ASAR Images Research Articles

Mapping the Yellow River Delta land subsidence with multitemporal SAR interferometry by exploiting both persistent and distributed scatterers

Due to highly compressible soil and a large amount of human activity, the costal deltas are more prone to ground subsidence. Many major costal deltas in the world are facing subsidence and are consequently more susceptible to flooding, salinization and seawater infusion or even permanent submergence. Therefore, ground subsidence has been a significant problem in coastal delta areas worldwide. The Yellow River Delta (YRD) is the second largest river delta in China. On the one hand, the YRD contains a large area of wetlands rich in biodiversity, and on the other hand, industrial activities and urbanization are extensive due to abundant underground resources such as oil, gas and brine. Excessive land use has caused different degrees of ground subsidence in this area. However, a detailed and comprehensive description of the ground subsidence pattern over the YRD has not been provided. Also, widespread non-urban area in Yellow River Delta region, such as wetlands, farmland and coastal tidal areas, hinders the application of persistent scatterer interferometry method (PSI) for comprehensive subsidence measurement over the whole area. In this paper, we developed a multitemporal InSAR method to map ground subsidence over the YRD area by exploiting both persistent scatterers (PS) and distributed scatterers (DS). This method is characterized by employing the coherence-weighted phase-linking algorithm for fast and reliable optimal phase reconstruction of each DS point and a two-tier network of PS and DS for the robust analysis of land subsidence. To extract the detailed and comprehensive ground subsidence over the whole YRD, we apply our method to 30 ENVISAT ASAR images (2007–2010) and 49 Sentinel-1A (S-1A) images (2015–2018) and obtain measurements of the ground subsidence during these two periods. Forty-one Sentinel-1B (S-1B) images (2016–2018) are also exploited for cross-sensor consistency validation with the result derived from the S-1A dataset. Our method shows a great advantage over the PSI method, providing much higher measuring point (MP) density in mapping land subsidence over the YRD, including 15-fold higher density for the ASAR dataset, 5.1-fold for the S-1A dataset and 5.3-fold for the S-1B dataset, which enables a very detailed description of local ground deformation patterns. Cross-track consistency in the derived measurements from the S-1A and S-1B datasets shows a standard deviation of 9.6 mm/yr for the vertical subsidence rate. A quantitative validation of the derived subsidence results compared with leveling measurements suggests an accuracy of 4.58 mm/yr for the standard deviation term. By comparing the ground deformation over the YRD during the periods of 2015–2018 and 2007–2010, we find that the subsidence in this region shows an overall intensification trend and many new and severe subsidence depressions appear along the coastline, with a maximum vertical subsidence rate of 432 mm/yr. Subsequently, the overextraction of underground brine for salt production is identified as the primary factor causing the ground subsidence near the YRD coastal area.

Detecting and monitoring of landslides using persistent scattering synthetic aperture radar interferometry

Persistent scatterer synthetic aperture radar interferometry (PSInSAR) is an applied time series technique to overcome limitations of InSAR (temporal and geometrical decorrelation and atmospheric delay anomalies) for monitoring of ground surface deformations. This method only monitors displacements on pixels with nearly constant temporal backscattering characteristics. In this study, datasets of ascending ALOS PALSAR (L-band) images recorded from 2006 to 2010 and descending ENVISAT ASAR (C-band) images acquisitioned between 2003 and 2010 were processed to detect and monitor the landslide occurred in the Noghol area, Iran. Application of the PSInSAR technique on both PALSAR and ASAR images has significantly improved monitoring of the Noghol landslide. However, the determination of vertical displacement of the landslide by the ASAR images processing is more correct compared to results of the PALSAR processing due to the descending orbital motion of ASAR. The ASAR images also overwhelm PALSAR images for determination of the landslide extent because of detection of more persistent scatterer points. The landslide displacement and aspect obtained by the Global Navigation Satellite System (GNSS) and PSInSAR techniques are in agreement (about 1.2–1.5 m westward in the period of 2003–2010). Particularly, processing results of the ASAR images are more similar to the GNSS measurements. Furthermore, assessment of the landslide type, mechanism and its displacement direction were possible by integration of the PALSAR and ASAR radar images with ascending and descending orbital motions, respectively.

