Radar Interferometry Technique Research Articles

Interview

Prof. Zhike Peng from Shanghai Jiao Tong University, talks to Electronics Letters about the background to his paper ‘Static clutter elimination for FMCW radar displacement measurement based on phasor offset compensation’, page 1491. Prof. Zhike Peng Currently, part of my research focuses on signal processing, microwave detection, and micro-Doppler analysis, in particular for microwave/RF radar vibration monitoring, biomedical, and some other industrial applications. To realise non-contact vibration and movement monitoring, we found microwave radar to be a good approach, as it is low-cost and has high robustness against harsh environments. Fortunately, benefiting from the technical advances in high-frequency printed circuit board and hardware miniaturisation technology, microwave radar modules are widely used in various applications. Therefore, we try to use microwave radar, as an effective short-range sensor to perform non-contact displacement tracking. Specifically, we use frequency-modulated continuous-wave (FMCW) radar to measure the displacement variation in vibration motion. Currently, using phase-based radar interferometry technique, FMCW radar has excellent capacity to measure small displacement variation. However, since the radar antenna has a finite radiation beam-width, i.e. it cannot be a point, all targets within the radar radiation coverage reflect echoes and the radar baseband signal is the sum of multiple components. Generally, FMCW radar can isolate different targets with a different range bin, but struggles to isolate components generated by targets in the same bin. Reflections from stationary objects (i.e. static clutter) near the desired target interfere with the wanted signals backscattering from the moving scatterers at the same range, causing the estimated displacement time series to be smaller than the truth. When the stationary object and the desired target have comparable reflective performance, the static clutter interference has a significant impact on the estimation accuracy. In our Letter, a post-processing procedure based on phasor offset compensation (POC) is proposed to eliminate the static clutter interference. It can be implemented easily by using an updated signal processing algorithm and achieves accurate displacement measurement. Previously, for this problem existing works mainly focus on the hardware side, such as installing a strong reflection point, or using frequency-shift transponders, which increase hardware complexity and is limited in real-life applications. Comparatively, our POC technique is a novel way to solve the static clutter interference problem from a signal processing side. This work can be directly applied in FMCW radar displacement measurement, e.g. vibration monitoring, large structural health monitoring, slow movement detection and vital sign detection. In the long run, the POC technique can be extended in other phase-based measurement system for a wide variety of applications. Currently, one portion of our research group is working on radar signal processing algorithms to achieve good performance in related applications. Specifically, we are now working on the research of non-contact vibration monitoring and structural health monitoring based on FMCW radar, and micro-Doppler analysis for pattern recognition. In the near future, we would like to extend our research in radar imaging and environmental perception. Then, we would like to investigate the information fusion technique combined with the camera, to obtain better and more intelligent environmental imaging and recognition. In the next 10 years, we would like to see more integrated software defined radar developing platforms and advanced radar signal processing algorithms for a variety of applications. Moreover, we expect to see intelligent radar detection systems with multiple type radars. Various sensors have their own advantages and drawbacks, therefore we need to see intelligent information fusion techniques to achieve better environmental imaging and recognition. This includes object recognition and physical quantity measurement, which is greatly beneficial to autopilot, robot vision and other fields. We would like to develop advanced signal processing methods, intelligent information fusion techniques and several prototypes of intelligent sensor to boost the development in this field.

Remarks on correcting ionospheric distortions in L-band radar interferometry

The L-band synthetic aperture radar (SAR) interferometry (InSAR) technique has a lower accuracy due to ionospheric phase distortions. Recently, a multiple-aperture interferometry (MAI)-based ionospheric correction method has been proposed. Using four types of ionosphere-distorted interferograms, the performance of the correction method was evaluated and then analyzed the feasibility of the correction method. The test interferograms contained severe azimuth streaking, low-frequency ionospheric phase distortion and drastic phase change due to the ionosphere. The results showed that (i) the existence and magnitude of ionospheric phase distortions can be recognized from MAI interferograms and (ii) the MAI-based ionospheric correction method efficiently reduced severe azimuth streaking and low-frequency distortion but did not mitigate the drastic phase change perfectly. It is allowed (i) to determine whether a given SAR interferogram has an ionospheric distortion and (ii) to predict whether the ionospheric distortion can be corrected by using the MAI-based ionospheric correction method.

