Interferometric Synthetic Aperture Radar Pairs Research Articles

Snow Penetration Depth Inversion in Tibetan Plateau Based on Coherence Scattering Model with X-band Data

Abstract. The snow penetration depth is a necessary input parameter to accurately evaluate the thickness and vertical structure of snow layer, which is conducive to understanding the freeze-thaw process of ice and snow and predicting the change of ice and snow mass balance. Interferometric Synthetic Aperture Radar (InSAR) exhibits great potential in estimating snow penetration depth due to the emission of microwave band and the ability of operating under all-day and all-weather conditions. In previous studies, the penetration depth of snow was obtained based on InSAR coherence, but the external factors such as temperature, humidity, topography, dielectric constant and so on also affect the penetration dept. In order to extract the penetration depth in detail, this paper this paper adopts a uniform volume model as the basis, introduces two parameters describing the physical properties of snow: the volume ambiguity height and the volumetric decorrelation. Then, the magnitude of volumetric decorrelation is used to establish the internal relationship between the magnitude and the volume ambiguity height to estimate the snow penetration depth. In order to verify the effectiveness and feasibility of this method, a TSX/TDX InSAR pair covering southeast Tibetan Plateau in 2012 is applied to estimate the snow penetration depth. And results indicate that X-band penetration depths range mainly between −2.753 meters and −4.589 meters with an average value of −3.671 meters m and standard deviation of 0.918 meters in snowy regions on the plateau.

Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR)

Abstract. Snow is a critical water resource for the western United States and many regions across the globe. However, our ability to accurately measure and monitor changes in snow mass from satellite remote sensing, specifically its water equivalent, remains a challenge. To confront these challenges, NASA initiated the SnowEx program, a multiyear effort to address knowledge gaps in snow remote sensing. During SnowEx 2020, the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) team acquired an L-band interferometric synthetic aperture radar (InSAR) data time series to evaluate the capabilities and limitations of repeat-pass L-band InSAR for tracking changes in snow water equivalent (SWE). The goal was to develop a more comprehensive understanding of where and when L-band InSAR can provide SWE change estimates, allowing the snow community to leverage the upcoming NASA–ISRO (NASA–Indian Space Research Organization) SAR (NISAR) mission. Our study analyzed three InSAR image pairs from the Jemez Mountains, NM, between 12 and 26 February 2020. We developed a snow-focused multi-sensor method that uses UAVSAR InSAR data synergistically with optical fractional snow-covered area (fSCA) information. Combining these two remote sensing datasets allows for atmospheric correction and delineation of snow-covered pixels within the radar swath. For all InSAR pairs, we converted phase change values to SWE change estimates between the three acquisition dates. We then evaluated InSAR-derived retrievals using a combination of fSCA, snow pits, meteorological station data, in situ snow depth sensors, and ground-penetrating radar (GPR). The results of this study show that repeat-pass L-band InSAR is effective for estimating both snow accumulation and ablation with the proper measurement timing, reference phase, and snowpack conditions.

InSAR Atmospheric Delay Correction Model Integrated from Multi-Source Data Based on VCE

With the rapid development of interferometric synthetic aperture radar (InSAR) measurement technology, its measurement accuracy requirements are increasing. Atmospheric delay errors must be corrected, especially in the case of crustal deformation monitoring, the 20% variation of tropospheric water vapor among InSAR pairs generally produces range from 10 cm to 14 cm deformation errors. Such errors can be of the same magnitude as the annual changes in crustal deformation, or even greater, masking crustal deformation information and seriously affecting the results of crustal deformation monitoring. Therefore, in order to obtain a more accurate InSAR atmospheric delay correction model, this paper calculated and integrated atmospheric delays that were estimated by different sources, including the 37 pressure levels of the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF)) numerical weather prediction model, ECMWF Reanalysis v5 (ERA5), and Global Navigation Satellite System (GNSS) measurement data from the crustal movement observation network of China, based on the variance component estimation (VCE) weighting method. The results showed that the integrated model, based on the VCE method, is better than the generic atmospheric correction online service (GACOS) model for InSAR measuring of crustal deformation. The precision in monitoring crustal deformations was improved by approximately 5 mm, the correlation coefficient of atmospheric delay errors and crustal deformations improved from 0.287 to 0.347, and accuracy improved by approximately 25%. However, the improvement in accuracy was limited because of system error decoherence that was induced by atmospheric noise caused by abundant vegetation or snow cover. Therefore, in order to achieve more accurate results, we recommend the adoption of the multi-source integrated atmospheric delay correction model, based on the VCE method, for InSAR high-precision measuring of crustal deformation and seismic activities.

