Conference Agenda

Atmospheric water vapour effects represent one of the major error sources of repeat-pass Interferometric Synthetic Aperture Radar (InSAR), and limit the accuracy of InSAR derived surface displacements. The spatio-temporal variations of atmospheric water vapour make it a challenge to measure small-amplitude surface displacements with InSAR. In previous studies, several InSAR atmospheric correction models have been successfully demonstrated: (1) Ground based correction models such as those using Global Navigation Satellite System (GNSS) observations. Such correction models are limited by the availability (and distribution) of ground observations. (2) Space based correction models including those involving NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and/or ESA Medium Resolution Imaging Spectrometer (MERIS). They are sensitive to the presence of clouds and there might be a time difference between space based water vapour and radar observations. (3) Numerical Weather Model (NWM) based correction models including those using European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim and/or Weather Research and Forecasting (WRF). Similar to space based correction models, there might be a time difference between NWM and radar observations. Taking into account the inherited advatanges and limitations of GNSS, MODIS and ECMWF water vapour products, we present a global and near-real-time InSAR atmospheric correction model in this paper.

Tropospheric delays can be routinely retrieved from ground based GNSS arrays in all-weather conditions and also in real-time. We develop an Iterative Tropospheric Decomposition (ITD) interpolation model that decouples the total tropospheric delays into (i) a stratified component highly correlated with topography therefore delineates the vertical troposphere profile, and (ii) a turbulent component resulting from disturbance processes (e.g., severe weather) in the troposphere which trigger uncertain patterns in space and time. The decoupled interpolation model can then be employed to generate improved dense tropospheric delay maps compared with previsous GNSS-based models. In order to deal with areas with limited (or no) GNSS stations, we introduce the operational high resolution ECMWF (HRES-ECMWF, ~16 km), available near real-time, as well as MODIS near IR water vapour data whenever available as constrains of the ITD model, which makes the correction model globally available in all-weather conditions at any time for the first time. The applications of the ITD model to Sentinel-1 interferograms show that approximately 68%-78% of noise reduction can be achieved.

Foundation: National Science Foundation of China (No.41374077)

The first Control Source Extremely Low Frequency (CSELF) network has been built recently under the support of National Development and Reform Commission of China, which distributed in the Beijing Capital Area (BCA) and Southern Section of South North Seismic Belt (SNSB) in China for earthquake monitoring study. The network can be a part of earthquake stereoscopic monitoring system when it is combined with the satellite observation.

The network can not only receive the natural electromagnetic signal but also the artificial electromagnetic signal from the powered transmitter. A experiment of the system has been performed during 2016. The powered artificial electromagnetic signals are transmitted from 5:00 to 7:00 and from 17:00 to 19:00(GMT+8) every day. The signals at 4 different frequencies (216, 63, 12.3, 3.46 Hz) are transmitted and recorded. The natural electromagnetic signal from 1000Hz to 1000s are recorded continuously. The five electromagnetic components (North-South electric field :Ex, East-West electric field: Ey, North-South magnetic field: Hx, East-West magnetic field: Hy, and vertical magnetic field：Hz) are measured at each station of the network. The spectra of each component, impedance tensor, apparent resistivity and Impedance phase etc. are calculated using the similar software to MT data processing software. The original time series and the preliminarily processed results are transferred to the data center in the Institute of Geology, China Earthquake Administration through the CEA intranet. The further data processing and analysis are carried out in the institute for earthquake monitor study.

The artificial source electromagnetic signal is analyzed in both time and frequency domain. The adaptive filtering method was used to the raw time series data to extract the target frequency’s signal. The preliminary result showed that the amplitudes of the electromagnetic field of the artificial signals are obviously bigger than those of the natural signal. The power spectral density of the artificial signals are about 1-2 decades bigger than the natural signals for the same frequencies. The polarization characteristics of the electric and the magnetic field are studied for both source signals and the relationship between them are studied.,

In addition to the study in the feature of the artificial source electromagnetic field, we are making a tentative research on the relationship between the electromagnetic variation and the earthquake events. Some anomalies before and after Jinggu M5.9 earthquake (Dec.6, 2014) appeared in the observed data at Jinggu station for recorded natural signals. The spectrum variations appeared before and after Litang M5.1 earthquake (Sep. 23,2016) in the observed data at Jinggu station for recorded artificial signals.

Spaceborne InSAR has been a well-known established technique since the first Earth-observing SAR satellite ERS-1 was launched on 17 July 1991. Cross-track InSAR can produce a digital elevation model (DEM), and differential InSAR (DInSAR) is able to measure crustal movement and deformation caused by, for example, subsidence, landslide, earthquake, volcanic, and glacier flows. Today, Synthetic Aperture Radar (SAR) data are acquired globally from many modern satellites: Sentinel-1 operated by the European Space Agency, ALOS-2 operated by the National Space Development Agency of Japan, Radarsat-2 operated by the Canadian Space Agency, TerraSAR-X and TanDEM-X operated by the German Space Agency, and the COSMO-SkyMed constellation operated by the Italian Space Agency.

Gaofen 3 (GF-3), as a Chinese ocean surveillance satellite, was launched from the Taiyuan Satellite Launch Centre on 10 August 2016, and has been in operation since January, 2017. It carries a multi-polarized C-band SAR sensor and operates in 12 working modes, capable of imaging Earth’s surface from high-resolution (1 m) to extremely-wide-swath (650 km). The advanced technological criteria of GF-3 satellite ensure high-quality SAR images, providing an opportunity for Chinese SAR interferometry (InSAR) study.

This work aims to verify interferometric ability of the level 1 SLC data and discuss the optional InSAR processing strategy for GF-3 satellite. Sample SAR data in strip map mode were collected in Tianjin and Shanghai to the InSAR test operations, and post-processed precise orbits are used to improve the coregistration. First, the azimuth offsets between azimuth spectra sub-looking images are investigated to confirm the SLC focusing quality. Second, DEM assisted coregistration (Arikan, M., 2007) is compared with the traditional polynomial method. The DEM assisted coregistration relies on the precise orbit, and it shows better coherence for GF-3 InSAR processing even in smooth topographic areas. By comparing the GF-3 interferogram with S1A result in Shanghai, an area of about 1 x 1 km are confirmed to be subsidence. The test results verify that GF-3 SAR data are capable in InSAR application of measuring ground movements, while continuous data acquisition and near real time precise orbit are necessary for scientific and engineering application in the future.

Arikan, M., van Leijen, F., Guang, L. and Hanssen, R.F., 2007, November. Improved image alignment under the influence of elevation. In Proceedings of FRINGE.

3D SAR Tomography (TomoSAR) [1-4] and 4D SAR Differential Tomography (Diff-TomoSAR) [8-14] exploit multi-baseline SAR data stacks to create an important new innovation of SAR Interferometry, to sense complex scenes with multiple scatterers mapped into the same SAR cell. In addition to the 3-D shape reconstruction and deformation solution in complex urban/infrastructure areas [2,4], and recent cryospheric ice investigations [5], emerging tomographic remote sensing applications include forest scenarios [3,6,7], e.g. tree height and biomass estimation, sub-canopy topographic mapping, and even search, rescue and surveillance. However, these scenes are characterized by temporal decorrelation of scatterers, orbital, tropospheric and ionospheric phase distortion and an open issue regarding possible height blurring and accuracy losses for TomoSAR applications particularly in densely vegetated mountainous rural areas. Thus, it is important to extend characterisations of temporal decorrelation, orbital, tropospheric and ionospheric phase distortion.

