Precise Three-Dimensional Deformation Retrieval in Large and Complex Deformation Areas via Integration of Offset-Based Unwrapping and Improved Multiple-Aperture SAR Interferometry:Application to the 2016 Kumamoto Earthquake

Conventional synthetic aperture radar(SAR)interferometry(InSAR)has been successfully used to precisely measure surface deformation in the line-of-sight(LOS)direction,while multiple-aperture SAR interferometry(MAI)has provided precise surface deformation in the along-track(AT)direction.Integration of the InSAR and MAI methods enables precise measurement of the two-dimensional(2D)deformation from an interferometric pair;recently,the integration of ascending and descending pairs has allowed the observation of precise three-dimensional(3D)deformation.Precise 3D deformation measurement has been applied to better understand geological events such as earthquakes and volcanic eruptions.The surface deformation related to the 2016 Kumamoto earthquake was large and complex near the fault line;hence,precise 3D deformation retrieval had not yet been attempted.The objectives of this study were to①perform a feasibility test of precise 3D deformation retrieval in large and complex deformation areas through the integration of offset-based unwrapped and improved multiple-aperture SAR interferograms and②observe the 3D deformation field related to the 2016 Kumamoto earthquake,even near the fault lines.Two ascending pairs and one descending the Advanced Land Observing Satellite-2(ALOS-2)Phased Array-type L-band Synthetic Aperture Radar-2(PALSAR-2)pair were used for the 3D deformation retrieval.Eleven in situ Global Positioning System(GPS)measurements were used to validate the 3D deformation measurement accuracy.The achieved accuracy was approximately 2.96,3.75,and 2.86 cm in the east,north,and up directions,respectively.The results show the feasibility of precise 3D deformation measured through the integration of the improved methods,even in a case of large and complex deformation.

A Comparative Study of Ionospheric Correction on SAR Interferometry—A Case Study of L’Aquila Earthquake

Synthetic Aperture Radar Interferometry(InSAR)has shown its potential on seismic deformation monitoring since it can achieve the accuracy of centimeter level or even the millimeter level.However,the irregular varieties of ionosphere can induce the additional phase delay on SAR interferometry,restricting its further application in high-precision deformation monitoring.Although several methods have been proposed to correct the ionospheric phase delay on SAR interferometry,the performances of them haven't been evaluated and compared.In this study,three commonly used methods,including polynomial fitting,azimuth offset and split-spectrum are applied to L'Aquila Earthquake to correct the ionospheric phase delay on two Phased Array type L-band Synthetic Aperture Radar(PALSAR)onboard the Advanced Land Observing Satellite-1(ALOS-1)images.The result indicates that these three methods can effectively correct the ionospheric phase delay error for SAR interferometry,where the standard deviations of the ionosphere-corrected results have decreased by almost a factor of 1.8 times for polynomial fitting method,4.2 times for azimuth offset method and 2.5 times for split-spectrum method,compared to those of the original phase.Furthermore,the result of the sliding distribution inversion of the seismic fault shows the best performance for split-spectrum method.

ADAPTIVE MODEL-BASED SCATTERING DECOMPOSITION OF POLARIMETRIC SAR INTERFEROMETRY

In this paper,a new decomposition method is proposed to solve the problems that vegetation component is overestimated and is not sensitive to directional scattering features with traditional polarimetric Synthetic Aperture Radar(SAR)decomposition.It uses a Polarimetric Interferometric Similarity Parameter(PISP)calculated from Polarimetric SAR Interferometry(PolInSAR)datasets to the scattering decomposition.The PISP is proposed to reveal the geometric sensitivity of SAR interferometry.It is defined by three optimized mechanisms obtained from PolInSAR datasets,therefore,it not only relates to the coherent scattering mechanism closely,but also sufficiently uses the phase and amplitude information.The PISP of building is high,and forest’s PISP is low.The proposed method uses the PISP as a judge condition to select different vegetation model adaptively.The decomposition results show the proposed method can effectively solve the vegetation ingredients overestimation problem.In addition,it is sensitive to the directional scattering.

Deriving glacier border information based on analysis of decorrelation in SAR interferometry

Variations of glaciers are important parameters for monitoring glacial change. Although optical remote sensing method can extract variations of glaciers effectively and accurately in cloudless regions, these variations are difficult to extract in cloudy conditions and bad weather. In this paper, a new method is presented, based on the decorrelation of repeat SAR interferometry, to extract the variations of glaciers. This method uses the decorrelation of the inland glacier＇s surface to extract the variation of glacier by comparing the coherence of the glacier and land cover in threshold values. For validation of this method, we compared classification results with that derived from TM images. An accuracy of better than 89% can be achieved if we consider the classification result from TM image as the ground truth. Results show that this method provides an effective way to identify icy areas from the coherent image.

Optimum selection of common master image for ground deformation monitoring based on PS-DInSAR technique

Considering the joint effects of various factors such as temporal baseline, spatial baseline, thermal noise, the difference of Doppler centroid frequency and the error of data processing on the interference correlation, an optimum selection method of common master images for ground deformation monitoring based on the permanent scatterer and differential SAR interferometry （PS-DInSAR） technique is proposed, in which the joint correlation coeficient is used as the evaluation function. The principle and realization method of PS-DInSAR technology is introduced, the factors affecting the DInSAR correlation are analysed, and the joint correlation function model and its solution are presented. Finally an experiment for the optimum selection of common master images is performed by using 25 SAR images over Shanghai taken by the ERS-1/2 as test data. The results indicate that the optimum selection method for PS-DInSAR common master images is effective and reliable.