Sentinel-1 and RADARSAT Constellation Mission InSAR Assessment of Slope Movements in the Southern Interior of British Columbia, Canada

Landslides are the most common natural hazard in British Columbia. The province has recorded the largest number of historical landslide fatalities in Canada, and damage to infrastructure comes at a great cost. In order to understand the potential impacts of landslides, radar remote sensing has become a cost-effective method for detecting downslope movements. This study investigates downslope movements in the Southern Interior of British Columbia, Canada, with Sentinel-1 and RADARSAT Constellation Mission (RCM) interferometric synthetic aperture radar (InSAR) data. The 2-dimensional time-series analysis with Sentinel-1 ascending and descending InSAR pairs from October 2017 to June 2021 observed distinct earthflow movements of up to ~15 cm/year in the east–west direction. The Grinder Creek, Red Mountain, Yalakom River, and Retaskit Creek earthflows previously documented are still active, with east–west movements of ~30 cm over the past four years. New RCM data acquired from June 2020 to September 2020 with a 4-day revisit capability were compared to 12-day Sentinel-1 InSAR pairs. The 4-day RCM InSAR pairs at higher spatial resolution showed better performance by detecting relatively small-sized slope movements within a few hundred meters, which were not clearly observed by Sentinel-1. The temporal variabilities observed from the RCM InSAR showed great potential for observing detailed slope movements within a narrower time window.

Reconstructed Aeolian Surface Erosion in Southern Mongolia by Multi-Temporal InSAR Phase Coherence Analyses

The Gobi Desert in southern Mongolia has been identified as the strongest dust storm hot spot threatening public health and socio-economic activities in East Asian countries. Despite its significance, the complete mapping of the aeolian surface erosion in southern Mongolian remains unresolved because of the extensive region of interest that cannot be interpreted easily by conventional approaches. Therefore, in this study, we built a mapping scheme to define undergoing aeolian erosion and applied it over the southern Gobi Desert. The remote sensing approach applied here was based on an interferometric synthetic-aperture radar (InSAR) time series technique. A number of Sentinel-1 InSAR pairs that generate phase coherences for a certain period were synthesized via the means of principle component analysis (PCA) to extract the topographic persistence indicative of surface erosion rates. Validation analyses performed through inter-comparisons of phase coherence signals over landmark areas and residuals between global digital elevation models (DEMs) confirmed the reliability of outputs. The results revealed the geological lineaments in southern Mongolia confining sandy deposits and the sediment transportation pathways. Apparently, such bounded aeolian deposits and transportation mechanisms within geological structures have significantly contributed to dust generation in the Gobi Desert over southern Mongolia. In addition, this study demonstrated that the newly developed InSAR time series technique has great potential for identifying intensified land erosion and dust sources.

Time‐Series Analysis of Volume Change at Brady Hot Springs, Nevada, USA, Using Geodetic Data From 2003–2018

AbstractBrady Hot Springs geothermal field has exhibited subsidence, as measured by interferometric synthetic aperture radar (InSAR). Previous studies have examined both the temporal evolution of the deformation from 2004 through 2016 and the spatial extent of the deformation, directly relating the observed subsidence to volumetric changes below the surface. We extend the modeling at Brady to analyze a data set of interferometric pairs spanning from the end of 2003 through 2018. We examine spatial and temporal trends in the observed deformation by time‐series analysis of each of the 1,656 cubic voxels in a parameterized elastic dislocation model to identify areas where the subsurface volume changes as a function of time. Joint time‐series analysis of Global Positioning System and InSAR pairs confirm significant changes in rates of volume change during time intervals when well operations were varied. The rate of subsidence increases with increased injection, consistent with the identification of thermal contraction of the rock matrix as the dominant driving mechanism. Conversely, the modeled volume increases when pumping ceases, suggesting thermal expansion of the rock matrix.

DSM generation with bistatic TanDEM-X InSAR pairs and quality validation in inclined topographies and various land cover classes