Ground deformation and fissure activity in Datong basin, China 2007–2010 revealed by multi-track InSAR

abstarctThe Datong basin is one of the complex geologic environments in China. Several faults are distributed in the basin, and a number of hidden faults have been discovered within the basin. Ground fissures (GFs) and land subsidence occur in this region. In the past, ground subsidence at Datong basin has been studied using groundwater level records, intermittent small-scale levelling measurements and field investigations. However, due to the low spatial resolution and temporal sampling of these records, detailed ground deformation within the basin remains poorly understood. In this study, we exploited Envisat ASAR and ALOS PALSAR images to map the ground deformation between 2007 and 2010. Most of the deformation within the basin occurred at rates of <20 mm/year. In addition to the subsidence due to coal mining in the western mountainous areas, at least four large subsidence zones could be detected. Our analysis indicates that the ground subsidence is affected by groundwater extraction and the distribution of faults. Additionally, the vertical deformation is much larger than the deformation in the east–west direction. Obvious deformation gradients occurred on individual GFs and the activity of the GFs varied spatially. Finally, Interferometric synthetic aperture radar (InSAR) observations related to groundwater exploitation and GFs were modelled and discussed.Abbreviations: GFs: ground fissures; SAR: Synthetic Aperture Radar; ASAR: Advanced Synthetic Aperture Radar; ALOS: Advanced Land Observing Satellite; PALSAR: Phased Array type L-band Synthetic Aperture Radar; InSAR: Interferometric Synthetic Aperture Radar; ESA: European Space Agency; JAXA: Japan Aerospace Exploration Agency; SBAS: Small Baseline Subsets; SRTM: Shuttle Radar Topography Mission; DEM: Digital Elevation Model; DORIS: Dopper Orbitography and Radiopositioning Integrated by Satellite instrument; MCF: minimum cost flow; LOS: line-of-sight2D/3D: two-dimensional/three-dimensional

Investigation of Ground Deformation in Taiyuan Basin, China from 2003 to 2010, with Atmosphere-Corrected Time Series InSAR

Excessive groundwater exploitation is common through the Taiyuan basin, China, and is well known to result in ground subsidence. However, most ground subsidence studies in this region focus on a single place (Taiyuan city), and thus fail to demonstrate the regional extent of the deformation phenomena in the whole basin. In this study, we used Interferometric Synthetic Aperture Radar (InSAR) time series analysis to investigate land subsidence across the entire Taiyuan basin region. Our data set includes a total of 75 ENVISAT ASAR images from two different frames acquired from August 2003 to September 2010 and 33 TerraSAR-X scenes spanning between March 2009 and March 2010. ERA-Interim reanalysis was used to correct the stratified delay to reduce the bias expected from the systematic components of tropospheric delay. The residual delay after correction of stratified delay can be considered as a stochastic component and be mitigated through spatial-temporal filtering. A comparison with MERIS (Medium-Resolution Imaging Spectrometer) measurements indicates that our atmospheric corrections improved agreement over the conventional spatial-temporal filtering by about 20%. The displacement results from our atmosphere-corrected time series InSAR were further validated with continuous GPS data. We found eight subsiding centers in the basin and a surface uplift to the north of Taiyuan city. The causes of ground deformation are analyzed and discussed in relation to gravity data, pre-existing faults, and types of land use.

