A single Interferometric Synthetic Aperture Radar (InSAR) interferogram provides a measurement of ground movement with centimetric accuracy, and therefore can only detect large ground motions such as those caused by co-seismic slip or volcano eruption. For detecting small amplitude and long term displacement such as post/inter seismic motion or ground subsidence, a time series of interferograms is needed to overcome the errors resulting from the atmosphere, DEM and orbit. In most of the currently available InSAR time series analysis packages, two fundamental assumptions are made, namely that (i) deformation signals are correlated in time, and (ii) atmospheric effects are correlated in space but not in time. Unfortunately, since atmospheric effects can be highly correlated with topography, the second assumption does not hold in most cases. The temporal correlation of atmospheric delays may completely mask or bias the geophysical signals and introduce unpredictable uncertainties on the velocity estimates.

To overcome this, we propose a strategy which (i) employs a generic InSAR atmospheric correction model for each interferogram by using tightly integrated HRES-ECMWF grid model output and GPS ZTD pointwise observations (global and all-time useable in near real-time); (ii) utilizes a series of model performance indicators to identify the date(s) with poor correction performance, including cross validation of ECMWF and GPS ZTD values, observed phase and modelled atmospheric delay correlations and phase standard deviations; (iii) uses an atmospheric phase screening (APS) model using partially corrected interferograms from step (i) to estimate atmospheric delays for each interferogram: higher performance of the correction model and reliable performance indicators will improve the estimation of APS; and (iv) applies the conventional time series analysis approach to extract the mean deformation rate as well as displacement time series. Our experiments with the proposed method suggest it is particularly beneficial for InSAR time series over mountain areas, as the residual atmospheric errors after correction are more likely to be randomly temporally distributed, which allows an easier minimization through time series analysis.

Landslide is one of the major and most frequently occurring geo-hazards around the world. After the 2008 Wenchuan Earthquake in China, a series of large-scale landslides were triggered. Unexpectedness and concealed nature of the landslides significantly increase the destruction degree and difficulty to prevent, exposing people’s livelihoods and infrastructure at risk.

Space borne radar remote sensing could realize macro dynamic monitoring of large-scale landslide hazards and provide an efficient way to obtain landslide surface deformation and spatio-temporal characteristics, hence contribute to early detection and early warning for local disaster risk management. This work shares several radar remote sensing applications in multiple landslide monitoring case studies in Sichuan since 2014 to till date. Long deformation evolutions of these landslides could be retrieved from time series InSAR processing with joint use of multi-platform InSAR observations. To fully investigate and validate the great potential of Sentinel-1 on landslide monitoring in complex terrain mountainous areas, and integrate the radar datasets from Sentinel-1 and TerraSAR-X, this work realized the landslide surface deformation acquisition with multi scales, short time intervals, and long time series, which also verify the great advantage of multi-platform spaceborne radar remote sensing on landslide monitoring. What’s more, combined with in situ measurements and other remote sensing observations for subsequent analysis and validation, space borne radar remote sensing applications could demonstrate great potentials to identify the spatio-temporal characteristics and investigate the failure mechanism for hazardous landslides.

This paper concludes that a comprehensive and effective Earth Observation (EO) based local landslides monitoring could avoid future human and infrastructure loses in the hill and High Mountain regions around the world.

Previous work with TerraSAR-X [1,2] indicated that landslides can be monitored on steep densely vegetated slopes in hilly terrain using sub-pixel offset tracking, sPOT over the Shuping area, Hubei, PR China. In this work, Cosmo-Skymed Spotlight data is employed at a later time period (27 June 2016 to 30 August 2016) to assess whether the mitigation measures employed to prevent further landslip have been effective using both dInSAR and sPOT processing. The results show good agreement between both methods over this 3 month time period with a small progressive motion towards the NNW of magnitude 10cm in azimuth and 5cm in slant-range. This is much smaller than the previous (accumulated) motion of up to 1m/year from February 2015-2016 using SBAS offset tracking [2] and from February 2009–April 2010 and January 2012–February 2013 using sub-pixel offset tracking [1], prior to the mitigation methods. Part of the reason for the success of dInSAR which was next to impossible to apply previously was that the mitigation measures resulted in a substantial portion of bare earth which had much higher phase coherence than the previously vegetated area. A comparison of the three methods are discussed alongside which one is best in different circumstances.