In 2007, synthetic aperture radar (SAR) imaging was modified by TerraSAR-X (TSX); this second-generation SAR satellite offers up to 1 m of spatial resolution. The satellite is capable of interferometric SAR (InSAR), which permits the generation of digital surface models (DSMs). TSX was designed for monostatic InSAR imaging, but the potential for acquired DSMs is limited due to the disadvantages of repeat-pass InSAR geometry under the influence of temporal and related spectral decorrelations. In 2010, TanDEM-X (TDX) was launched to operate in a synchronized helix orbit with TSX to achieve high-quality DSMs covering almost the entire World in the basis of bistatic SAR imaging. In this paper, we focused on the DSM potential of TDX InSAR pairs in inclined topographies, and open, built-up, and forest land cover classes. A 5-m gridded TDX DSM was generated by interferometric processing and comprehensively analyzed by using model-to-model comparison approaches utilizing a reference airborne laser scanning (ALS) DSM. Absolute and relative vertical accuracies were estimated separately for all land cover classes using standard deviation and normalized median absolute deviation considering the influence of terrain tilt. Coherence with the reference DSM was determined by vertical profiles and frequency distribution graphics of height differences. Inaccurate regions were visualized by the generation of height error maps (HEMs). During the analysis, the qualities of the generated 5-m TSX DSM and a freely available 1-arcsecond (~ 30 m) Shuttle Radar Topography Mission (SRTM) DSM were validated and compared with TDX.

An improved method of three-dimensional displacement field generation in mining areas with a single InSAR pair

ABSTRACT An improved method combining a probability integral method and interferometric synthetic aperture radar (InSAR) for retrieving three-dimensional (3D) displacement field caused by coal mining is proposed. In this paper, fully considering dip angles of coal seams, we improved the method of obtaining 3D deformation using the linear relationship between horizontal displacement and surface tilt. Compared with the former method ignoring dip angles of coal seams, the improved method is more accurate in retrieving 3D displacement in mining areas. The improved method is first validated with a simulated coal seam with a dip angle of about 25°. The root-mean-square errors (RMSEs) in the Up-Down, East-West and South-North directions are 23.4, 33.0 and 8.0 mm, respectively. Finally, real SAR data are used to retrieve the 3D displacement fields of the Number 15235 working face of the Jiulong coal mine with a dip angle of about 13°. Due to the lack of field observations to evaluate horizontal displacement accuracy, Up-Down displacement is compared with leveling data. The RMSEs of the improved and former methods are 6.4 and 7.1 mm, respectively. The real data also indicate that the improved method is more accurate. In summary, the improved method is effective for obtaining a 3D displacement field, especially in the inclined coal seams mining area.

Deriving time-series three-dimensional displacements of mining areas from a single-geometry InSAR dataset

This paper presents a method for deriving time-series three-dimensional (3-D) displacements of mining areas from a single-geometry interferometric synthetic aperture radar (InSAR) dataset (hereafter referred to as the SGI-based method). This is mainly aimed at overcoming the limitation of the traditional multi-temporal InSAR techniques that require SAR data from at least three significantly different imaging geometries to fully retrieve time-series 3-D displacements of mining areas. The SGI-based method first generates the multi-temporal observations of the mining-induced vertical subsidence from the single-geometry InSAR data, using a previously developed method for retrieving 3-D mining-related displacements from a single InSAR pair (SIP). The weighted least-squares solutions of the time series of vertical subsidence are estimated from these generated multi-temporal observations of vertical subsidence. Finally, the time series of horizontal motions in the east and north directions are estimated using the proportional relationship between the horizontal motion and the subsidence gradient of the mining area, on the basis of the SGI-derived time series of vertical subsidence. Seven ascending ALOS PALSAR images from the Datong mining area of China were used to test the proposed SGI-based method. The results suggest that the SGI-based method is effective. The SGI-based method not only extends the SIP-based method to time-series 3-D displacement retrieval from a single-geometry InSAR dataset, but also limits the uncertainty propagation from InSAR-derived deformation to the estimated 3-D displacements.

URBAN MODELLING PERFORMANCE OF NEXT GENERATION SAR MISSIONS

Abstract. In synthetic aperture radar (SAR) technology, urban mapping and modelling have become possible with revolutionary missions TerraSAR-X (TSX) and Cosmo-SkyMed (CSK) since 2007. These satellites offer 1m spatial resolution in high-resolution spotlight imaging mode and capable for high quality digital surface model (DSM) acquisition for urban areas utilizing interferometric SAR (InSAR) technology. With the advantage of independent generation from seasonal weather conditions, TSX and CSK DSMs are much in demand by scientific users. The performance of SAR DSMs is influenced by the distortions such as layover, foreshortening, shadow and double-bounce depend up on imaging geometry. In this study, the potential of DSMs derived from convenient 1m high-resolution spotlight (HS) InSAR pairs of CSK and TSX is validated by model-to-model absolute and relative accuracy estimations in an urban area. For the verification, an airborne laser scanning (ALS) DSM of the study area was used as the reference model. Results demonstrated that TSX and CSK urban DSMs are compatible in open, built-up and forest land forms with the absolute accuracy of 8–10 m. The relative accuracies based on the coherence of neighbouring pixels are superior to absolute accuracies both for CSK and TSX.