A Phase Unwrapping Approach Based on Extended Kalman Filter for Subsidence Monitoring Using Persistent Scatterer Time Series Interferometry

Persistent scatterer interferometry that overcomes the spatial and temporal problems is an effective technique for measuring the surface deformation. The main issue of the technique, however, is unwrapping the persistent scatterers’ phases that are irregularly spaced. The problem is even more challenging when the deformation rate is too high. In this paper, a phase unwrapping method based on an extended Kalman filter as a path-following method is presented. Mean fringe frequency as the phase slope, which is to be used in the extended Kalman filter, is estimated within a local window. The most proper paths for unwrapping are identified by a proposed hybrid cost map, which is a combination of the scaled phase derivative variance, the distances between the persistent scatterer pixels, and the discontinuity locations. The presented method is applied to ENVISAT ASAR images acquired over southwestern Tehran for subsidence monitoring. The maximum displacement rate estimated from the proposed method is about 18 cm/year. Moreover, the results are then validated using a continuous GPS station and leveling measurements acquired over a different time interval. The difference between the rates estimated from the GPS measurements and the proposed method is 0.2 cm/year. It was found that the proposed method makes a significant improvement over the unwrapping problem.

Monitoring the tabular icebergs C28A and C28B calved from the Mertz Ice Tongue using radar remote sensing data

We analyzed the evolution processes of two tabular icebergs, C28A and C28B, originating from iceberg C28, using continuous multisource radar remote sensing data. The monitoring began during the calving of iceberg C28 from the Mertz Ice Tongue in February 2010 and ended in April 2012. The evolution of the iceberg area was determined from ENVISAT ASAR images, and the freeboard change was derived from CryoSat-2 profiles. Two patterns of iceberg area decreases are observed during iceberg drifting. In austral summer (from October to next March), iceberg area shows a gradual decrease and it is interpreted to represent edge wasting, sidewall melting and wave erosion, the gradual decrease of the area of C28A occurred at rates between 8.1 km2/month and 16.5 km2/month. In austral winter (from April to September), iceberg area has several discrete decreases (sudden drop) while it remained constant for most of the time, and it is interpreted to be large rift calving primarily caused by ocean swell and basal melting. Calving area of the two studied icebergs is observed to be greater in the winter. The freeboard decreased at different rates at different locations on the same iceberg (between −0.02 ± 0.22 and −0.82 ± 0.28 m/month for C28A and C28B), suggesting a laterally inhomogeneous melting of icebergs. The average rate of change of the C28B freeboard during its 22-month grounding period was −0.03 ± 0.01 m/month, which is considerably smaller than the −0.76 ± 0.23 m/month observed when it was freely drifting in the ocean. The cold-water regime surrounding the iceberg can help the iceberg maintain a stable state. This study reveals the potential use of radar remote sensing when monitoring Antarctic icebergs.

TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

Abstract. Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

GROUND SUBSIDENCE ALONG SHANGHAI METRO LINE 6 BY PS-InSAR METHOD

Abstract. With the rapid development of urban economy, convenient, safe, and efficient urban rail transit has become the preferred method for people to travel. In order to ensure the safety and sustainable development of urban rail transit, the PS-InSAR technology with millimeter deformation measurement accuracy has been widely applied to monitor the deformation of urban rail transit. In this paper, 32 scenes of COSMO-SkyMed descending images and 23 scenes of Envisat ASAR images covering the Shanghai Metro Line 6 acquired from 2008 to 2010 are used to estimate the average deformation rate along line-of-sight (LOS) direction by PS-InSAR method. The experimental results show that there are two main subsidence areas along the Shanghai Metro Line 6, which are located between Wuzhou Avenue Station to Wulian Road Station and West Gaoke Road Station to Gaoqing Road Station. Between Wuzhou Avenue Station and Wulian Road Station, the maximum displacement rate in the vertical direction of COSMO-SkyMed images is −9.92 mm/year, and the maximum displacement rate in the vertical direction of Envisat ASAR images is −8.53 mm/year. From the West Gaoke Road Station to the Gaoqing Road Station, the maximum displacement rate in the vertical direction of COSMO-SkyMed images is −15.53 mm/year, and the maximum displacement rate in the vertical direction of Envisat ASAR images is −17.9 mm/year. The results show that the ground deformation rates obtained by two SAR platforms with different wavelengths, different sensors and different incident angles have good consistence with each other, and also that of spirit leveling.