We report here on 3D imaging (especially in vertical layers) over densely vegetated mountainous rural areas using 3-D SAR imaging (SAR tomography) derived from data stacks of X-band COSMO-SkyMed Spotlight and L band ALOS-1 PALSAR data stacks over Dujiangyan Dam, Sichuan, China. The new TanDEM-X 12m DEM is being used to assist co - registration of all the data stacks first. Then, atmospheric correction is being assessed using weather model data such as ERA-I, MERRA, MERRA-2, WRF; Linear phase-topography correction and MODIS spectrometer correction will be compared and ionospheric correction methods are discussed to remove tropospheric and ionospheric delay. Then the new TomoSAR method with the TanDEM-X 12m DEM is described to obtain the number of scatterers inside each pixel, the scattering amplitude and phase of each scatterer and finally extract tomograms (imaging), their 3D positions and motion parameters (deformation). A progress report will be shown on these different aspects.

This work is partially supported by the CSC and UCL MAPS Dean prize through a PhD studentship at UCL-MSSL.

[1] A. Reigber, A. Moreira, “First Demonstration of Airborne SAR Tomography using Multibaseline L-band Data,” IEEE TGARS, 38(5), pp.2142-2152, 2000.

[2] G. Fornaro, F. Serafino, F. Soldovieri, “Three Dimensional Focusing With Multipass SAR Data,” IEEE TGARS, 41(3), pp. 507-517, 2003.

[3] M. Nannini, R. Scheiber, R. Horn, “Imaging of Targets Beneath Foliage with SAR Tomography,” EUSAR’2008.

[4] F. Lombardini, F. Cai, D. Pasculli, “Spaceborne 3-D SAR Tomography for Analyzing Garbled Urban Scenarios: Single-look Superresolution Advances and Experiments," IEEE JSTARS, 6(2), pp.960-968, 2013.

[5] L. Ferro-Famil, C. Leconte, F. Boutet, X. Phan, M. Gay, Y. Durand, “PoSAR: A VHR Tomographic GB-SAR System Application to Snow Cover 3-D Imaging at X and Ku Bands,” EuRAD’12.

[6] F. Lombardini, F. Cai, “3D Tomographic and Differential Tomographic Response to Partially Coherent Scenes,” IGARSS’08.

[7] M. Pardini, K. Papathanassiou, “Robust Estimation of the Vertical Structure of Forest with Coherence Tomography,” ESA PolInSAR ’11 Workshop.

[8] F. Lombardini, F. Cai, “Evolutions of Diff-Tomo for Sensing Subcanopy Deformations and Height-varying Temporal Coherence,” ESA Fringe’11 Workshop.

[9] F. Lombardini, “Differential Tomography: A New Framework for SAR Interferometry”, IEEE TGARS, 43(1), pp.37-44, 2005.

[10] Xiang, Zhu Xiao, and Richard Bamler. "Compressive sensing for high resolution differential SAR tomography-the SL1MMER algorithm." In Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International, pp. 17-20. IEEE, 2010.

[11] F. Lombardini, M. Pardini, “Superresolution Differential Tomography: Experiments on Identification of Multiple Scatterers in Spaceborne SAR Data,” IEEE TGARS, 50(4), pp.1117-1129, 2012.

[12] F. Lombardini, F. Viviani, F. Cai, F. Dini, “Forest Temporal Decorrelation: 3D Analyses and Processing in the Diff-Tomo Framework,” IGARSS’13.

[13] Tebaldini, S., & Rocca, F. (2012). Multibaseline polarimetric SAR tomography of a boreal forest at P-and L-bands. IEEE Transactions on Geoscience and Remote Sensing, 50(1), 232-246.

[14] Huang, Y., Ferro-Famil, L., & Reigber, A. (2012). Under-foliage object imaging using SAR tomography and polarimetric spectral estimators. IEEE transactions on geoscience and remote sensing, 50(6), 2213-2225.

A 6.4-magnitude earthquake occurred near Pishan County on 3^rd July, 2015. The epicenter was recorded at 37.459°N, 78.154°E, according to the USGS. The moment tensor solution from the USGS indicates that the earthquake was the result of a reverse fault rupture on a south-dipping fault (United States Geological Survey, 2015). This region is affected by the south-north converging India-Eurasia collision. The continental collision of the India and Eurasia plates is associated with a relative convergence rate of 40-50 mm/yr (Liu J. et al., 2015, Liang and Gan, 2013). Northward underthrusting of India beneath Eurasia has led to the development of the west Kunlun orogens and generates numerous earthquakes which consequently make this area one of the most seismically hazardous regions on Earth (United States Geological Survey, 2015). Using Synthetic Aperture Radar interferometry (InSAR), we mapped the near-field surface displacement of this event to better characterize, the seismic source parameters. Analysis of the interferograms obtained during ascending and descending orbits of the Sentinel-1A satellite in IW mode and modeling using a two-step inversion strategy suggest that this event involved thrust motion on a south-dipping fault. The best-fit slip model in the inversion suggests that the majority of the coseismic slip was concentrated on a thrust fault with a strike of 112°, a dip of 25° and an average rake angle of 89°. The maximum slip was ~1.2 m at a depth of ~12.5 km. The accumulative seismic moment was up to 4.5x10¹⁸ N×m, which is equivalent to a magnitude of Mw 6.4. The InSAR results supplied near-field geodetic measurements and provided independent constraints on the source parameters of this rupture.

In April 25, 2015, a strong earthquake occurred about 80 kilometers northwest of Kathmandu, the capital of Nepal. The surface wave magnitude measured by China Earthquake Network Center is Ms8.1 (http://news.ceic.ac.cn/CC20150425141126.html), and the moment magnitude calculated by the Harvard University CMT based on the focal mechanism is Mw7.9 (http://www.globalcmt.org/CMTsearch.html). And the magnitude of the Nepal earthquake is similar to that of the Wenchuan earthquake on the eastern boundary of the Tibetan Plateau in May 12, 2008. After the main shock, two aftershocks greater than magnitude seven broke out. The earthquake affected many parts of Nepal, Tibet, India, Chinese Bangladesh, Bhutan, caused a total of more than 30000 casualties. The earthquake is a thrust type earthquake that occurred in the subduction zone of Himalaya since the 8 magnitude earthquake in 1934. Most areas of Nepal are located in the mountains region of southern Himalaya. Although located on a small fault basin, the capital Kathmandu is still on the hanging wall of the Himalaya fault zone. The special terrain and geomorphic conditions cause the loss of radar coherent signal energy, which is not conducive to InSAR deformation observation. In addition, because the earthquake occurred in the heavily forested areas, in order to reduce the effect of forest on electromagnetic waves, to achieve the monitoring of surface deformation caused by the earthquake, this paper uses ALOS2/PALSAR2 dual polarization data to study. The data is the synthetic aperture radar data acquired and processed by the PALSAR-2 sensor on the ALOS-2 satellite. The working band of the sensor is L band, and the polarization of the data used in this paper is HH/HV. In this paper, we use the synthetic aperture radar differential interferometry to obtain the partial coseismic deformation field of Nepal earthquake. The results show that when the revisit period is short, InSAR technology plays an important role in the region, provide the deformation information of high signal-to-noise ratio for the earthquake. The InSAR results revealed that the Kathmandu region was strongly uplifted during the earthquake, and the area is the maximum deformation area. Corresponding to it, large surface subsidence occurred on the north side of Kathmandu, and the deformation field is consistent with the characteristics of pure thrust type earthquakes. In addition, in order to make full use of the dual polarization characteristics of the data, on the basis of obtaining the seismic deformation, this paper studies the correlation of polarization images. It is found that the intensity of polarization image changes before and after the earthquake. And we make a simple evaluation of the building damage in Kathmandu area. The results show that the extreme value of seismic deformation occurs in the west of Kathmandu City, and the low value of the correlation of polarization image also appears in the area. Therefore, there exists spatial correlation between deformation and image correlation. The correlation distribution of different polarization images is not completely consistent, perhaps because of the different degree of damage to the building. It provides a new way to detect the seismic damage of buildings by using multi polarization images.