This work was partially supported by the CSC and UCL MAPS Dean prize through a PhD studentship at UCL-MSSL. We thank Space Catapult, Harwell space campus in general and Terri Freemantle, in particular, for arranging the provision of Cosmo-SkyMed data through the CORSAIR010 data grant.

[1] L. Sun and J.-P. Muller, “Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas,” Remote Sensing, 8, 25, doi: 10.3390/rs8080659

[2] L. Sun, J.-P. Muller, and J. Chen, “Time Series Analysis of Very Slow Landslides in the Three Gorges Region through Small Baseline SAR Offset Tracking ,” Remote Sensing, 9, 1314. doi: 10.3390/rs9121314

3D SAR Tomography (TomoSAR) [1-4] and 4D SAR Differential Tomography (Diff-TomoSAR) [8-14] can be used to 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 often 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 of 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 and has raised a number of unforeseen challenges, which will be described. Then, atmospheric correction is assessed using weather model data such as ERA-I and compared against GACOS in addition to ionospheric correction methods to remove 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.

On 3 September 2017, North Korea (Democratic People's Republic of Korea, DPRK) claimed it has successfully tested a hydrogen bomb that could be loaded on to a long-range missile. Seismic readings of 6.3 indicated the test was bigger than any other that has been conducted. Punggye-ri Nuclear Test Site is the only known nuclear test site of North Korea. During the past 12 years, nuclear tests were conducted at the site in October 2006, May 2009, February 2013, January 2016, September 2016, and September 2017. Because of political and other complex factors, it is impossible to obtain any GPS, geology, and field surveying data for direct monitoring and research. InSAR provides a new inspiring research method for underground nuclear deformation monitoring. Here, we use multiple spaceborne SAR data that are ALOS-2, Sentinel-1 and TerraSAR-X to retrieve surface displacement caused by the latest 3 events. The results show that InSAR provides an independent tool to locate and retrieve surface displacement of nuclear tests in North Korea as a supplement of seismic and other methods.

Punggye-ri Nuclear Test Site is located in the northern part of DPRK with complicated land cover, high altitude and mountainous terrain. To achieve homogeneous and reliable measurements in the nuclear test site based on InSAR is really challenging. In mountainous regions, the atmospheric phase screen (APS) can cause serious problems in InSAR observation. From the images we have processed, it is obviously to distinguish atmospheric phase delay. Hence, we conduct APS correction based on WRF (Weather Research and Forecasting) and ECMWF (European Center for Medium range Weather Forecasting) to reduce the APS in D-InSAR processing. Second, the coherence of InSAR interferometric pairs is affected by many factors such as spatial-temporal baseline, wavelength and land cover. We selected multiple interferometric combinations and compared the performance of C-band Sentinel-1, L-band ALOS-2 and X-band TerraSAR-X in InSAR deformation monitoring. The results show that the L-band ALOS-2 data are generally more coherent therefore can provide effective information for surface deformation monitoring. Finally, due to the lack of external data to verify the reliability of InSAR results, we cross-validated the monitoring results of multi-source SAR data with different wavelengths, incident angles, and spatial resolutions aiming to get the robust and trustable result.

Key words：InSAR；Underground nuclear test；Surface deformations；Multiple SAR data；North Korea

Land cover classification is one of the important applications of polarimetric SAR (PolSAR) data. With the development of PolSAR techniques and the increasing demand for PolSAR data in applications, many SAR satellites with full-polarization mode have been successively launched, such as the widely used Japanese ALOS-2 PALSAR-2 (ALOS-2) and The Canadian RADARSAT-2 (R-2) data. China also successfully launched the first civilian SAR satellite with full-polarization in January 2017 - GF-3. However, due to the parameter differences in different SAR sensors, the resolution difference and difference in observation incidence, although in the same area there may be different land cover classification result obtained from different SAR images and the feature selection for classification may be different.