Spatiotemporal Evolution of Land Subsidence in the Beijing Plain 2003–2015 Using Persistent Scatterer Interferometry (PSI) with Multi-Source SAR Data

Land subsidence is one of the most important geological hazards in Beijing, China, and its scope and magnitude have been growing rapidly over the past few decades, mainly due to long-term groundwater withdrawal. Interferometric Synthetic Aperture Radar (InSAR) has been used to monitor the deformation in Beijing, but there is a lack of analysis of the long-term spatiotemporal evolution of land subsidence. This study focused on detecting and characterizing spatiotemporal changes in subsidence in the Beijing Plain by using Persistent Scatterer Interferometry (PSI) and geographic spatial analysis. Land subsidence during 2003–2015 was monitored by using ENVISAT ASAR (2003–2010), RADARSAT-2 (2011–2015) and TerraSAR-X (2010–2015) images, with results that are consistent with independent leveling measurements. The radar-based deformation velocity ranged from −136.9 to +15.2 mm/year during 2003–2010, and −149.4 to +8.9 mm/year during 2011–2015 relative to the reference point. The main subsidence areas include Chaoyang, Tongzhou, Shunyi and Changping districts, where seven subsidence bowls were observed between 2003 and 2015. Equal Fan Analysis Method (EFAM) shows that the maximum extensive direction was eastward, with a growing speed of 11.30 km2/year. Areas of differential subsidence were mostly located at the boundaries of the seven subsidence bowls, as indicated by the subsidence rate slope. Notably, the area of greatest subsidence was generally consistent with the patterns of groundwater decline in the Beijing Plain.

Optimized fuzzy cellular automata for synthetic aperture radar image edge detection

The development of coastline detection has been the subject of several reports. An optimized fuzzy cellular automata (FCA) algorithm for SAR image edge detection, which combines newly defined cellular automata (CAs) and fuzzy rules, is proposed. An extended Moore neighborhood is used for cellular automaton. Twelve custom masks were defined to study the edge angles of the radius two neighborhood of the main pixel. Comparing these edge angles with the radius, one neighborhood of the main pixel is useful when deciding whether or not a pixel is an edge pixel. The model was tested on two sets of images. The first dataset contained optical and simulated SAR images and the second contained an Envisat ASAR image and a ScanSAR image. A 3 × 3 Lee filter (as a preprocessing phase) was applied to each subimage containing coastlines, and the subimages were then processed using an FCA edge detector. The results were compared with those from a Sobel edge detector, Roberts edge detector, wavelet transform edge detector, and classic CA model. The results showed that the proposed method is more appropriate for edge detection of SAR images when compared with classic methods. The proposed method and wavelet transform edge detector showed good continuity, but the proposed method dealt better with speckle noise effects.

A New Approach for Monitoring the Terra Nova Bay Polynya through MODIS Ice Surface Temperature Imagery and Its Validation during 2010 and 2011 Winter Seasons