Ground Stability Monitoring of Undermined and Landslide Prone Areas by Means of Sentinel-1 Multi-Temporal InSAR, Case Study from Slovakia

Multi-temporal synthetic aperture radar interferometry techniques (MT-InSAR) are nowadays a well-developed remote sensing tool for ground stability monitoring of areas afflicted by natural hazards. Its application capability has recently been emphasized by the Sentinel-1 satellite mission, providing extensive spatial coverage, regular temporal sampling and free data availability. We perform MT-InSAR analysis over the wider Upper Nitra region in Slovakia, utilizing all Sentinel-1 images acquired since November 2014 until March 2017. This region is notable for its extensive landslide susceptibility as well as intensive brown coal mining. We focus on two case studies, being impaired by recent activation of these geohazards, which caused serious damage to local structures. We incorporate a processing chain based on open-source tools, combining the current Sentinel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS) implementation. MT-InSAR results reveal substantial activity at both case studies, exceeding the annual displacement velocities of 30 mm/year. Moreover, our observations are validated and their accuracy is confirmed via comparison with ground truth data from borehole inclinometers and terrestrial levelling. Detected displacement time series provide valuable insight into the spatio-temporal evolution of corresponding deformation phenomena and are thus complementary to conventional terrestrial monitoring techniques. At the same time, they not only demonstrate the feasibility of MT-InSAR for the assessment of remediation works, but also constitute the possibility of operational monitoring and routine landslide inventory updates, regarding the free Sentinel-1 data.

Integrated space geodesy for mapping land deformation over Choushui River Fluvial Plain, Taiwan

ABSTRACTGroundwater is an important part of the precious water resources. As the fresh surface water resources become scarcer because of climate change, population growth, and industrial activities, more and more groundwater has been extracted to meet the demands of various water uses (e.g. municipal, industrial, and agricultural). Excessive groundwater extraction leads to severe ground subsidence which compromises the safety of surface and underground infrastructures. Modelling the effects of groundwater extraction is vital to the management and sustainable use of groundwater. However, results of such modelling have to be validated with inputs such as the field survey of ground subsidence. Levelling and continuous global positioning system (GPS) receiver networks are routinely used to collect these field measurements. Unfortunately, these techniques have limitations in terms of areal coverage and density of survey marks and, as a result, subsidence hot spots can be easily missed out. In order to provide a comprehensive picture of subsidence to aid geotechnical modelling and to assess the effectiveness of measures used to mitigate ground subsidence, satellite imaging radar interferometry techniques (interferometric synthetic aperture radar (InSAR) can be used to complement other deformation monitoring techniques. In this study, 20 Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) images acquired from 31 December 2006 to 26 February 2011 were used to map the land displacement over the Choushui River Fluvial Plain (CRFP), Taiwan. The GPS measurements acquired at 10 continuously operating reference stations (CORS) were used to refine the orbit error in the each differential interferogram obtained from each radar image pair. The displacement time series over the distributed scatterers and the persistent scatterers were analysed. Several subsidence bowls were identified in CRFP. A quantitative comparison was conducted to compare the radar measurements to the GPS measurements over 36 GPS CORS stations. Good agreement between both measurements was observed with coefficient of determination (R2) of 0.97, absolute mean difference of 3.2 mm year−1, and standard deviation of 4 mm year−1. The InSAR-measured Line-of-Sight displacement and GPS-measured horizontal displacement were integrated to derive the vertical displacement map. Two displacement maps were generated using two ALOS-2 PALSAR-2 pairs acquired between 2015 and 2016. Similar subsidence patterns were found in the two maps compared to the 2006–2011 displacement rate map, suggesting the land over the same region might have continued to fall.