Outward growth and associated slip partitioning of the Tibetan Plateau is always a heated spot in the geosciences field worldwide. Dalbute fault zone is a rare transpressive fault along the northern margin of the Tibet, which plays an import role in absorbing the plateau’s northward expansion. And most importantly, the middle segmentation of the Dalbute fault zone is quite close to the Karamay City (less than 30 km in distance), a very important petroleum city in the Xinjiang Province, China. Therefore, the fault zone’s seismic activity has drawn the most consideration. GPS monitoring displays that, there occurs a sudden reduce (~5-8 mm/yr) in the northward velocities of the Tibet when cutting across the NE-SE-striking Dalbute fault zone. Previous researches attribute the rate drop to the fault’s over-thrusting. Except for the crustal thickening, we notice that the strike-slip directed displacement also takes part in the Tibet’s outward growth, like absorbing the northeastward extrusion of the Junggar Basin in the northern Tian Shan range. But this speculation lacks of quantification. Besides, whether the Heshituolegai basin, Tuoli basin, Baerluker Mountain are the termination tectonics of the Dalbute fault zone still remained unclear. We plan to apply radar images provided by the Dragon project to dig into these scientific questions. We use the Small Baseline PS-InSAR technique to quantify the slip rate field, faulting segmentation, seismic activity and the possible termination structures for the Dalbute fault zone. The slip partitioning mechanism between the strike-slip and thrusting submotions will also be constrained through the help of different flying azimuth (ascending and descending) of radar satellite and the verification from the campaign and permanent GPS measurements. This study is also a meaningful exploration for slip portioning mechanism among terminus of a transpressive fault arround the Tibet. This research will also provide some useful results for the future works on protecting against and mitigating earthquake disasters in the urban areas.

Synthetic aperture radar (SAR) can penetrate clouds and haze and obtain information on ground conditions at various times of day and under different weather conditions. Since the 1950s, SAR has been widely used in the fields of surface subsidence monitoring, topographic mapping, resource exploration, environmental remote sensing and military applications, etc. In recent years, with the rapid development of SAR technology, building change detection in SAR images has become a research hotspot, especially after an earthquake. SAR technology can overcome the effects of bad weather and obtain images rapidly after earthquakes.

Information on seismic damage to buildings in SAR images from different time phases, especially in post-earthquake SAR images, is easily disturbed by other factors that affect the accuracy of information discrimination. To identify and evaluate the distribution of seismic damage accurately and make full use of the abundant texture features in the SAR image, a method for texture feature change detection in SAR images based on the watershed segmentation algorithm is proposed in this paper. We calculate the omnidirectional texture values of 8 types of texture features based on gray level co-occurrence matrices (GLCMs) .Based on the optimization of texture feature parameters, the principal components of feature parameters are segmented using the watershed segmentation algorithm, and the feature object image is obtained. Conventional methods of change detection based on texture features usually take the pixel as the calculating unit. This method introduces the concept of object orientation and carries out the calculation of the difference map at the object level. Finally, the classification threshold values for different levels of seismic damage are selected, and the identification of building damage is achieved. Using ALOS data from before and after the 2010 Yushu earthquake as an example to verify the effectiveness of the method, the overall accuracy of the building extraction is 88.9%. Compared with pixel-based methods, methods based on gray features, and methods based on single texture features, it is shown that the proposed method is effective.

The method made a breakthrough in the following ways. (1)Taking the texture feature object as the unit used in the change detection algorithm, the concept of object orientation is introduced to change detection, which represents a break from the conventional change detection methods that use the pixel as the unit.(2) The watershed segmentation algorithm is applied to texture features based on statistics, which makes the segmentation more meaningful.

Earthquake is among the most catastrophic natural disasters which seriously threat people’s lives and property. Since most of deaths and injuries in earthquakes are primarily caused by building collapse, rapid and accurate detection of collapsed buildings in urban areas is vitally important to emergency rescue and damage assessment. However, it’s often difficult to achieve suitable pre-event SAR data due to the unexpectedness and suddenness of earthquakes.

The polarimetric SAR (PolSAR) is capable of measuring the amplitude and phase of backscattered signals in four combinations of polarization. Moreover, it is sensitive to the characteristics of target like shape, size, material, structure and orientation. These make it become a potential data source to researches on building collapse extraction by using only post-earthquake SAR image. Based on this, many researches have been conducted (Li et al., 2012; Zhao et al., 2013). One issue existing is the misidentification of collapsed buildings and intact buildings which are not parallel to the SAR flight path since the scattering mechanism of the oriented intact buildings change to volume scattering dominant and reflection asymmetric. To eliminate this deficiency, the optimum polarimetric contrast enhancement (OPCE) method (Yang et al., 2000) is introduced to identify the collapsed buildings (Zhang et al., 2015). Using this method, the contrast of the intact buildings and collapsed buildings is enhanced through rotating the transmitting and receiving polarimetric antenna states. However, polarimetric information is not considered when applying this method. Yang et al. (2004) extended the OPCE method and combined it with the entropy and two polarimetric similarities, i.e. generalized optimum polarimetric contrast enhancement (GOPCE).

In this paper, we propose a new building collapse identification method based on the GOPCE method and the corresponding process framework is also presented. Moreover, the homogeneity feature of the grey level co-occurrence matrix (GLCM) is introduced to modify the GOPCE method. The case study is Yushu county where a Ms 7.1 earthquake occurred on April 14th, 2010. One post-earthquake Radasat-2 PolSAR image acquired on April 21th is utilized to test the proposed methods. By comparing with the OPCE and GOPCE methods, the GOPCE combined with homogeneity method performs better and more collapsed buildings are correctly detected. The misclassification of collapsed buildings and oriented intact buildings is also reduced. Experiments show that our proposed method can meet both time efficiency and detection accuracy requirements of earthquake rescue.

Acknowledgement

This work is supported by the Dragon 4 Cooperation Program [32244] and the National Natural Science Foundation of China [41571337].

The 2008 Wenchuan earthquake resulted in thousands of geo-hazards including landslides, and debris flows. In this paper, we will attempt to use time series InSAR techniques to monitor the activities of two post-seismic geohazards, namely the Daguangbo landslide and the Wenjiagou debris flow.

Caused by the 2008 Wenchuan earthquake, the Daguangbao landslide is one of the largest landslides in the world. The whole mountaintop collapsed in the 2008 earthquake, leading to a height change up to 500 meters. TanDEM-X data is used to generate a high resolution post-seismic DEM in this paper. The high gradients of topographic errors and the decorrelation caused by vegetation in mountainous areas make the processing of Tandem-X data challenging. To solve this, we propose a re-flattening iterative method to generate a post-seismic DEM. 15 Sentinel SAR images were acquired during March 2015 to March 2016. The time series displacements of the Daguangbao landslide are obtained using our advanced InSAR TS+AEM method with the Sentinel-1 SAR images and high-resolution post-seismic TanDEM-X DEM. Four active zones are observed with a maximum displacement rate of 8 cm/year, suggesting that this landslide is still active even 8 years after the earthquake.

The Wenjiagou debris flow was the second largest landslide in the Wenchuan earthquake. The volume of the deposits is determined by comparing the post-seismic DEM derived from tandem-x data and the pre-seismic SRTM. In this site, a complex project has been set up to prevent potential debris flows by separating water and mud. Our InSAR results from Sentinel-1 observations (2015~2016) suggest that the source area of this debris flow is still active due to steep topography and rainfalls, whilst the project site and its downstream are stable. The impacts of this debris flow prevention project are to be discussed.