Polynyas are dynamic stretches of open water surrounded by ice. They typically occur in remote regions of the Arctic and Antarctic, thus remote sensing is essential for monitoring their dynamics. On regional scales, daily passive microwave radiometers provide useful information about their extent because of their independence from cloud coverage and daylight; nonetheless, their coarse resolution often does not allow an accurate discrimination between sea ice and open water. Despite its sensitivity to the presence of clouds, thermal infrared (TIR) Moderate Resolution Imaging Spectroradiometer (MODIS) provides higher-resolution information (typically 1 km) at large swath widths, several times per day, proving to be useful for the retrieval of the size of polynyas. In this study, we deal with Aqua satellite MODIS observations of a frequently occurring coastal polynya in the Terra Nova Bay (TNB), Ross Sea (Antarctica). The potential of a new methodology for estimating the variability of this polynya through MODIS TIR during the 2010 and 2011 freezing season (April to October) is presented and discussed. The polynya is observed in more than 1600 radiance scenes, after a preliminary filter evaluates and discards cloudy and fog-contaminated scenes. This reduces the useful MODIS swaths to about 50% of the available acquisitions, but a revisit time of less than 24 h is kept for about 90% of the study period. As expected, results show a high interannual variability with an opening/closing fluctuation clearly depending on the regime of the katabatic winds recorded by the automatic weather stations Rita and Eneide along the TNB coast. Retrievals are also validated through a comparison with a set of 196 co-located high-resolution ENVISAT ASAR images. Although our estimations slightly underestimate the ASAR derived extents, a good agreement is found, the linear correlation reaching 0.75 and the average relative error being about 6%. Finally, a sensitivity test on the applied thermal thresholds supports the effectiveness of our setting.

Spatio-Temporal Characterization of a Reclamation Settlement in the Shanghai Coastal Area with Time Series Analyses of X-, C-, and L-Band SAR Datasets

Large-scale reclamation projects during the past decades have been recognized as one of the driving factors behind land subsidence in coastal areas. However, the pattern of temporal evolution in reclamation settlements has rarely been analyzed. In this work, we study the spatio-temporal evolution pattern of Linggang New City (LNC) in Shanghai, China, using space-borne synthetic aperture radar interferometry (InSAR) methods. Three data stacks including 11 X-band TerraSAR-X, 20 L-band ALOS PALSAR, and 35 C-band ENVISAT ASAR images were used to retrieve time series deformation from 2007 to 2010 in the LNC. An InSAR analysis from the three data stacks displays strong agreement in mean deformation rates, with coefficients of determination of about 0.9 and standard deviations for inter-stack differences of less than 4 mm/y. Meanwhile, validations with leveling data indicate that all the three data stacks achieved millimeter-level accuracies. The spatial distribution and temporal evolution of deformation in the LNC as indicated by these InSAR analysis results relates to historical reclamation activities, geological features, and soil mechanisms. This research shows that ground deformation in the LNC after reclamation projects experienced three distinct phases: primary consolidation, a slight rebound, and plateau periods.

Optimal selection and application analysis of multi-temporal differential interferogram series in StaMPS-based SBAS InSAR

ABSTRACTThe optimal selection of multi-temporal differential interferogram series is an important step to monitor ground subsidence using the Stanford method for persistent scatterers (StaMPS)-based small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR). Using a deformation model and its two solution methods, least squares and singular value decomposition, we present the composing mode and optimal selection of multi-temporal differential interferogram series and show that their quality and quantity affect the accuracy of monitored deformation information of SBAS InSAR. Using 29 ENVISAT ASAR images covering urban areas of Beijing, China, a different number of optimal multi-temporal differential interferogram series are formed to monitor urban ground subsidence by the StaMPS-based SBAS method. The comparison and verification of test results indicate that the quality and quantity of multi-temporal differential interferogram series substantially impact the singularity and degree of ill condition of the deformation model, locations of the selected slowly decorrelating filtered phase (SDFP) pixels, and monitored annual mean subsidence velocities. The suitable number of multi-temporal differential interferogram series under the optimal quality is 1–2 for a month in urban ground subsidence monitoring using StaMPS-based SBAS InSAR, a higher quantity of differential interferograms of the optimal quality is not always better.