Structural Health and Stability Assessment of High-Speed Railways via Thermal Dilation Mapping With Time-Series InSAR Analysis

Thermal dilation is a vital component of deformation along the extensive railway network infrastructure. To monitor subtle deformation, the synthetic aperture radar interferometry (InSAR) technique has been adopted as a space-borne geodetic tool. However, InSAR applications in railway stability surveillance have been largely limited by the sparseness of detectable point-like targets (PTs). Moreover, only one-dimensional linear displacements in radar line-of-sight direction can be measured by a single data stack. To address these issues, we developed an improved persistent scatterers InSAR approach that can retrieve thermal dilation effects with an increased number of PTs along the railways. This proposed strategy effectively combines SAR amplitude, interferometric phase, and the spatial information of railway structures to maximize the number of PTs. A least square fitting of the residual phase obtained by iterative spatial-temporal filtering with respect to temperature difference is used to estimate the thermal dilation of metal and concrete-asphalt materials. To validate the effectiveness of this approach, case studies using ENVISAT ASAR (ASAR) and TerraSAR-X (TSX) datasets were carried out on the railways of Beijing–Tianjin, Beijing–Shanghai, and Shanghai–Hangzhou. Subsidence velocity, gradient, and thermal dilation were used to identify hazardous grades along each railway. Furthermore, linear deformation rates in two dimensions, i.e., vertical and west-east directions, along Shanghai–Hangzhou Railway were inverted from ascending ASAR and descending TSX observations to reveal track conditions at a high level of detail.

Monitoring Building Deformation with InSAR: Experiments and Validation.

Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated.

The Use of C-/X-Band Time-Gapped SAR Data and Geotechnical Models for the Study of Shanghai’s Ocean-Reclaimed Lands through the SBAS-DInSAR Technique

In this work, we investigate the temporal evolution of ground deformation affecting the ocean-reclaimed lands of the Shanghai (China) megacity, from 2007 to 2016, by applying the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique known as the Small BAseline Subset (SBAS) algorithm. For the analysis, we exploited two sets of non-time-overlapped synthetic aperture radar (SAR) data, acquired from 2007 to 2010, by the ASAR/ENVISAT (C-band) instrument, and from 2014 to 2016 by the X-band COSMO-SkyMed (CSK) sensors. The long time gap (of about three years) existing between the available C- and X-band datasets made the generation of unique displacement time-series more difficult. Nonetheless, this problem was successfully solved by benefiting from knowledge of time-dependent geotechnical models, which describe the temporal evolution of the expected deformation affecting Shanghai’s ocean-reclaimed platforms. The combined ENVISAT/CSK (vertical) deformation time-series were analyzed to gain insight into the future evolution of displacement signals within the investigated area. As an outcome, we find that ocean-reclaimed lands in Shanghai experienced, between 2007 and 2016, average cumulative (vertical) displacements extending down to 25 centimeters.

Preliminary study of conditions influencing slope dynamics in the area of Rovegliana (North-Eastern Italian pre-Alps)

The main aim of this study is to comprehend landslide phenomena that affect the area of Rovegliana (North-Eastern Italian pre-Alps), quantifying soil displacements and investigating conditions that influence slope dynamics. Geological surveying turns out to be useful as support to the satellite radar interferometry technique, whose results allowed to position the points of a GPS network. In a delimited area of two districts, identified with high level of criticality, laser-scanner surveying has been implemented on damaged buildings. Preliminary results show that the area is affected by superficial slow moving phenomena which need to be further investigated and monitored to plan effective remediation works.

Combining differential SAR interferometry and the probability integral method for three-dimensional deformation monitoring of mining areas

ABSTRACTWith the exploitation of coal resources, ground surface subsidence continues to occur in mining areas, destroying the ecological environment and significantly affecting the daily productivity and life of humans. The differential synthetic aperture radar interferometry (D-InSAR) technique is widely used to monitor ground surface deformation because of its unique advantages such as high accuracy and wide coverage. However, conventional D-InSAR technology provides only one-dimensional (1D) displacement monitoring along the radar line of sight (LOS). This article proposes a method based on an analysis of the mining subsidence law for true three-dimensional (3D) displacement monitoring by combining D-InSAR and a subsidence prediction model based on the probability integral method. In this approach, 1D displacement, obtained using D-InSAR, is then combined with the prediction model to obtain the 3D displacement of ground surface target points. Here, 3D displacement curves were obtained for the Fengfeng mining area (China) using RadarSat-2 images obtained on 9 January and 2 February 2011. True ground surface displacement was measured simultaneously by levelling when the 152under31 s working face was being exploited in Jiulong mine. Vertical displacement and inclined deformation calculated using the proposed method were compared with levelling survey data and the results showed average differences of 3.2 mm and 0.1 mm m−1, respectively; the calculated maximum displacement in the east–west and south–north directions were 106 and 73 mm, respectively. The spatial distribution of the displacements was in accordance with the mining subsidence law. Thus, the new method can retrieve highly accurate 3D displacements caused by mining subsidence.