The Red River Fault (RRF) is a major strike-slip fault running about 1000 km from southeast Tibet to South China Sea. As a result of the collision of the India and Eurasian plates, the fault is complicated, the average displacement rate is 2 to 5 mm/year and decreases from north to south. Investigation of the fault deformation information is significant to study its dynamic pattern, however, the large topography variations make it difficult to collect ground observations using GNSS.

Interferometric Synthetic Aperture Radar (InSAR), as a valued geodetic tool, has been applied in mapping crustal deformation at the scale of hundreds of kilometres with a high spatial resolution (e.g. a few metres to tens of metres) over the past two decades. Sentinel-1A was launched in April 2014, Sentinel-1B in April 2016 and both have been collecting data routinely. In the RRF zone, Sentinel-1 data are being acquired every 12/24 days with both satellites. The small temporal baseline, together with small spatial baselines (i.e. orbital separations) greatly improve interferometric coherence at C-band. In addition, Sentinel-1 images cover a wide footprint, 250 km from near to far range in Interferometric Wide Swath (TOPS) mode. Since October 2014, there have been over 400 Sentinel-1 images collected from 4 descending and 3 ascending tracks covering the RRF zone. Also, over 1500 ALOS-1 images collected between 2007 and 2011 are available in this region, and ALOS-2 data are being systematically acquired since 2014. The long wavelength (L-band) of ALOS-1/2 ensures good coherence. All the above-mentioned factors make it now possible to use InSAR to monitor slow-slip crustal deformation in this region.

The SAR data are interferometrically processed using our automatic processing chain based on the InSAR Scientific Computing Environment (ISCE) software. The variable climate in RRF zone challenges InSAR observing and processing, we calibrate the interferograms for atmospheric water vapour using high-resolution ECMWF products. Finally, time series analysis is performed to determine the interseismic deformation rate of the RRF using the in-house InSAR time series inversion package (InSAR TS + AEM, Li et al. 2009). It includes an advanced network correction approach for residual orbital correction and an atmospheric phase screen estimation with a priori deformation model. The InSAR measurements will be discussed to implicate future seismic hazard in the RRF zone.

Li, Z., Fielding, E. J., Cross, P. 2009: Integration of InSAR Time-Series Analysis and Water-Vapor Correction for Mapping Postseismic Motion After the 2003 Bam (Iran) Earthquake. IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, 9.

Conventional dInSAR techniques have been frequently used in the past for deformation mapping including the mapping of landslide activities. However, several difficulties arise when attempting to apply dInSAR in areas with steep slopes and rugged topography, high humidity and dense vegetation cover such as over the Three Gorges Region. In addition to these difficulties, it is shown that the maximum detectable displacement gradient of dInSAR can be exceeded in our case study area even when using the highest resolution TerraSAR-X data.

A sub-Pixel Offset Tracking approach (sPOT) is applied to monitor slow-moving landslides in densely vegetated and steep terrain. This approach is shown of being capable of measuring centimetre-level landslide rates by using natural scatterers in densely vegetated terrain in line with measurements derived from corner reflectors.

The potential and limitations of TSX-ST (TerraSAR-X Staring Spotlight) data on measuring surface deformation using dInSAR and offset tracking techniques are assessed through case studies on the southern banks of the Yangtze River, in particular whether the improvement of the resolution of Staring Spotlight mode helps to address some of the issues that were encountered previously.

In addition, we show how the TanDEM-X Coregistered Single look Slant range Complex (TDX CoSSC) data can be employed to produce a 6 m resolution DEM. The impact of using different sources of DEMs is then assessed on deformation measurements via offset tracking and dInSAR.

Finally, the relationship between landslide occurrence and possible hydrological driving factors is assessed to infer possible landslide mechanisms.

This work was partially supported by the China Scholarship Council (CSC) and UCL through a PhD studentship at UCL-MSSL.

For decades, crustal motion and surface deformation processes have been investigated with differential SAR Interferometry. This geodetic technique can lead to very good estimations of ground movement, when applied to co- and interseismic processes, land subsidence phenomena, landslides or volcanic motion with significant deformation magnitudes. However, its application still presents a challenge considering wide-scale, subtle ground movement that is hardly measurable with InSAR in the presence of often indistinguishable orbital, atmospheric or topographic noise.

Different SAR sensors such as ESA’s ERS-1/2, ESA’s Envisat ASAR, ESA’s Sentinel-1 and JAXA’s ALOS PALSAR are tested in this study to assess their capability to achieve the required accuracy in the interferometric phase for monitoring slow, low magnitude surface movements (in the low mm-level). This applies to, for example, observations of glacial isostatic uplift, interseismic strain accumulation or small subsidence processes.

The range of possible error sources, such as residual orbital artefacts or atmospheric water vapour, require to be addressed in order to allow the extraction of any subtle deformation signals. Their elimination from interferograms present the biggest challenge due to their ‘masking’ characteristic.

This study advances currently known time series inversion methods for deformation monitoring and mapping of natural hazards. Results from two InSAR time series approaches are compared. On the one hand, this comprises an improved time series inversion package developed at the University of Glasgow and Newcastle University (“InSAR TS+AEM”, Li et al. 2009), based on the more classical and well established Small Baseline approach. This includes an advanced network correction approach for residual orbital effects and an atmospheric phase screen estimation with an a priori deformation model. On the other hand, a new technique is tested for reducing image artefacts and to derive a time series from InSAR data: A combined approach of Principal Component Analysis and Independent Component Analysis aims to separate the desired ground deformation signal from unwanted noise in interferograms. The idea is to take advantage of the signals’ different spatial and temporal characteristics and to decompose the mixtures into statistically independent components in space and time to filter out geophysical deformation.

Li, Z., Fielding, E. J., Cross, P. 2009: Integration of InSAR Time-Series Analysis and Water-Vapor Correction for Mapping Postseismic Motion After the 2003 Bam (Iran) Earthquake. IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, 9.

Damxung area is the place where strong earthquakes happen frequently, and the former studies have shown that there is a close relationship between strong earthquakes and active faults in this place, so it is necessary for us to study the distribution, geometric structure and motion characteristics of the faults if we want to know the initiation mechanism and seismogenic environment of the earthquakes. In this paper, by using a wide range of remote sensing data such as Landsat-7 ETM+, ALOS, GF-2, Sentinel-1 and DEM data, and utilizing a wide variety of image enhancement technology such as multiband color composite, PCA and ratio analysis based on these data, active fault information was extracted and the remote sensing interpretation marks about active faults were established, and finally, we displayed the the distribution and activity of the Yadong-Gulu fault and the Jiali fault in the study area. Our results have shown that: the Yadong-Gulu fault mainly consisted of normal faults and strike slip faults, and it could be divided into three parts. The north part of the Yadong-Gulu fault had direction toward NNE with part of it buried, and normal faults developed associating with strike slip faults. The middle part of the Yadong-Gulu fault had direction toward NE, and the fault was exposed, and the main faults of it were sinistral strike-slip normal faults. The south part of the Yadong-Gulu fault had a direction toward NNE, which then changed to NS on south, and the fault was partly buried with many secondary faults around it, and it mainly consisted of dextral strike-slip normal faults which had formed many graben basins. The Jiali fault was buried partly in the study area and could be divided into two branches, and it was dextral strike-slip normal fault. The wide existence of fault triangular facet, pull-apart basin and river break in the remote sensing images revealed that this area had a tectonic background characterizing by stretch and twist, which was mainly governed by upwelling movement on vertical direction and extension movement on horizontal direction of the middle Tibetan Plateau which was caused by the subduction of the India Plate. The remote sensing interpretation in this paper reflected the current characteristics of faults’ activities in the study area, and the characteristics of these activities had a close relationship with the earthquakes. What’s more, the results of this study also showed that enhancement processing upon remote sensing image could highlight some specific landforms and geological structure information, and the remote sensing image had unparalleled advantages compared with field geological investigation, and remote sensing technology had a bright prospect in geological investigation and geological disaster monitoring.