The aim of our study is to improve the land classification accuracy using GF-3, R-2 and ALOS-2 polarimetric SAR data. In this study, we used polarimetric decomposition results including Pauli decomposition H-α-A decomposition, and Yamaguchi decomposition as classification features and analyzed their distributions for different land cover types. After that, we selected the optimal combination of decomposition features as classification parameter for GF-3, R-2 and ALOS-2 respectively, and then carried out the experiments of land cover classification in Beijing. The results showed that for GF-3, using the components of Yamaguchi decomposition as feature parameters performs best, but for R-2 and ALOS-2, using the components of H-α-A decomposition as feature parameters performs best. Moreover, ALOS-2 has the highest classification accuracy (80%), but GF-3 and R-2 have similar classification accuracy (77%). Our study gives some references for the application of GF-3 PolSAR data.

Monitoring Anthropogenic Surface Deformation in Tibetan Plateau Using Sentinel-1 Data

Yunfeng Tian, Jingfa Zhang, Yi Luo, Yongsheng Li

Key Laboratory of Crustal Dynamics, Institute of Crustal Dynamics, China Earthquake Administration

1 Anningzhuang Road, Haidian, Beijing 100085, China

tel(O) 86-10-62842646 zhangjingfa@hotmail.com

1. INTRODUCTION

InSAR has been one of the key techniques for crustal deformation study. However, attentions should be paid to various nontectonic surface deformation which can also be captured by InSAR, for example, the ground subsidence due to extraction of underground water, which is common nowadays for densely populated urban regions. The presence of localized deformation arising from anthropogenic activities often obscures the movement of the Earth’s upper crust layer; and thus introduces bias in quantifying slip rates of active faults or motion of crustal blocks. In this work, we focus on the deformation related to human activities in Tibetan plateau, with the help the high-resolution Sentinel-1 C-band SAR data collected from late 2014 to early 2018, aiming to figure out various signals in the InSAR deformation map.

2. DATA & ANALYSIS

We used both ascending and descending orbital data of Sentinel-1 A/B satellites which serve as a validation of the signals we observed. The observation interval was 24 days from late 2014 to early 2017 and 12 days since middle 2017.

We processed the data using the GMTSAR software package (Sandwell et al., 2011). We first aligned all other acquisitions to the super master scene that we manually specified; and then generated interferograms for each acquisition pair. Strong decorrelation during the interferometric processing is rare due to the improved orbits of Senetinel-1 satellites and dry climate on the highland of Tibetan plateau, except for areas with strong seasonal frost deformation. The LOS displacement time series were generated using the coherence-based SBAS method which assigns small weights to pixels with lower coherence and produces a continuous deformation map, compared to traditional methods. Finally, the velocity was derived by fitting a straight line to the displacement time series.

3. RESULTS

(1). Ground subsidence due to mining

The Sentinel-1 data captured clearly the ground subsidence due to the mining activity at Zhaxikang (Figure 1), a town located right at the eastern fault trace of the Sangri-Cuona rift in southern Tibet. The maximum subsiding rate reaches ~10 mm/yr during the data period. Locations of construction sites and buildings were identified from the high-resolution multi-spectral images in Google Earth; and they were in good accordance with the distribution of the subsidence area in InSAR LOS rate map.

Figure 1. InSAR LOS rates (descending orbit) for Zhaxikang Mine in Sangri-Cuona Rift. (a) Location map. (b) Rate profile. The width of buffer zone is 5 km at both sides of the profile line. The color of symbol in profile plot represents the distance to the profile line.

(2). Ground uplift due to oil-drilling activity

There are several oil fields along the Mangya-Huatugou thrust fault zone in Qinghai province, China. The oil-drilling work usually involves injecting water down to the deep after extracting underground oil out, to maintain a certain level of pressure. We observed, using Sentinel-1 InSAR time series analysis, several localized uplifting areas in Qinghai province (Figure 2). The maximum uplifting rate can be > 10 mm/yr in the LOS direction.

Figure 2. InSAR LOS rates (descending orbit) for oil field north of Huatugou Town, Qinghai province, China. (a) Location map. (b) Rate profile.

(3) Other types of small-scale deformation or bias

The ground deformation can be also caused by other human activities, such as the extraction of underground water for agricultural irrigation or drinking in urban area. The cause of such subsidence can usually be investigated by checking the locations of villages or towns where high demand of water supply is often needed.

There are also some subsidence places where no obvious anthropogenic activities are presented. These regions often locate in the river basin or in valley between mountain peaks, and also along certain active fault zones. It is difficult to discern the cause of such deformation without help of other sources. Therefore, attentions should be paid when deriving the contemporary fault slip rate of such active fault.