Advanced Three-Dimensional Finite Element Modeling of a Slow Landslide through the Exploitation of DInSAR Measurements and in Situ Surveys

In this paper, we propose an advanced methodology to perform three-dimensional (3D) Finite Element (FE) modeling to investigate the kinematical evolution of a slow landslide phenomenon. Our approach benefits from the effective integration of the available geological, geotechnical and satellite datasets to perform an accurate simulation of the landslide process. More specifically, we fully exploit the capability of the advanced Differential Synthetic Aperture Radar Interferometry (DInSAR) technique referred to as the Small BAseline Subset (SBAS) approach to provide spatially dense surface displacement information. Subsequently, we analyze the physical behavior characterizing the observed landslide phenomenon by means of an inverse analysis based on an optimization procedure. We focus on the Ivancich landslide phenomenon, which affects a residential area outside the historical center of the town of Assisi (Central Italy). Thanks to the large amount of available information, we have selected this area as a representative case study highlighting the capability of advanced 3D FE modeling to perform effective risk analyses of slow landslide processes and accurate urban development planning. In particular, the FE modeling is constrained by using the data from 7 litho-stratigraphic cross-sections and 62 stratigraphic boreholes; and the optimization procedure is carried out using the SBAS-DInSAR retrieved results by processing 39 SAR images collected by the Cosmo-SkyMed (CSK) constellation in the 2009–2012 time span. The achieved results allow us to explore the spatial and temporal evolution of the slow-moving phenomenon and via comparison with the geomorphological data, to derive a synoptic view of the kinematical activity of the urban area affected by the Ivancich landslide.

Comparison of Small Baseline Interferometric SAR Processors for Estimating Ground Deformation

The small Baseline Synthetic Aperture Radar (SAR) Interferometry (SBI) technique has been widely and successfully applied in various ground deformation monitoring applications. Over the last decade, a variety of SBI algorithms have been developed based on the same fundamental concepts. Recently developed SBI toolboxes provide an open environment for researchers to apply different SBI methods for various purposes. However, there has been no thorough discussion that compares the particular characteristics of different SBI methods and their corresponding performance in ground deformation reconstruction. Thus, two SBI toolboxes that implement a total of four SBI algorithms were selected for comparison. This study discusses and summarizes the main differences, pros and cons of these four SBI implementations, which could help users to choose a suitable SBI method for their specific application. The study focuses on exploring the suitability of each SBI module under various data set conditions, including small/large number of interferograms, the presence or absence of larger time gaps, urban/vegetation ground coverage, and temporally regular/irregular ground displacement with multiple spatial scales. Within this paper we discuss the corresponding theoretical background of each SBI method. We present a performance analysis of these SBI modules based on two real data sets characterized by different environmental and surface deformation conditions. The study shows that all four SBI processors are capable of generating similar ground deformation results when the data set has sufficient temporal sampling and a stable ground backscatter mechanism like urban area. Strengths and limitations of different SBI processors were analyzed based on data set configuration and environmental conditions and are summarized in this paper to guide future users of SBI techniques.