Deriving Dynamic Subsidence of Coal Mining Areas Using InSAR and Logistic Model

The seasonal variation of land cover and the large deformation gradients in coal mining areas often give rise to severe temporal and geometrical decorrelation in interferometric synthetic aperture radar (InSAR) interferograms. Consequently, it is common that the available InSAR pairs do not cover the entire time period of SAR acquisitions, i.e., temporal gaps exist in the multi-temporal InSAR observations. In this case, it is very difficult to accurately estimate mining-induced dynamic subsidence using the traditional time-series InSAR techniques. In this investigation, we employ a logistic model which has been widely applied to describe mining-related dynamic subsidence, to bridge the temporal gaps in multi-temporal InSAR observations. More specifically, we first construct a functional relationship between the InSAR observations and the logistic model, and we then develop a method to estimate the model parameters of the logistic model from the InSAR observations with temporal gaps. Having obtained these model parameters, the dynamic subsidence can be estimated with the logistic model. Simulated and real data experiments in the Datong coal mining area, China, were carried out in this study, in order to test the proposed method. The results show that the maximum subsidence in the Datong coal mining area reached about 1.26 m between 1 July 2007 and 28 February 2009, and the accuracy of the estimated dynamic subsidence is about 0.017 m. Compared with the linear and cubic polynomial models of the traditional time-series InSAR techniques, the accuracy of dynamic subsidence derived by the logistic model is increased by about 50.0% and 45.2%, respectively.

Improving the quality of interferometric synthetic aperture radar digital elevation models through a segmentation-based coregistration approach

With the rapid development of remote sensing, multiple techniques are now capable of producing digital elevation models (DEMs), such as photogrammetry, Light Detection and Ranging (LiDAR), and interferometric synthetic aperture radar (InSAR). Satellite-derived InSAR DEMs are particularly attractive due to their advantages of large spatial extents, cost-effectiveness, and less dependence on the weather. However, several complex factors may limit the quality of derived DEMs, e.g., the inherited errors may be nonlinear and spatially variable over an entire InSAR pair scene. We propose a segmentation-based coregistration approach for generating accurate InSAR DEMs over large areas. Two matching algorithms, including least squares matching and iterative closest point, are integrated in this approach. Three Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) InSAR DEMs are evaluated, and their root mean square errors (RMSEs) improved from 17.87 to 9.98 m, 51.94 to 15.80 m, and 27.12 to 12.26 m. Compared to applying a single global matching strategy, the segmentation-based strategy further improved the RMSEs of the three DEMs by 3.27, 13.01, and 9.70 m, respectively. The results clearly demonstrate that the segmentation-based coregistration approach is capable of improving the geodetic quality of InSAR DEMs.

ALS model-based comparison of Cosmo-SkyMed and TerraSAR-X HS DSMs on varied land forms

Since 2007, the revolutionary X-band synthetic aperture radar (SAR) satellites Cosmo-SkyMed (CSK) and TerraSAR-X (TSX) have been collecting high-resolution images that are convenient for digital surface model (DSM) acquisition by the interferometric SAR (InSAR) technique. In this study, the potential of DSMs derived from CSK and TSX high-resolution spotlight (HS) images is thoroughly analysed regarding the basic accuracy metrics absolute vertical accuracy (AVA) and relative vertical accuracy (RVA). Utilising convenient InSAR pairs, 2 m gridded DSMs are generated in Istanbul and validated with model-based comparisons using an actual airborne laser scanning (ALS) DSM. Results show that CSK and TSX DSMs are compatible in open, built-up and forest land forms. The AVAs are between 8 m and 10 m based on standard deviation of height discrepancies against the ALS model. The RVAs, calculated by the coherence of neighbouring pixels for each DSM, are superior to AVAs for both CSK and TSX.

A method for monitoring hydrological conditions beneath herbaceous wetlands using multi-temporal ALOS PALSAR coherence data

Reed marshes, the world’s most widespread type of wetland vegetation, are undergoing major changes as a result of climate changes and human activities. The presence or absence of water in reed marshes has a significant impact on the whole ecosystem and remains a key indicator to identify the effective area of a wetland and help estimate the degree of degeneration. Past studies have demonstrated the use of interferometric synthetic aperture radar (InSAR) to map water-level changes for flooded reeds. However, the identification of the different hydrological states of reed marshes is often poorly understood. The analysis given in this paper shows that L-band interferometric coherence is very sensitive to the water surface conditions beneath reed marshes and so it can be used as classifier. A method based on a statistical analysis of the coherence distributions for wet and dry reeds using InSAR pairs was, therefore, investigated in this study. The experimental results were validated by in-situ data and showed very good agreement. This is the first time that information about the water cover under herbaceous wetlands has been derived using interferometric coherence values. This method can also effectively and easily be applied to monitor the hydrological conditions beneath other herbaceous wetlands.

