatter observations and geometric measurements for basin formation mechanisms is briefly discussed.

In cold regions where soils freeze and thaw annually, the ground surface deforms due to the density difference between groundwater and ground ice. Here we mapped thaw subsidence and frost heave signals over the Toolik Lake area on the North Slope of Alaska using 12 ALOS PALSAR Interferometric Synthetic Aperture Radar (InSAR) scenes (2006–2010). For the first time, we jointly analyzed InSAR observations with a large number of soil measurements collected within ~ 100 km of the Toolik Field Station. We found that the InSAR-observed deformation patterns are mainly related to soil water content and the seasonal active layer freeze-thaw (FT) cycle. We did not observe any substantial long-term subsidence trend outside the 2007 Anaktuvuk River Fire scar. This suggests that the magnitude of the maximum annual thaw subsidence did not change much outside the fire zone during the study period. The joint analysis of InSAR and field observations allows us to show that the amplitude of the seasonal thaw subsidence is proportional to the total amount of ice that has melted into liquid water at any given time. We note that topography influences the spatial distribution of soil water content, and the availability of soil water influences the type of vegetation that can grow. As a result, we found that the average seasonal thaw subsidence increases along a geomorphic-ecohydrologic transect with heath vegetation on the drier ridge-tops, tussock tundra on hillslopes, and sedge tundra at the wet lowland riparian zones. In addition, we detected a net uplift between late July and early September, mostly in the wetter riparian zone that experienced a larger seasonal thaw subsidence. Toolik Field Station in-situ records suggest that the air temperature fluctuated around or below freezing in early September during the ALOS PALSAR data acquisition times (at ~ 12 am local time). In this scenario, ice can be formed at the top of the soil, which leads to frost heave in saturated soils. Our results highlight how InSAR can improve our understanding of active layer freeze-thaw and water storage dynamics in permafrost environments.

International audience; Some of Titan's small northern hemisphere lakes show raised rampart features (which are distinct from raised rims), and appear as SAR-bright mound-like annuli extending away from the lake for up to tens of kilometers from the shoreline. We investigate the infrared and microwave characteristics of these features using Cassini Visual and Infrared Mapping Spectrometer (VIMS) and RADAR data. A spectral comparative analysis is performed among the lakes, their ramparts, and the surrounding regions. We overcome the profound difference in spatial resolution between VIMS and SAR data by using a method that provides overlays between the spectral images and SAR, thus enabling the correct selection of VIMS pixels. The surface properties of the selected areas are obtained using a radiative transfer analysis on the selected VIMS pixels, in addition to emissivity obtained from the RADAR in radiometry mode. Analysis of these combined and co-registered data provides constraints for the formation mechanism(s) of raised ramparts. The results show that the emissivity of the raised ramparts is close to that of Titan's labyrinthic terrains and to that of empty lake floors in the northern polar regions. This is confirmed by the VIMS analysis that also shows that the infrared spectral response of the raised ramparts is very similar to that of some empty lake floors. This suggests that both areas are made from or are covered by a similar material. In addition, two out of the eight lakes with raised ramparts show spectral differences at three specific wavelengths, 1.6, 2.0, and 5.0 μm, between the ramparts and the surrounding terrain. We hypothesize that this could be due to some component, or mixture of components in the ramparts that is less absorbent at these specific wavelengths, or it could be an effect of different grain sizes. These observations provide first insights into the possible mechanisms leading to the formation of the raised ramparts that are discussed here.

Frequency domain beamforming methods, such as Stolt migration, yield efficient and fast processing of ultrasound data. Stolt migration, by migrating the individual element data in a 2-D frequency domain, improves processing speed by up to two orders of magnitude compared to conventional delay-and-sum (DAS) beamforming. However, as commonly implemented, it relies on the assumption that the speed-of-sound is constant, and is unable to be applied with advanced beamforming techniques such as phase aberration correction. Here, we demonstrate another approach to frequency domain beamforming, using the range-Doppler method developed for synthetic aperture radar imaging. The range-Doppler method is similar in speed to Stolt migration, but because it involves only a 1-D Fourier transform in array dimension, it can account for speed-of-sound inhomogeneities. We demonstrate our method with simulated channel signals of point targets and diffuse scatterers, and find similar image quality (e.g., mainlobe width, sidelobe levels, and contrast-to-noise ratio) to DAS beamforming in noise-free conditions. We further analyze signals acquired through a near-field phase-screen and from multi-layered media by modifying Doppler processing to correct for phase aberration and to account for the local sound-speed differences, respectively.

The Yukon–Kuskokwim (YK) Delta is a region of discontinuous permafrost in the subarctic of southwestern Alaska. Many wildfires have occurred in the YK Delta between 1971–2015, impacting vegetation cover, surface soil moisture, and the active layer. Herein, we demonstrate that the remotely sensed active layer thickness (ReSALT) algorithm can resolve the post-fire active layer dynamics of tundra permafrost. We generated a stack of Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar interferograms over a study region in the YK Delta spanning 2007–2010. We applied ReSALT to this stack of interferograms to measure seasonal subsidence associated with the freezing and thawing of the active layer and subsidence trends associated with wildfire. We isolated two wildfire-induced subsidence signatures, associated with the active layer and the permafrost layer. We demonstrate that InSAR is sensitive to increases in active layer thickness following wildfire, which recovers to pre-fire values after approximately 25 years. Simultaneously, we show that fire gradually thins the permafrost layer by 4 m, which recovers to pre-fire thickness after 70 years.

The topography provided by altimetry, SAR-Topo, and stereo radargrammetry has opened new doors for Titan research by allowing for quantitative analysis of morphologic form. Using altimetry measurements, we show that Titan's Maria are consistent with an equipotential surface but that several filled lakes are found to be hundreds of meters above this sea level, suggesting that they exist in isolated or perched basins. Within a given drainage basin, empty lake floors are typically higher than the liquid elevation of nearby lakes/seas, suggesting local subsurface connectivity. The majority of Titan's lakes reside in topographically-closed, sharp-edged depressions whose planform curvature suggests lateral expansion through uniform scarp retreat. Many, but not all, empty lake basins exhibit flat floors and hectometer-scale raised rims that present a challenge to formation models. We conclude that dissolution erosion can best match the observed constraints, but that challenges remain in the interpretation of formation processes and materials.