Integration of InSAR Analysis and Numerical Modeling for the Assessment of Ground Subsidence in the City of Lisbon, Portugal

In this work, we exploit the integration of an advanced synthetic aperture radar (SAR) interferometry technique and the application of the finite-element method for the assessment and the interpretation of a localized subsidence phenomenon that took place within a specific area of Lisbon, Portugal. SAR images over the Lisbon city, covering different time intervals in the period of 1995–2010, were acquired and processed by means of the persistent scatterers (PSs) technique. Results clearly reveals a localized subsidence, limited to an area $2\;\text{km} \times 1.5\;\text{km}$ wide, which has been confirmed by the leveling performed in 1976, 1996, and 2010. A physical interpretation of the observed ground deformations is provided based on the results of a finite-element model using stratigraphic data, in situ piezometric measurements, and geotechnical properties of the involved soils. The ground subsidence is interpreted as the consequence of a consolidation process affecting the central fine-grained soil layer, which in turn has been driven by water withdrawal from the existing aquifers. The change of the hydraulic boundary conditions was generated by the excavation works for the construction of underground lines and also by the reduction of rainfall water infiltration as an effect of the increase in ground surface impermeable areas due to urbanization. The consequent consolidation process of the compressible fine-grained soil layer is supposed to provide a reasonable explanation of the observed time series of ground displacement in the examined area.

Study on spatial variation of land subsidence over Minagish–Umm Gudair oil fields of Kuwait using synthetic aperture radar interferometry technique

Land subsidence can be a major problem where there are large-scale underground activities such as oil extraction. This paper addresses the spatial variability of land subsidence over Minagish and Umm Gudair oil fields of Kuwait. Synthetic aperture radar interferometry (InSAR) with multiple reference scenes using a persistent scatterer InSAR toolchain was employed in this study. Twenty-nine scenes of advanced synthetic aperture radar data (for the period January 2005 to August 2009) were used to make 20 pairs of interferograms (with high coherence and low noise) of stable point-like reflectors. The output of this study is the land subsidence maps of Minagish and Umm Gudair oil fields with a spatial resolution of 40 m. The results indicate that there is land subsidence of 29.9 mm/year in the southern part of the oil field (Umm Gudair). This is the first detailed assessment of land subsidence in the Minagish–Umm Gudair oil fields; therefore, no ground-truth data are available to compare the subsidence results. The results were consistent, indicating their validity.

Using radar interferometry and SBAS technique to detect surface subsidence relating to coal mining in Upper Silesia from 1993-2000 and 2003-2010

Abstract In the presented research ERS1-2 and Envisat ASAR archive data were used for the periods 1993 – 2000 and 2003 – 2010. The radar images were acquired over Upper Silesia in southern Poland. DinSAR (Differential InSAR) and SBAS (Small Baseline Subset) methods were applied for the detection of the most subsided areas. The DinSAR images were layer stacked for an image using 26 interferometry pairs of ERS1-2 SAR and 16 pairs from Envisat ASAR images in an ascending-descending orbit combination. The stacking of these images showed the most subsided parts of these cities even under low coherent areas, but the results are less precise. In the Upper Silesian Coal Basin, intensive underground coal exploitation has resulted in several surface deformations under Bytom (~8-17 km2), Piekary Śląskie (~9-15 km2), Ruda Śląska (~32-42 km2) and Katowice (~20-23 km2) with 25-40 cm of subsidence (in general) in the studied time periods. The SBAS technique has also shown that coal mining caused subsidence in the cities of Bytom, Katowice, and Piekary Śląskie of 5-7 cm/yr. The presented SBAS method did not work for low coherent areas, e.g. dense forested areas. DInSAR data also pointed to several decreasingly less active mining areas, which relate to the mine closures in Bytom and Ruda Śląska, which is also verified by the time series analysis.

Cloud Computing for Earth Surface Deformation Analysis via Spaceborne Radar Imaging: A Case Study