A method for monitoring hydrological conditions beneath herbaceous wetlands using multi-temporal ALOS PALSAR coherence data

Abstract. Reed marshes, the world’s most widespread type of wetland vegetation, are undergoing major changes as a result of climate changes and human activities. The presence or absence of water in reed marshes has a significant impact on the whole ecosystem and remains a key indicator to identify the effective area of a wetland and help estimate the degree of degeneration. Past studies have demonstrated the use of interferometric synthetic aperture radar (InSAR) to map water-level changes for flooded reeds. However, the identification of the different hydrological states of reed marshes is often poorly understood. The analysis given in this paper shows that L-band interferometric coherence is very sensitive to the water surface conditions beneath reed marshes and so can be used as classifier. A method based on a statistical analysis of the coherence distributions for wet and dry reeds using InSAR pairs was, therefore, investigated in this study. The experimental results were validated by in-situ data and showed very good agreement. This is the first time that information about the water cover under herbaceous wetlands has been derived using interferometric coherence values. This method can also effectively and easily be applied to monitor the hydrological conditions beneath other herbaceous wetlands.

Retrieving three-dimensional displacement fields of mining areas from a single InSAR pair

This paper presents a novel method for retrieving three-dimensional (3-D) displacement fields of mining areas from a single interferometric synthetic aperture radar (InSAR) pair. This method fully exploits the mechanism of mining subsidence, specifically the proportional relationship between the horizontal displacement and horizontal gradient of vertical displacements caused by underground mining. This method overcomes the limitations of conventional InSAR techniques that can only measure one-dimensional (1-D) deformation of mining area along the radar line-of-sight direction. The proposed method is first validated with simulated 3-D displacement fields, which are obtained by the FLAC $$^{\mathrm{3D}}$$ software. The root mean square errors of the 3-D displacements retrieved by the proposed method are 13.7, 27.6 and 3.6 mm for the West–East, North–South, and Up–Down components, respectively. We then apply the proposed method to estimate the 3-D displacements of the Qianyingzi and the Xuzhou coal mines in China, respectively, each along with two Advanced Land Observing Satellite (ALOS) Phased Array Type L-band Synthetic Aperture Radar images. Results show that the estimated 3-D displacement is highly consistent with that of the field surveying. This demonstrates that the proposed method is an effective approach for retrieving 3-D mining displacement fields and will play an important role in mining-related hazard prevention and environment assessment under limited InSAR acquisitions.

Glacier Thickness Change Mapping Using InSAR Methodology

This letter presents a novel method for high-precision estimation of mountain glacier thickness change from the conventional interferometric synthetic aperture radar (InSAR) interferograms and multiaperture InSAR measurements. The method exploits the two components of displacement along the line of sight of radar beam and along track for deriving the glacier thickness change. To demonstrate the method, we estimate the glacier thickness change for the Dongkemadi Glacier in Tibet Plateau, China. The performance of this method is validated by field survey data. The results obtained with three InSAR pairs covering the Dongkemadi Glacier in the same seasons of three years show considerable spatial variability. The results in this study are, to our knowledge, the first ones with such a method, and they demonstrate the feasibility of the approach to obtain and analyze the mountain glacier thickness change.

Integrated analysis of PALSAR/Radarsat-1 InSAR and ENVISAT altimeter data for mapping of absolute water level changes in Louisiana wetlands

Interferometric Synthetic Aperture Radar (InSAR) has been used to detect relative water level changes in wetlands. We developed an innovative method to integrate InSAR and satellite radar altimetry for measuring absolute or geocentric water level changes and applied the methodology to remote areas of swamp forest in coastal Louisiana. Coherence analysis of InSAR pairs suggested that the HH polarization is preferred for this type of observation, and polarimetric analysis can help to identify double-bounce backscattering areas in the wetland. ENVISAT radar altimeter-measured 18-Hz (along-track sampling of 417 m) water level data processed with regional stackfile method have been used to provide vertical references for water bodies separated by levees. The high-resolution (~ 40 m) relative water changes measured from ALOS PALSAR L-band and Radarsat-1 C-band InSAR are then integrated with ENVISAT radar altimetry to obtain absolute water level. The resulting water level time series were validated with in situ gauge observations within the swamp forest. We anticipate that this new technique will allow retrospective reconstruction and concurrent monitoring of water conditions and flow dynamics in wetlands, especially those lacking gauge networks.