Mapping landslide surface displacements with time series SAR interferometry by combining persistent and distributed scatterers: A case study of Jiaju landslide in Danba, China

InSAR technology provides a powerful tool to detect potentially unstable slopes across wide areas and to monitor surface displacements of a single landslide. However, conventional time series InSAR methods such as persistent scatterer interferometry (PSI) and small-baseline subset (SBAS) can rarely identify sufficient measurement points (MPs) in mountainous areas due to decorrelations caused by steep terrain and vegetation coverage. In this study, we developed a new InSAR approach, coherent scatterer InSAR (CSI), to map landslide surface displacements in the radar line-of-sight (LOS) direction by combining persistent scatterers (PS) and distributed scatterers (DS). The key ideas of CSI include the employment of the generalized likelihood ratio (GLR) test for the identification of statistically homogeneous pixels (SHPs) and the use of the phase linking algorithm to estimate optimal phase for each DS pixel. The joint exploitation of PS and DS targets dramatically increases the spatial density of MPs, which makes the phase unwrapping more reliable. To demonstrate the effectiveness of the CSI approach, we applied it to retrieve the historical displacements of the Jiaju landslide in Danba County of southwest China using 19 L-band ALOS PALSAR images (2006–2011) and nine C-band ENVISAT ASAR images (2007–2008). Multiple comparisons clearly illustrated the big advantages of CSI over PSI and SBAS in mapping landslide displacements with more details owing to much higher (>10 times) MP density. Furthermore, the superiority of L-band SAR data over C-band for landslide investigation in rural environments was confirmed. Quantitative validation of the CSI results for PALSAR data against in-situ GPS measurements suggested an accuracy of about 10.5millimeters per year (mm/year) in terms of root mean square error (RMSE). Afterwards, the spatial-temporal characteristics of the Jiaju landslide surface displacements were summarized, with a new upper boundary for the active northern part delineated. Particularly, the northern part of the landslide moved faster than the southern part, exhibiting a maximum LOS displacement rate of around 120mm/year. Subsequently, the fluvial erosion by the Dajinchuan River was identified as the predominant impact factor for the instability of the Jiaju landslide. Finally, the major problems and challenges for the application of CSI method were discussed, and the conclusions were given.

TIME SERIES ANALYSIS OF INSAR DATA TO STUDY LAND SUBSIDENCE INDUCED BY GROUNDWATER LEVEL DECLINE IN SIRJAN PLAIN

Abstract. Sirjan located in Southwest of Kerman City, Iran, is a city with average annual rainfall of 132mm. Over-exploitation of groundwater used for irrigation of pistachios gardens has caused serious land subsidence in Sirjan Plain. In this research we have used the Interferometric Synthetic Aperture Radar technique to estimate the subsidence rate in Sirjan plain. 18 Interferograms extracted from 12 ENVISAT ASAR images spanning between April 2004 and September 2010, have been studied. The SBAS algorithm was then applied in order to estimate the mean subsidence velocity map. Maximum subsidence rate is estimated as 28cm/yr. Furthermore, groundwater level fluctuations in the study area has been investigated in the piezometer wells located in the study area. Comparing between the results obtained from the interferometry and groundwater level fluctuation maps, shows a strong correlation between head decline in groundwater and land subsidence.

Correcting InSAR Topographically Correlated Tropospheric Delays Using a Power Law Model Based on ERA-Interim Reanalysis