We present a case study on the migration to a Cloud Computing environment of the advanced differential synthetic aperture radar interferometry (DInSAR) technique, referred to as Small BAseline Subset (SBAS), which is widely used for the investigation of Earth surface deformation phenomena. In particular, we focus on the SBAS parallel algorithmic solution, namely P-SBAS, that allows the production of mean deformation velocity maps and the corresponding displacement time-series from a temporal sequence of radar images by exploiting distributed computing architectures. The Cloud migration is carried out by encapsulating the overall P-SBAS application in virtual machines running on the Cloud; moreover, the Cloud resources provisioning and configuration phases are implemented in an automatic way. Such an approach allows us to preserve the P-SBAS parallelization strategy and to straightforwardly evaluate its performance within a Cloud environment by comparing it with those achieved on a HPC in-house cluster. The results we present were achieved by using the Amazon Elastic Compute Cloud (EC2) of the Amazon Web Services (AWS) to process SAR datasets collected by the ENVISAT satellite and show that, thanks to the Cloud resources availability and flexibility, large DInSAR data volumes can be processed through the P-SBAS algorithm in short time frames and at reduced costs. As a case study, the mean deformation velocity map of the southern California area has been generated by processing 172 ENVISAT images. By exploiting 32 EC2 instances this processing took less than 17 hours to complete, with a cost of USD 850. Considering the available PB-scale archives of SAR data and the upcoming huge SAR data flow relevant to the recently launched (April 2014) Sentinel-1A and the forthcoming Sentinel-1B satellites, the exploitation of Cloud Computing solutions is particularly relevant because of the possibility to provide Cloud-based multi-user services allowing worldwide scientists to quickly process SAR data and to manage and access the achieved DInSAR results.

Spatio-temporal evolution of aseismic ground deformation in the Mexicali Valley (Baja California, Mexico) from 1993 to 2010, using differential SAR interferometry

Abstract. Ground deformation in Mexicali Valley, Baja California, Mexico, the southern part of the Mexicali-Imperial valley, is influenced by active tectonics and human activity, mainly that of geothermal fluid extraction in the Cerro Prieto Geothermal Field. Significant ground deformation, mainly subsidence (~ 18 cm yr−1), and related ground fissures cause severe damage to local infrastructure. The technique of Differential Synthetic Aperture Radar Interferometry (DInSAR) has been demonstrated to be a very effective remote sensing tool for accurately measuring the spatial and temporal evolution of ground displacements over broad areas. In present study ERS-1/2 SAR and ENVISAT ASAR images acquired between 1993 and 2010 were used to perform a historical analysis of aseismic ground deformation in Mexicali Valley, in an attempt to evaluate its spatio-temporal evolution and improve the understanding of its dynamic. For this purpose, the conventional 2-pass DInSAR was used to generate interferograms which were used in stacking procedure to produce maps of annual aseismic ground deformation rates for different periods. Differential interferograms that included strong co-seismic deformation signals were not included in the stacking and analysis. The changes in the ground deformation pattern and rate were identified. The main changes occur between 2000 and 2005 and include increasing deformation rate in the recharge zone and decreasing deformation rate in the western part of the CPGF production zone. We suggested that these changes are mainly caused by production development in the Cerro Prieto Geothermal Field.

Railway deformation detected by DInSAR over active sinkholes in the Ebro Valley evaporite karst, Spain

Abstract. Subsidence was measured for the first time on railway tracks in the central sector of Ebro Valley (NE Spain) using Differential Synthetic Aperture Radar Interferometry (DInSAR) techniques. This area is affected by evaporite karst and the analysed railway corridors traverse active sinkholes that produce deformations in these infrastructures. One of the railway tracks affected by slight settlements is the Madrid–Barcelona high-speed line, a form of transport infrastructure highly vulnerable to ground deformation processes. Our analysis based on DInSAR measurements and geomorphological surveys indicates that this line shows dissolution-induced subsidence and compaction of anthropogenic deposits (infills and embankments). Significant sinkhole-related subsidence was also measured by DInSAR techniques on the Castejón–Zaragoza conventional railway line. This study demonstrates that DInSAR velocity maps, coupled with detailed geomorphological surveys, may help in the identification of the railway track sections that are affected by active subsidence.