Moreover, subsidence or uplift trend can also be fake deformation signal, especially in mountainous regions with high and steep topography. The situation might get worse, sometimes, in thrust faulting zone where both crustal uplifting and large topographic errors concur.

4. CONCLUSIONS

Our recent work using the latest spaceborne C-band SAR satellites (Sentinel-1 A/B) data demonstrated that InSAR technique nowadays is capable of measuring the crustal deformation at the millimeter level accuracy. Ground deformation related to anthropogenic activity, either subsidence or uplift, can be detected with sufficient confidence for the broad area in Tibetan plateau. However, there is also regional deformation whose origin is unknown or difficult to investigate. We should prefer to not make conclusions on geological issues before figuring out the origins of such observed deformation.

ACKNOWLEDGEMENTS

This work is supported jointly by National Science Foundation of China (41104001), China Earthquake Administration (Y201711), and Institute of Crustal Dynamics (ZDJ2017-29).

REFERENCES

Sandwell, D., R. Mellors, X. Tong, M. Wei, and P. Wessel (2011). Open radar interferometry software for mapping surface deformation, Eos Trans. AGU 92(28) 234, doi:10.1029/2011EO280002.

Landslides are one of the most damaging hazards for human beings and can be affected by multiple factors, including the natural environment and human activities. Since the Three Gorges Dam on the Yangtze River was completed in 2003, detecting and monitoring the landslides in the upstream area has become more important in order to protect human lives and properties. Compared to conventional in situ measurements, various remote sensing techniques have been carried out and found capable of monitoring landslides in difficult terrain over a large area.

This study focuses on monitoring landslides in the Three Gorges Region (TGR), which is characterised by the high humidity, dense vegetation, and steep slopes. Shuping with centre coordinates of 30.996◦N, 110.609◦E and Tanjiahe with centre coordinates of 31.030◦N, 110.509◦E are the two selected study sites. Synthetic aperture radar (SAR) techniques are applied to monitor landslides in these study areas and mitigation works performed to reduce the risks of landsldies in unstable areas. To assess the accuracy of digital elevation models (DEMs) derived from interferometric SAR data, TLS data was acquired by Zhang and co-workers and this is compared with the post-mitigation 6 m TDX CoSSC DEMs, SRTM and ASTER DEMs and DEMs derived from Cosmo-Skymed Spotlight data. The assessment of mitigation is also carried out by comparing two sets of Terrestrial Laser Scanning (TLS) data of the study sites before and after remediation.

The potential and limitations of using different SAR data, especially Sentinel-1 to identify unstable regions for follow-up acquisitions of TerraSAR-X Staring Spotlight and Cosmo-Skymed Spotlight data are described. The potential of TLS techniques which have not been widely used in previous studies will also be evaluated. Furthermore, the effect of mitigation in landslide area is also going to be assessed.

Acknowledgments: We thank Prof. J. Zhang, Dr. Q. Jiao, and Dr. T. Xue from the China Earthquake Administration for their support on our fieldwork.

Together with SAR interferometry (InSAR), Ground-Based Synthetic Aperture Radar (GBSAR) has proven to be a powerful field-based remote sensing tool for deformation monitoring. This work proposes two complete GBSAR data processing chains developed on the basis of advanced InSAR time series analysis algorithms including the Small Baseline Subset (SBAS) concept and the Persistent Scatterer Interferometry (PSI) for continuous deformation monitoring. The developed SBAS chain exploits redundant interferograms and processes consecutive GBSAR imagery unit by unit, which allows the opportunity to investigate temporarily coherent targets and reduces the requirement of computation memory. Contrarily, the PSI chain is more computationally sufficient and is developed to support early warning and rapid decision-making in urgent situations. Two practical applications are given in this work to demonstrate the feasibility of the developed GBSAR data processing chains for continuous deformation monitoring.

The magnitude 7.0 Jiuzhaigou earthquake occurred in August 8, 2017 resulted in a large number of landslides near the Jiuzhaigou panda sea, causing road congestion and seriously affecting the earthquake emergency rescue progress. The landslide caused by earthquake has the characteristics of wide distribution and large quantity. Because of the urgency of the disaster and high resolution of unmanned aerial vehicle (UAV) images the traditional artificial visual interpretation model cannot meet the needs of earthquake emergency response. Therefore, it is necessary to provide an automatic information identification method. Thus, the distribution range of landslide can be identified quickly and accurately.