Abstract: The Qinghai Tibet Plateau is the world's youngest and most active plateau, due to the collision between the India plate and the Asian plate led to most of the region's fault zone is active, a lot of small earthquakes between Mw5.0 and Mw6.0 occurred every year, these small earthquakes can cause ground subsidence, influence in fault state. Based on the ENVISAT satellite data, the surface deformation caused by small Tibet earthquake were analyzed obtain the coseismic deformation field, comparative analysis the surrounding areas of land subsidence caused by the small earthquakes, and use the GPS data to verify, results showed that there was high consistency between the SAR data acquisition deformation and GPS measurement result.

Keywords: coseismic deformation, small earthquake, surface deformation

1. research status

The Qinghai Tibet Plateau is the world's youngest and most active plateau, with an average altitude of more than 5000 m, the main structural features currently are the results of the India plate and the Asian plate collision since the 50-60Ma. Because the impact time is new, tectonic collision and orogeny of the intact are save well, and many continental dynamic process after collision are continues, so the Tibetan Plateau is the most ideal place for the new structure research.

Qinghai Tibet Plateau is a strongly rising block surrounded by the surrounding active faults. The surrounding fracture surface tend to plateau interior, thus formed in the mountains around the edge of the plateau to plateau lowland obduction "coronary morphology structure". The type of peripheral plateau active tectonics dominated by fracture structure, its basic characteristics are the reverse fault internal fault dip plateau. The southern boundary of the Tibetan Plateau is the main boundary fault zone in Himalaya, the west adjacent to the Yika La Kunlun fault zone and the Pamir Plateau; the northern boundary along the northern margin of West Kunlun fault zone, the Altun fault and the northern margin of Qilian Mountains fault zone, curving to six mountain fault zone; the Eastern boundary along the Longmen Mountain Fault Zone, An’ninghe fault and Xiaojiang Fault with the extension of the twists and turns.

Select the Lhasa block as the study area, analysis the surface deformation of Mw5.0~6.0 earthquake in the study area, using the traditional two track difference method for data processing, the basic idea is to generate two pass interference using two images before and after of the surface change experimentation area, topographic information removed from the interferogram. Then can get the deformation information. The basic process is needed before the earthquake and after the earthquake SAR data and DEM data, the data before the earthquake as the main image formed interferogram with the post earthquake data, simulated interferogram using DEM, the simulated interferogram is subtracted from the interferogram by SAR data, then form the differential interferogram. The advantage of this method is that it does not need the phase unwrapping of the interferogram to avoid the difficulty of understanding, but also can obtain the precision of the deformation results.

2. research significance

The Qinghai Tibet Plateau is an earthquake prone area, especially some small earthquakes (Mw5.0~6.0). These earthquakes release the earth's crust stress, reduce the probability of strong earthquakes in the fault, and effectively alleviate the seismic risk in the region. At the same time, through the study of the mechanism of the occurrence of small earthquakes, we can obtain the geophysical parameters. It provides valuable information for the assessment of regional seismic hazard.

Study on deformation field of small earthquakes in Lhasa block since 90s of last century using InSAR technique. In March 24, 2010 the Tibet area (N32.51 degrees, E92.83 degrees) a Mw5.6 earthquake as an example, using the traditional differential method pass interference to obtain the coseismic deformation field of the earthquake, coseismic interferograms obtained using multiple sets of different seismic data, through data analysis to obtain the coseismic displacement of the interferometric phase, clear surface displacement caused by the earthquake. At the same time, the use of GPS data to verify the accuracy of the result, inverse the fault parameters based on coseismic deformation field and GPS data, to obtained the detailed parameters of fault, which can provide the basis for the subsequent study of fault and the mechanism of earthquake.

This work will report the studies undertaken in the past year, which is aimed to developing viable methods and techniques for detecting anomalies from space and terrestrial electromagnetic data that are observed by the SWARM satellite and the network of the Control Source Extremely Low Frequency (CSELF) in China and investigating the correlation between anomalies and earthquakes. We have developed an effective algorithm for detecting anomalies from time series data and evaluated them over benchmark datasets, as well as preliminarily on electromagnetic data observed by the Swarm satellites and by the CSELF. We will present a number of issues related to the Swarm satellite data, the methods required to process the data, and finally present a comparative case study of the Jingpu earthquake using the Swarm and CSELF data.

InSAR techniques provide researchers a set of tools for topographic mapping, as well as for monitoring deformations on the Earth surface. In Dragon-1 and Dragon-2, our focus was on DEM generation and surface motion estimation with medium resolution InSAR. Since Dragon-3, SAR datasets of high spatial and temporal resolution (TerraSAR-X, COSMO-SkyMed) are available and with the availability of Sentinel-1 data, a global time-series coverage is now reality.

Topographic mapping and surface motion estimation with spaceborne SAR sensors are the main topics of the Dragon-4 project "Multi-baseline SAR processing for 3D/4D reconstruction (id 32278-2)” under the framework of THREE- AND FOUR-DIMENSIONAL TOPOGRAPHIC MEASUREMENT AND VALIDATION (id 32278). In Dragon-4, we work on different test sites investigating the following four topics:

1. Topographic mapping with SAR. We developed a maximum a posteriori (MAP) estimation method for multi-baseline InSAR assisted by StereoSAR. According to Bayesian theory, the combination of StereoSAR and InSAR for topographic mapping can be viewed as update of the StereoSAR DSM with InSAR phase observations. At the same time, the StereoSAR DSM is also a constraint to InSAR phase observations, which can solve the problem of elevation ambiguity and avoid phase unwrapping problems. The Mount Song has been selected as the test area, which is one of the five sacred mountains of China. The experimental result shows that there is neither systematic error nor large data voids in MAP estimated DSM and the standard deviation of height error σ_h of MAP estimated DSM is less than 10 m with respect to the photogrammetric DEM for the whole area, while in plain areas σ_h is about 5 m.

2. Urban subsidence analysis. SAR systems can measure distances and movements with high precision. Using for example PS-InSAR, deformations can be estimated with a very high precision. The long-term surveillance of urban subsidence and the infrastructure stability in Shanghai is our major research goal since Dragon-1. With data starting from ERS-1, over ENVISAT ASAR, ALOS PALSAR, up to modern systems like TerraSAR-X, COSMO SkyMed, PALSAR-2, and Sentinel-1, we continuously monitor the subsidence over Shanghai for far over a decade now. The combination of this data and the analysis of the continuous deformation is still on-going. Remarkably, the PS-InSAR precision stays stable over time even using different sensors.

3. Coseismic displacement from Sentinel-1 TOPS data. Terrain Observation by Progressive Scans (TOPS) mode from the Sentinel-1A/B satellites provides up-to-date high-quality Synthetic Aperture Radar (SAR) images over a large coverage, making it widely applied to earthquake studies. Recent work focuses on generation of co-seismic displacement of large earthquakes from Sentinel-1 TOPS images. However, many small/deep/offshore earthquakes have relatively smooth ground displacement disturbed by strong atmospheric influence. The coherence images spanning these earthquakes maybe not desirable e.g. due to the complex topography. Therefore, methods to derive such smooth co-seismic displacements from time-series is needed. We developed a new Sentinel-1 TOPS images analysis strategy with applications to earthquakes occurred recently in China.