Monitoring Crustal Deformations with Radar Interferometry: A Review

The crustal movements, probably motivating earthquakes, are considered as one of the main geodynamic sources. The quantitative measurements of ground surface deformations are vital for studying mechanisms of the buried faults or even estimating earthquake potential. A new space-geodetic technology, synthetic aperture radar interferometry (InSAR), can be applied to detect such large-area deformations, and has demonstrated some prominent advantages. This paper reviews the capacity and limitations of InSAR, and summarises the existing applications including some of our results in studying the earthquake-related crustal motions. Finally it gives the outlook for the future development of InSAR.

Bam earthquake: Surface deformation measurement using radar interferometry

On the 26th December 2003 an earthquake with MW=6.5 shook a large area of the Kerman Province in Iran. The epicenter of the devastating earthquake was located near the city of Bam. This paper described the application of differential synthetic aperture radar interferometry (D-INSAR) and ENVISAT ASAR data to map the coseismic surface deformation caused by the Bam earthquake including the interferometric data processing and results in detail. Based on the difference in the coherence images before and after the event and edge search of the deforma- tion field, a new fault ruptured on the surface was detected and used as a data source for parameter extraction of a theoretical seismic modeling. The simulated deformation field from the model perfectly coincides with the result derived from the SAR interferometric measurement.

Ground infrastructure monitoring in coastal areas usingtime-series inSAR technology:the case study of Pudong International Airport,Shanghai

Shanghai Pudong International Airport(PDIA),with its east side built along the coast with weak geological conditions,is prone to uneven foundation settlement due to the consolidation and compression of soil and erosion of coastal tides,affecting the safe operation of the airport.Therefore,it is crucial to conduct dynamic subsidence monitoring within the airport,especially in the runway area.29 scenes of ascending track Sentinel-1A radar images from August 2016 to June 2018 are selected to perform surface deformation inversion based on PS-InSAR and improved SBAS-InSAR for PDIA and its around coastal area.Through cross-validation,the reliability of the time-series InSAR technique for dynamic monitoring of surface deformation of coastal zone infrastructures is confirmed.The results show severely uneven settlement.By combining the monitoring results with the local geological and hydrological dataset,the driving factors of differential deformation of the infrastructures are analyzed,including stratigraphic geological conditions,ground loadings,foundation treatment methods,water erosion,and groundwater level changes.Finally,the time-series deformation characteristics and the causes of PDIA’s runway are emphasized based on the PS deformation results.This case provides a reference for the safety management of critical infrastructure in coastal areas using advanced InSAR technique.

Mapping land subsidence over the eastern Beijing city using satellite radar interferometry

Beijing City has suffered from groundwater-induced subsidence since the late 1930s and the over-exploration of groundwater could lead to subsidence as much as−12.0 cm yr−1.Previous studies on the ground deformation at Beijing City mainly focused on the period before the year of 2014 when a mega-engineering project was launched to reduce water shortage in Beijing.To study the most recent ground deformation,19 L-band ALOS-1 PALSAR images(June 2007–January 2011),24 C-band Sentinel-1 SAR images(June 2015–November 2016)together with 9 ALOS-2 PALSAR acquisitions(September 2014–February 2017)were analysed in this work.Levelling measurements were exploited to verify the ALOS-1-based time series InSAR(TS-InSAR)result while Sentinel-1 and ALOS-2 result were cross-verified with each other.Furthermore,the whole study area was divided into four sub-zones,and the result indicated that the subsidence rates over five townships,Cuigezhuan,Jinzhan,Liyuan,Songzhuang and Yanjiao were accelerating and more attentions should be paid.On the contrary,the town centre of Douge Zhuang township experienced a decreasing trend between these two temporal-periods.Additionally,the time series measurements with respect to five selected measurement points and the profile line along the subsidence hot spots were analysed.

TanDEM-X multiparametric data features in sea ice classification over the Baltic sea

In this study,we assess the potential of X-band Interferometric Synthetic Aperture Radar imagery for automated classification of sea ice over the Baltic Sea.A bistatic SAR scene acquired by the TanDEM-X mission over the Bothnian Bay in March of 2012 was used in the analysis.Backscatter intensity,interferometric coherence magnitude,and interferometric phase have been used as informative features in several classification experiments.Various combinations of classification features were evaluated using Maximum likelihood(ML),Random Forests(RF)and Support Vector Machine(SVM)classifiers to achieve the best possible discrimination between open water and several sea ice types(undeformed ice,ridged ice,moderately deformed ice,brash ice,thick level ice,and new ice).Adding interferometric phase and coherence-magnitude to backscatter-intensity resulted in improved overall classification per-formance compared to using only backscatter-intensity.The RF algorithm appeared to be slightly superior to SVM and ML due to higher overall accuracies,however,at the expense of somewhat longer processing time.The best overall accuracy(OA)for three methodologies were achieved using combination of all tested features were 71.56,72.93,and 72.91%for ML,RF and SVM classifiers,respectively.Compared to OAs of 62.28,66.51,and 63.05%using only backscatter intensity,this indicates strong benefit of SAR interferometry in discriminating different types of sea ice.In contrast to several earlier studies,we were particularly able to successfully discriminate open water and new ice classes.