Tropospheric delay caused by spatiotemporal variations in pressure, temperature, and humidity in the lower troposphere remains one of the major challenges in Interferometric Synthetic Aperture Radar (InSAR) deformation monitoring applications. Acquiring an acceptable level of accuracy (millimeter-level) for small amplitude surface displacement is difficult without proper delay estimation. Tropospheric delay can be estimated from the InSAR phase itself using the spatiotemporal relationship between the phase and topography, but separating the deformation signal from the tropospheric delay is difficult when the deformation is topographically related. Approaches using external data such as ground GPS networks, space-borne spectrometers, and meteorological observations have been exploited with mixed success in the past. These methods are plagued, however, by low spatiotemporal resolution, unfavorable weather conditions or limited coverage. A phase-based power law method recently proposed by Bekaert et al. estimates the tropospheric delay by assuming the phase and topography following a power law relationship. This method can account for the spatial variation of the atmospheric properties and can be applied to interferograms containing topographically correlated deformation. However, the parameter estimates of this method are characterized by two limitations: one is that the power law coefficients are estimated using the sounding data, which are not always available in a study region; the other is that the scaled factor between band-filtered topography and phase is inverted by least squares regression, which is not outlier-resistant. To address these problems, we develop and test a power law model based on ERA-Interim (PLE). Our version estimates the power law coefficients by using ERA-Interim (ERA-I) reanalysis. A robust estimation technique was introduced in the PLE method to estimate the scaled factor, which is insensitive to outliers. We applied the PLE method to ENVISAT ASAR images collected over Southern California, US, and Tianshan, China. We compared tropospheric corrections estimated from using our PLE method with the corrections estimated using the linear method and ERA-I method. Accuracy was evaluated by using delay measurements from the Medium Resolution Imaging Spectrometer (MERIS) onboard the ENVISAT satellite. The PLE method consistently delivered greater standard deviation (STD) reduction after tropospheric corrections than both the linear method and ERA-I method and agreed well with the MERIS measurements.

MONITORING OF MASJED-SOLEIMAN EMBANKMENT DAM’S DEFORMATION USING A COMBINATION OF INTERFEROMETRIC SYNTHETIC APERTURE RADAR (INSAR) AND FINITE ELEMENT MODELING

The fresh water shortage is one the most important challenges in many countries like Iran. So there have been incentives to manipulate and manage water resources by constructing dams. Clay core embankments are one of the most popular dam structures. A layer of clay can be a reliable obstacle in front of water stream. However, because of the soil’s nature, these kinds of dams have the potential of instability. Thus deformation of clay core dams should be monitored frequently. The aim of this study is to use the combination of Interferometric Synthetic Aperture Radar technique (InSAR) and Finite Element Modeling (FEM) for dam’s deformation monitoring. For the InSAR analysis we used data from ENVISAT sensor and processed those using Small BAseline Subset (SBAS). We show that InSAR is an invaluable approach to monitor clay core dam’s deformation in specific circumstances. The deformation derived from InSAR was used as an initial condition in Finite Element Modeling. The case study is Masjed Soleiman Dam which is situated in South West of Iran. We used 19 ASAR images of ENVISAT sensor from 2003/8/22 to 2010/5/7. The process of ASAR images showed maximum velocity of 11 mm/year in LOS direction at central lower areas of dam. These results were compared with Geodetic Surveying Operations at four points on dam and the average agreement of 77 percent was obtained. The results of ENVISAT data have a good consistency with FEM results. Horizontal and vertical displacements derived from instrumentations and modeling are plotted versus depths. There is a good agreement between modeling results and instrumentations data.

The Crustal Deformation Revealed by GPS and InSAR in the Northwest Corner of the Tarim Basin, Northwestern China