The reconstruction of topographic information and their changes in the context of our dynamic Earth is one of the main applications of photogrammetry and remote sensing. With advancements in sensor technology and data processing, three-dimensional information can be retrieved in unprecedented precision. With the release of the TanDEM DEM, the DLR released the most precise world-wide DEM, an invaluable data set for numerous applications. The global availability and the high precision are proof of the extra-ordinary capability of Synthetic Aperture Radar (SAR) interferometry (InSAR) for 3D measurements.

With the SAR geodesy concept of the DLR, the radargrammetric measurements are having a comeback. Thanks to the high orbit-precision of TerraSAR-X and TanDEM-X, and by using collateral data to correct the atmospheric delay, absolute 3D positioning precision within a few centimeters is nowadays possible. However, there are several limitations for reaching the maximum precision in SAR geodesy and interferometric SAR. Therefore, a deeper understanding of the underlying error sources is necessary to fully use the potential of the aforementioned methods.

With the rapid developments in photogrammetric computer vision the multi-view photo-consistency measures for dense and accurate 3D reconstructed evolved and based on developments like semi-global matching for multi-view-stereo, photogrammetry reaches relative height precisions in the centimeter domain, comparable to or even outplaying LiDAR.

In this context, the Dragon-4 project “Topographic Mapping - Validation (32278-1)” is working on the three- and four-dimensional high-precision measurement using SAR and photogrammetry. Currently, we are working on three main objectives:

1. Validating the final version of the TanDEM DEM in test sites in China and Germany
2. Demonstrating the high absolute precision of SAR geodetic measurements with tests conducted in Wuhan
3. Showing the achievable precision of dense image matching in photogrammetry

With the recent progress in the three-dimensional measurement precision of photogrammetry and SAR, four-dimensional time-series measurements for surface motion estimation can become possible offering alternatives to differential interferometry based methods. This is especially beneficial, because these methods can be used as supplement to differential interferometry and derived methods, because they are especially applicable for fast surface motions that are otherwise especially difficult to be measured.

In this paper, we provide a better understanding of temporal decorrelation of tropic forest from TropiScat in various timescales. TropiScat is a ground-based campaign operated at the Paracou field station, French Guiana since October 2011, which allows gathering the tomogram of the forest in all polarizations at P band with a temporal sampling of 15 minutes . To analyze the temporal decorrelation we evaluate the intensity and coherence of the signal array of 15 transmitting and receiving antenna pairs. The vertical distribution of temporal coherence is obtained by comparing two tomograms acquired at different times. To further understand the temporal decorrelation, we evaluate the coherence between tomogram obtained from antenna pairs of different times and that of the same time. The procedure to produce the tomogram and different tomogram processors will be discussed in the final paper .

Terrain Observation by Progressive Scans (TOPS) mode from the Sentinel-1A/B satellites provides up-to-date high-quality Synthetic Aperture Radar (SAR) images over a large coverage, making it widely applied to earthquake studies. Recent work focuses on driving coseismic displacement of large earthquakes from a pair of TOPS images. However, many small/deep/offshore earthquakes have relatively smooth ground displacement disturbed by strong atmosphere influence. The coherence images spanning these earthquakes maybe not desirable either duo to the complex topography. Therefore, methods to derive such smooth coseismic displacement from time-series analysis is needed. Here we present a novel Sentinel-1 TOPS images analysis strategy with applications to a few earthquakes occurred recently in China.

First is the 5 February 2016Mw 6.4 MeiNong earthquake that occurred in Taiwan. For this case, we take a modified spectral diversity method for coregistration of TOPS images to get a smooth interferogram in which the obvious phase jumps are well corrected. Then we take time-series analysis using TOPS images acquired before and after the earthquake to improve the derived coseismic displacement. The results are validated with GPS data near the epicenter area.

Another case includes a series of M<7 earthquakes occurred on the Qinghai-Tibet plateau, To study these earthquake, we collect time-series Sentinel-1 TOPS images acquired before and after earthquakes. We improve the time-series TOPS data processing chain to estimate the coseismic displacement on detected persistent scatters. Our results show that the temporally uncorrelated atmospheric signal can be largely reduced and the subtle coseismic displacement signal can be derived more precisely than single interferogram.

Synthetic Aperture Radar Interferometry (InSAR) is a powerful tool for large-area topographic mapping due to its capability of all-time all-weather imaging and high sensitivity to terrain relief. However, there is an inherent contradiction between geometric decorrelation and sensitivity of height measurement for topographic mapping with a single InSAR pair. A normal baseline of proper length is required to keep a balance between the two issues. A promising solution to this problem is the so-called multi-baseline InSAR analysis. The basic principle of multi-baseline InSAR is to derive an optimal height estimate by joint analysis of multiple phase measurements from several interferograms with different normal baselines. Compared with single-baseline InSAR, the major benefit of using multi-baseline observations is the possibility of exploiting redundant topographic phase observations with different height of ambiguities to improve the accuracy of phase unwrapping, or even avoid phase unwrapping.

In this study, after the analysis and discussion of the probability distribution of interferometric phase, we propose a maximum likelihood (ML) estimation method assisted by SRTM DEM data for multi-baseline InSAR topographic mapping. Based on our method, a spaceborne data multibaseline InSAR processing flow is established. In order to well adapt it to the repeat-pass interferometric pairs, the processing flow integrates the atmospheric effect correction method to improve the reliability of multi baseline estimation. The simulation experiments were designed to test the effectiveness of the maximum likelihood height estimation method and atmospheric effect correction method. The proposed multibaseline InSAR processing flow was applied in ALOS/PALSAR dataset covering Mount Tai area, China. The accuracy of resultant DEMs at spatial resolution of 20 m is evaluated by using a standard Chinese national DEM of scale 1:10,000 as reference. The results show that multi-baseline InSAR can improve DEM accuracy compared with single-baseline case. The quality of multi-baseline InSAR DEM can meet the American DTED-2 standard.

As the global sea level rises, there is increased concern about the growing urbanization of the low-lying deltaic coastal regions, and the related coastal hazards. Furthermore, the local relative sea-level rise can be significantly affected by vertical ground motions, either due to natural processes (e.g., global isostatic adjustment, tectonics, sediment consolidation and compaction, upstream sediment load reduction) and to human activities (e.g., groundwater extraction, land reclamation, building construction and consolidation). Deformation phenomena can be in the same order of magnitude (or greater) than climate-induced sea level rise. However, coastal ground motions are in practice often poorly known, and in many cases, little information is available about the patterns and time evolution of ground motion. It is, therefore, worth to monitor coastal delta regions through advanced Earth Observation (EO) systems that are capable detecting the ongoing surface deformation phenomena, recovering their spatial extent on the ground and following their temporal variability. This is beneficial for the subsequent interpretation of natural/anthropogenic processes causing surface motion.

The activities of this present Dragon IV project are mostly focused on the analysis of modification processes that characterize two important Delta river areas in China: the Yangtze and the Pearl River Deltas. Both delta regions are significantly affected by sea-level rise and natural/anthropogenic deformation phenomena, making it clear the need of extended analyses for a better understanding of the mechanisms responsible for the observed surface modifications, and for the planning of actions devoted to risk prevention for populations living in coastal areas.

More specifically, the aim is to retrieve long-term displacement time-series from EO data, specifically satellite Synthetic Aperture Radar (SAR), of the investigated areas through advanced differential interferometric synthetic aperture (DInSAR) techniques, as well as to complement DInSAR results with information derived from GPS/leveling campaigns with the aim to perform sound and extended geophysical analyses, and coastal erosion or accretion rates, which will be obtained by jointly exploiting archives of SAR data and the new generation of optical remote sensing systems.