Monitoring of ground surface and subsurface deformations at oil sands using radar interferometry

Conventional monitoring methods, such as surveying and tiltmeter, require labor-intensive and time-consuming fieldwork, and they are limited to specific locations, either survey stations or an array of tiltmeters. Furthermore, none of the studies about the geomechanical inversion of cumulative surface deformations for the inference of subsurface volumetric changes in Canadian oil sands has yet been published. Radar interferometry has been widely used for monitoring surface deformations over a large area in all weather conditions with high accuracy. We have developed a method to detect surface deformations by radar interferometry techniques and to estimate subsurface volumetric changes by geomechanical inversion of surface deformation measurements. Differential interferometric synthetic aperture radar was implemented using first advanced land observation satellite phased array type L-band synthetic aperture radar data; the resulting interferograms indicated the vertical surface deformations between July 2007 and March 2011. An additional investigation into the detected surface deformations was performed to retrieve time-series maps of cumulative surface deformations, which accounted for the temporal evolution of the changes in surface elevation. The temporal analysis confirmed that the ground surface experienced nonlinear time-varying vertical deformations, reaching up to [Formula: see text] and [Formula: see text] for a 3.7 year time period starting in July 2007. The surface deformations were interpreted using cubic polynomial regression with historical information on fluid injection and withdrawal. The positive curvilinear relationships between the fluid volume changes, which were caused by steam injection and bitumen/water production, and the surface deformations, were found with an [Formula: see text] of greater than 0.73. The fractional volumetric changes in the reservoir were examined by applying geomechanical inversion to surface deformation measurements. The fractional volumetric changes ranged from [Formula: see text] to [Formula: see text] with respect to the initial reservoir volume for the 3.7 year period. A positive linear relationship between fluid volume changes and subsurface volumetric changes was determined with [Formula: see text] ranging from 0.515 to 0.992.

InSAR monitoring using RADARSAT-2 data at Piton de la Fournaise (La Reunion) and Karthala (Grande Comore) volcanoes

Abstract Piton de la Fournaise (La Reunion) and Karthala (Grande Comore) are the two active volcanoes of the Southwestern Indian Ocean. A 14 month (April 2013 to June 2014) monitoring period was carried out at both volcanoes using synthetic aperture RADAR interferometry (InSAR) techniques on RADARSAT-2 data. Thanks to the SEAS-OI (Survey of Environment Assisted by Satellite in the Indian Ocean) station, 21 SAR scenes were acquired over this period and InSAR results revealed the slow subsidence of the Dolomieu caldera floor at Piton de la Fournaise, following the 2009 and 2010 eruptions, and the subsidence of the whole cone between April and July 2013. At Karthala no evidence of any volcanic activity was found for the period April 2013 to June 2014. The use of systematic InSAR for volcano monitoring is an efficient tool to study effusive eruptions. We showed that, during periods of unrest, InSAR is able to pick up early signs of a future eruption and monitor secondary phenomena that require no real-time data. During an effusive crisis, it is still difficult to carry out fully operational InSAR monitoring, but using the example of the June 2014 eruption at Piton de la Fournaise, we show that SAR data can help with the detection and tracking of lava flows and active flow paths during effusive eruptions, based on SAR coherence and SAR amplitude. These preliminary results are very promising for the future of InSAR monitoring of active volcanoes and highlight the need for near-real-time access to SAR data in the mapping of active lava flows during effusive eruptions. This study also revealed the major role of ground stations like SEAS-OI in the efficiency of this monitoring, supplying free, near-real-time remote sensing data to the scientific and institutional communities.

Mapping Two-Dimensional Deformation Field Time-Series of Large Slope by Coupling DInSAR-SBAS with MAI-SBAS

Mapping deformation field time-series, including vertical and horizontal motions, is vital for landslide monitoring and slope safety assessment. However, the conventional differential synthetic aperture radar interferometry (DInSAR) technique can only detect the displacement component in the satellite-to-ground direction, i.e., line-of-sight (LOS) direction displacement. To overcome this constraint, a new method was developed to obtain the displacement field time series of a slope by coupling DInSAR based small baseline subset approach (DInSAR-SBAS) with multiple-aperture InSAR (MAI) based small baseline subset approach (MAI-SBAS). This novel method has been applied to a set of 11 observations from the phased array type L-band synthetic aperture radar (PALSAR) sensor onboard the advanced land observing satellite (ALOS), spanning from 2007 to 2011, of two large-scale north–south slopes of the largest Asian open-pit mine in the Northeast of China. The retrieved displacement time series showed that the proposed method can detect and measure the large displacements that occurred along the north–south direction, and the gradually changing two-dimensional displacement fields. Moreover, we verified this new method by comparing the displacement results to global positioning system (GPS) measurements.