The Northwestern Corner of the Tarim Basin (hereinafter the NOCTB) is surrounded by the Pamir salient, the south Tian Shan Mountains, and the Tarim Basin. The tectonic settings of these three structures dominate the crustal deformation patterns and seismic events in the NOCTB and its adjacent regions. We integrated the GPS and InSAR measurements to derive a large-scale three-dimensional velocity map of the NOCTB. The GPS data obtained during 38 campaigns between 1992 and 2013 were used to derive a horizontal velocity field. 149 Envisat ASAR images observed along four satellite tracks between 2003 and 2011 were processed to get a line of sight rate map based on the small baseline subset time series analysis method and a homogeneous isotropic model. Finally, we modeled the dip angle, slip rate, and locking depth of selected faults. The results indicate that the crustal convergence is not uniformly distributed across the NOCTB: more than 50% of the N–S shortening is absorbed by the Tian Shan Mountains in the southwest, whereas the N–S shortening rates are low and therefore the strain accommodations are smaller in the east of the NOCTB. The vertical displacement rates in the NOCTB range from −2 to 3 mm/year with different magnitudes in different areas. The main uplift areas are located on the junction region between frontal MPT and the southwestern STT including the Kazkeaerte fault, Aikenerte fault, the Southern Artux fault, and part areas in north of the Kalping fault. The main subsident areas are located on central belt of STT including the Totgumbaz–Alpaleh fault, Nothern Artux fault, the southwestern Karatieke fault, and the north of Puchang/Piqiang fault. Compared with the substantial N–S shortening rate of ~10 mm/year, the vertical rate across each fault ranges from approximately −1 to 1 mm/year, suggesting that vertical movement in NOCTB area is relatively moderate at present. Both the horizontal and vertical rates show obvious changes across the Kazkeaerte fault and the Kuzgong fault, revealing that the basin–mountain junction region between the Pamir, the Tarim Basin, and the south Tian Shan Mountains is subject to accumulate strain and triggers stronger earthquakes. The Kuzgong fault plays an important role of transforming the crustal movements between the southwestern end of the STT and the north frontal MPT. The displacement field from geodetic observations could not find any evidence that the Puchang/Piqiang fault is a geological boundary of Kepingtage nappe. The modeled fault geometry and slip rate imply that three faults in the NOCTB are slipping at 6–10 mm/year along a decollement fault that dips at 19°–27° and is locked at a shallow depth of 6–10 km, whereas some other faults are undergoing a status of interseismic slip deficit.

Combining ocean numerical model and SAR imagery to investigate the occurrence of oil pollution, a case study for the Java Sea

IndoNACE is an abbreviation of Indonesian Seas Numerical Assessment of the Coastal Environment, a pilot study between Indonesia and Germany that combining analysis of oil spills from SAR images and numerical tracer studies from 3-D numerical model. Aim of this study is to understand the observed seasonal variations in marine oil pollution. Within this study, a visual inspection of all available SAR images is performed in order to generate maps of oil pollution occurrence in the Java Sea. Afterward, a set of numerical models is applied to trace back the origin of oil pollution. Our results showed that by analysing 706 ENVISAT ASAR images, the highest number of oil spills occurrence in the Java Sea was found during the transition monsoons, i.e. March to May and September to November. Assuming Marine Protected Area (MPA) of Seribu Islands as the end position of oil trajectory, we found that the origins of oil pollutions in that area were mostly from north and east.

Monitoring of the Spatio-Temporal Dynamics of the Floods in the Guayas Watershed (Ecuadorian Pacific Coast) Using Global Monitoring ENVISAT ASAR Images and Rainfall Data

The floods are an annual phenomenon on the Pacific Coast of Ecuador and can become devastating during El Niño years, especially in the Guayas watershed (32,300 km2), the largest drainage basin of the South American western side of the Andes. As limited information on flood extent in this basin is available, this study presents a monitoring of the spatio-temporal dynamics of floods in the Guayas Basin, between 2005 and 2008, using a change detection method applied to ENVISAT ASAR Global Monitoring SAR images acquired at a spatial resolution of 1 km. The method is composed of three steps. First, a supervised classification was performed to identify pixels of open water present in the Guayas Basin. Then, the separability of their radar signature from signatures of other classes was determined during the four dry seasons from 2005 to 2008. In the end, standardized anomalies of backscattering coefficient were computed during the four wet seasons of the study period to detect changes between dry and wet seasons. Different thresholds were tested to identify the flooded areas in the watershed using external information from the Dartmouth Flood Observatory. A value of −2.30 ± 0.05 was found suitable to estimate the number of inundated pixels and limit the number of false detection (below 10%). Using this threshold, monthly maps of inundation were estimated during the wet season (December to May) from 2004 to 2008. The most frequently inundated areas were found to be located along the Babahoyo River, a tributary in the east of the basin. Large interannual variability in the flood extent is observed at the flood peak (from 50 to 580 km2), consistent with the rainfall in the Guayas watershed during the study period.