In order to evaluate the combined risk of sea level rise, storm surges, and ground subsidence, the availability of high-resolution digital elevation models (DEM) of monitored coastal areas is mandatory. Added-value EO data products, such as the updated DEMs of coastal areas subject to sea-level rise, the time-series of terrain displacement, mean displacement velocity maps, and time-series of SAR backscattering maps, will be obtained by exploiting archives of SAR data with different levels of spatial resolution spanning a long time interval of about 20 years since the beginning of 2000s to 2020.

During the first year of this present D4 project, some preliminary activities have been conducted for processing Sentinel-1 data on both Delta regions by using different DInSAR tools in such a way to perform combined Small Baseline Subset (SBAS) [1] and Permanent Scatterers (PS) [2] analyses. Sentinel 1 time-series span about last three years. However, in order to have the historical perspective of the deformations occurring in the two areas, a few experiments have been carried out to obtain deformation maps covering the time lapse between 2002 to present days using (when available) ENVISAT and Cosmo-SkyMed SAR acquisitions. The latter are worth to complement the analyses performed over the last four years over the reclaimed lands of the Shanghai city [3].

The availability of updated DEMs of the areas subject to sea-level rise (and/or flooding) is also of fundamental importance. It is worth emphasizing that nowadays, global coverage catalogues of DEMs imaging most of the Earth’s surface are available (such as the ones recovered through the Shuttle Radar Topography Mission in 2001) and also new SAR missions have recently been specifically deployed (such as the TanDEM-X mission [4]) for the generation of updated profiles of the terrain. During the first months of activities, a DEM of the coastal area of the Shanghai megacity has been generated by applying the method [5]-[6] based on the use of bistatic SAR data acquired by the TerraSAR-X and TanDEM-X sensors. The analysis of the generated DEM, as well as its use for the application of flooding models in the Shanghai area, is still in progress.

The preliminarily results of the activities performed during the first year of this D4 project will be analyzed and properly integrated with the results of other investigations, for instance by performing SAR Tomography [] experimentations over Delta river cities.

[1] Berardino, P., G. Fornaro, R. Lanari, E. Sansosti (2002), A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms, IEEE Trans. Geosci. Remote Sens., 40(11), 2375-2383.

[2] A. Ferretti, C. Prati, and F. Rocca (2001), Permanent scatterers in SAR interferometry, IEEE Trans. Geosci. Remote Sens., 39(1), 8-20.

[3] Zhao Q., Pepe A., Gao W., Lu Z., Bonano M., He M.L., Wang J., Tang X. (2015) A DInSAR investigation of the ground settlement time evolution of ocean-reclaimed lands in Shanghai, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 1763-1781.

[4] Krieger G., Moreira A., Fiedler H., Hajnsek I., Werner M., Younis M., Zink M. (2007) TanDEM-X: A satellite formation for high-resolution SAR interferometry. IEEE Tans. Geosci. Remote Sens., 45, 3317-3340.

[5] Kubanek J., Westerhaus M., Schenk A., Aisyah N., Brotopuspito K., Heck B. (2015a) Volumetric change quantification of the 2010 Merapi eruption using TanDEM-X InSAR. Remote Sensing of Environment, 164,16-25.

[6] Kubanek J., Richardson J., Charbonnier S., Connor L. (2015b) Lava flow mapping and volume calculations of the 2012-13 Tolbachik, Kamchatka fissure eruption using bistatic TanDEM-X InSAR. Bulletin of Volcanology, 77,1-13.

Mean sea-level (MSL) is rising worldwide, and correlated changes in the ocean tides are also occurring; the combination of both may increase or diminish total sea-levels (TSL) in a complex manner. Higher ambient water levels can increase the flood risk to coastal zones, more so under storm surge episodes. However, even without a storm event, increasing MSL coupled with increasing tides may lead to more nuisance flooding, or flooding events produced from the coupling of high tides and rising MSL. Hong Kong is particularly sensitive to changes in water levels, as it has a large population with much of its infrastructure near the shore. Furthermore, land subsidence and past reclamation projects may have induced changes in resonant and frictional properties of the tides, which may yield non-uniform spatial changes in water levels throughout Hong Kong. In this work, the historical full-spectrum tidal variability at a number of coastal tide gauges in Hong Kong is determined, and the past behavior of the relations between major tides and shallow-water overtides is examined to understand the changes in friction and resonance and the implication for future water level spectra in the region. Additionally, the locations surrounding each tide gauge is examined via remote sensing images from the Sentinel series of earth observing satellites, and past and present images are contrasted to determine changes to coastal morphology, and compared to the frictional determinations of the ground based gauges and to the history of land subsidence and land reclamation in the region.

In recent years, quantitative measurements of significant wave height (SWH) by the use synthetic aperture radar (SAR) and radar cross section (RCS) methods has been proven effective in different approaches without prior knowledge of wind information. An update of an existing simple semi-empirical algorithm, aided by parameterized filtering of RCS, is presented in this study to address the issue of how the RCS values depend on empirical algorithms in different systems, using the wavelength value of the dominant wave peak and the relationship function of RCS to incidence angle derived from the SAR image. To determine the wavelength of dominant wave peaks, we implement a contrast limited adaptive histogram equalization (CLAHE) method, based on a parameterized image texture analysis. An adaptive filtering method ensures a statistically robust determination of the filtering parameter, resulting in a higher contrast SAR image that allows more efficient dominant wave peak identification, as clearer wave patterns can be revealed by higher image contrast level. We also propose a preliminary empirical update for the backscatter cross-section to incidence angle function for vertical polarization in a 5.405 GHz SAR system. Standard meteorological buoy data from National Buoy Data Center (NDBC) is used in development of the empirical model through validation. This research employs Level-1 GRD Sentinel-1A SAR images from 2015 to early 2017 that look at Hawaii and the central part of the west coast of the United States of America, selected to represent deep to shallow water depth and river influenced estuaries. However, extreme sea states are not considered due to the limitation of the image repository and buoy data availability. Beside the two analysis methods described above, additional detailed analyses are conducted on the sea state relation to the velocity bunching mechanism, based on SWH estimation result.

The synthetic aperture radar (SAR) interferometry (In-SAR) technique has already shown its importance in landslide mapping and monitoring applications. However, the usefulness of traditional differential In-SAR applications is limited by disturbing factors such as temporal decorrelation and atmospheric disturbances. And the Persistent Scatters Interferometry (PSI) technique need plenty of scenes, at least 25 scenes. Small Baseline Subsets (SBAS) is recently developed In-SAR approach. And it has a wide range of application prospects in the surface deformation monitoring because it could attain tiny deformation information of the surface and obtain long time series, slow deformation field of the surface. In this paper, we choose the Minjiang river basin as a study area, using SBAS approach obtained the surface deformation, and the deformation points which are unreasonable is removed according to certain conditions. The results show that the surface deformation points are mainly distributed on the right bank of the river, which is related to the low sensitivity of the ENVISAT data whose orbit is descending direction. Analyzed spatial relationship the potential landslide areas extracted using the spatial analysis method in ArcGIS software and the historical landslides. Meanwhile, the potential landslide areas are mainly distributed along the river. The main reason for this rule is the influence of the river erosion on the slope foot so that landslides distributed along the River; What’s more, among 30 historical landslides, 16 points lie in the deformation area, and 11 points lie in the potential landslide area, only 3 points are outside of the deformation area. Which shows that the landslide deformation points can better reflect the spatial distribution of historical landslides. Therefore, in the absence of historical landslide inventories, potential landslides detection by using deformation points provides effective assistance for regional disaster prevention and investigation.

Key words: landslide, SBAS technology, landslide deformation point, Minjiang River Basin.

The surface deformation caused by mining is seriously threatening the safety of Mining area. It is necessary to continuously monitor the surface deformation of mining areas, in order to ensure the safety of production, as well as supporting early warning and risk control. Limited by the side-looking geometry of SAR sensors, only deformation along line-of-sight can be retrieved with time series InSAR technology from a single stack of SAR images. Since the terrain varies greatly in mining areas, it is very difficult to monitor the overall 3D deformation of mining pits and dump sites with a single stack of SAR images. Therefore, fusion of PS point clouds from multi-stack SAR images is necessary.

In this paper, fusion of PS point clouds retrieved by time series InSAR from multi-stack SAR images would be carried out. For the first step, the best PS points are select from the geocoded PS points with a threshold on the variance of estimated heights within a certain window. Then, binary images are generated with the selected PS points. Coarse offsets of the same object between binary images from different stacks are estimated and compensated. After that, point correspondences are created with the compensated PS points, followed by the least squares adjustment to calculate precise offsets between corresponding points. In the final step, offset compensation would be carried out, leading to precisely fused point clouds. the offset between PS points This fusion approach includes several key steps, such as selection of excellent PS points, finding the best PS point matching model between different stacks with iteration, least-squares adjustment without any reference data, PS point cloud re-locating with least squares adjustment, etc.

With this fusion method, three dimensional deformation of an open pit mine in Anshan will be estimated from multi-stack SAR images and presented in the fullpaper. 3D deformation of open pit mines is beneficial to monitoring the mining process. The relationship between mining activity and surface damage can also be analyzed with the assistance of surface deformation pattern, subsidence rate and other possible factors in the mining area.

Key words: Time Series InSAR; Surface Deformation; Multi-stack Fusion; Open Pit Mine

Multitemporal interferometric synthetic aperture radar (InSAR) observations have been widely used to characterize spatial and temporal variations of ground deformation of tectonic, climatic or anthropic origin. An accuracy in the order of a millimeter per year on velocity measurements can be achieved in areas where a dense archive of InSAR data exists, and when methodological developments are applied to enhance coherence and improve the signal to noise ratio. With systematic acquisitions and a revisit time of 24 days over Tibet, the new Sentinel-1 radar data offer new perspectives to retrieve small deformation signal and better separate various sources of deformation. We review here our most recent studies over the tibetan plateau, emphasing improvments in InSAR processing of both the Envisat archive and newly acquired Sentinel-1 data.

We characterize the ground motion induced by the response of the permafrost active layer to climatic forcing, over a 60000m2 area in the northwestern part of the tibetan plateau, during 8 years spanned by the Envisat archive. This phenomena is limited to Cenozoic sedimentary basins and is spatially variable in both its seasonal amplitude (2.5–12 mm) and multiannual trend (−2 to 3 mm/yr). A degree-day integrated model adjusted to the data indicates that subsidence occurs when the surface temperature exceeds zero (May to October) over areas where seasonal movements are large (>8 mm). The period of subsidence is delayed by 1–2 months over areas where smaller seasonal movements are observed, suggesting an unsaturated soil where water occurs in the deeper part of the active layer. We use the same Envisat archive to characterize the interseismic strain pattern across the Altyn Tagh fault system. The previous permafrost study helps better unwrapping interferograms and referencing velocity maps on adjacent tracks, which leads to a better quantification of the tectonic signal. Here we also test various strategies to correct tropospheric delays, improving as well the differentiation between secular tectonic deformation and seasonal signals. A linear feature of strain localization (1-2 mm/yr of velocity change in the line of sight -LOS-) is identified north of the Altyn Tagh strike-slip Fault (ATF) within the Tarim basin, parallel to the ATF. We suggest that the ATF is connected at depth with a transpressive ramp emerging north of it in the basin, both structures accommodating by slip partitioning an oblique (N52°E) convergence rate of 14.2 mm/yr. South of the ATF, we also observe strain localization along a continuous feature, possibly the Jinsha suture, corresponding to 3 mm/yr of velocity change in the LOS. Finally, taking advantage of our experience in InSAR processing of long-tracks, small deformation and difficult terrain conditions areas, we adapt our chain to the processing of Sentinel-1 (S1) data, focusing on the eastern-southeastern border of the tibetan plateau, from the Haiyuan fault to the north to the Xian Shui He fault to the south.

It is challenging to effectively extract the near-field deformation of large earthquakes using InSAR approach, especially from the short-wavelength radar sensors, such as the C-, X- band systems. The issue leads to incomplete deformation field of large earthquakes in the vital regions, which are critical for earthquake studies. Some of the well-known decorrelation effects could lead to signal loss and prevent successful phase unwrapping, such as the geometric (or spatial), temporal, and Doppler decorrelation, etc. The decorrelation effects may reduce the received energy of satellite radar sensors from the back-scattering of ground targets. Hence, the incoherence (or partial of it) of radar signals will greatly reduce the signal-to-noise ratio of InSAR phase and leads to information loss in the deformation field or serious phase jumping issues in the final products. In the near-field of large earthquakes, high phase gradient may be irresolvable by traditional unwrapping methods. In extreme situations, the complete incoherence of radar returns could occur when the phase difference of neighbor pixels exceedingπradians. Except for this physical limitation of the radar systems, it is possible to extract useful information from InSAR data. Moreover, severe DEM errors (depending on baselines and topography) will also greatly influence the phase unwrapping process and introduce heavy phase jumping errors, leading to unreliability of InSAR observations.

To overcome the limitations described above, we developed a simple strategy for phase unwrapping. Due to strong phase gradient following large earthquakes, we first multi-look the InSAR phase to a lower resolution and implement conventional Goldstein filtering and unwrapping. After the step, we use a 2-D spatial filter to estimate the first order deformation signals and remove this component from the unwrapped phase. We do the same procedure in an iterative way until it is impossible to unwrap the residual phase. The final residual phase plus the filtered-out phase using Goldstein filter are deemed as the total residuals for the wrapped phase. We then resample the total residuals to the original spatial resolution of InSAR phase and removed it from the observations. Then the conventional unwrapping procedures will be able to used for extracting InSAR phase covering even the near-field of earthquake deformation area. The total residuals could also include useful information excluded from earthquake deformation, such as localized deformation of landslides, small areas of uplift or subsidence, besides the DEM error phase.

We had successfully applied the method to some large earthquakes, such as the 2015 Illapel, Chile earthquake, the 2016 Ecuador earthquake, the 2016 Central Itlay earthquake sequence, and the 2016 New Zeland earthquake, etc. So far, we only consider the Sentinel-1 data here, due to its small temporal decorrelation effects, but it would be much easier to work with L-band data, such as ALOS-1/2. Also, in some mountainous regions, it is also valuable to use the method to overcome the phase unwrapping issues for interseismic or postseismic InSAR phase retrieval.

In eastern Tibet, the left-lateral, ~1400 km-long, Xianshuihe fault system (XFS) is oneof the most tectonically active intra-continental fault system in China. More than 20 M>6.5 earthquakes broke this fault since 1700, including the recent 2010 Mw6.9 Yushu earthquake. We focus here on the northwestern segment of the XFS, the Ganzi fault, east of the Yushu rupture, identified as a seismic gap capable of producing Mw7.6 earthquakes. The Quaternary slip-rate of this Ganzi segment is estimated to 6-8 mm/yr, from offsets measurements and cosmogenic dating of moraine crests and alluvial fan edges (Chevalier et al., 2017). To characterize the present-day behavior of this segment, we process the first two-years of Sentinel-1 InSAR data to produce an average velocity map across the Ganzi fault, using both descending and ascending data. We adapt our InSAR processing chain (NSBAS) to the specificities of Sentinel-1 data and produce a simple elastic model of the InSAR-derived velocity field. We discuss our first results in comparison with the existing GPS data and the long-term tectonic setting.