Based on the deep analysis of the features of remote sensing images of landslide, an automatic information identification model for object oriented analysis is constructed. Firstly, the remote sensing images are segmented at different scales to obtain different levels of image objects according to different types and scales of land objects. Then, SEath algorithm is used to construct feature rule set automatically by comprehensive utilization of the information of spectrum, texture and shape of object at every level, and the distribution of earthquake-induced landslides is identified. After that, taking artificial visual interpretation as a reference, the recognition accuracy and efficiency are evaluated. Finally, the spatial distribution features of landslide body in topographic factor and fracture distribution layer are analyzed by statistical analysis. The overall accuracy is 94.8%, and the Kappa coefficient is 0.827. At the same time, on the basis of the same configuration of the computer, the present method is twice as efficient as that of the artificial visual interpretation method.

The paper also analyzes the earthquake-induced landslide distribution features in elevation, slope, aspect, fault distance and other factors. The correlation between landslide and topographic factors is found. It is concluded that the earthquake-induced landslide in the study area is mainly controlled by the Tazang fault. The spatial distribution rule can provide information support for landslide risk assessment, disaster investigation, prediction and prevention. There are obvious fault effects in the distribution of landslide.

The geologic observations presented above suggest that conjugate strike-slip faults are significant structures along the Bangong-Nujiang suture zone in central Tibet. However, some small fault zones located inside the Qinghai Xizang Plateau, especially in the secondary blocks, have not attracted enough attention. For example, a series of V-shaped conjugate strike slip fault systems between Lhasa block and Qiangtang block. The V-shaped conjugate strike slip fault zone is composed of a series of small fault zones with oblique lines. It is an important product of the neotectonic movement in the Qinghai Tibet Plateau. It plays an important role in the deformation of the East-West extensional tectonic deformation in the Qinghai Tibet Plateau. This study will use InSAR technology to obtain the surface deformation information of conjugate strike-slip faults(Bengco Fault and Dongqiao Fault). The two faults are nearly 300 km in length. Therefore, the wide range SAR data should be selected (for example, Sentinel-1 IW mode SAR width is 250km) and used to obtain the active fault deformation signal in the whole conjugate strike slip fault at one time, which will help the overall analysis of the fault distribution. We will analysis the whole motion characteristics of conjugate strike-slip faults，investigate the strain accumulation of tectonic deformation in time and space. It is helpful to understand the characteristics of a series of conjugate strike slip faults developed in the middle part of the Qinghai Tibet Plateau.

The tremendous development of InSAR missions (e.g., Sentinel-1A/1B, ALOS-2, TerraSAR-X/TanDEM-X, COSMO-SkyMED, RADARSAT-2, and Gaofen-3) in recent years facilitates the study of smaller amplitude geohazard deformation monitoring using longer time series and over greater spatial scale, and this trend is set to continue with Sentinel-1C/D, Gaofen-3B/C, RADARSAT Constellation planned for launch during 2018-2025. This poses more challenges for correcting interferograms for atmospheric (tropospheric) effects since the spatial and temporal variations of tropospheric delay may dominate over large scales and can cause errors comparable in magnitude to those associated with crustal deformation (e.g. landslides, city subsidence and so on). In previous attempts, observations from Global Navigation Satellite System (GNSS) and Numerical Weather Models (NWM) have been used to reduce atmospheric effects on InSAR measurements, but GNSS-based correction models are limited by the availability (and distribution) of GNSS stations, and for NWM-based correction models, there might be a time difference between NWM and radar observations.

To overcome this, we have developed a generic InSAR atmospheric correction model whose notable features comprise: (i) global coverage, (ii) all weather, all time useability, (iii) correction maps available in near real-time, and (iv) indicators to assess the correction performance and feasibility. The model integrates operational high resolution ECMWF data (0.125-degree grid, 137 vertical levels, 6-hour interval) and continuous GPS tropospheric delay estimates (every 5 minutes) using an iterative tropospheric decomposition model. The model’s performance for InSAR atmospheric correction was tested using globally-distributed interferograms, encompassing both flat and mountainous topographies, mid-latitude and near polar regions, monsoon and oceanic climate systems, achieving a phase precision and displacement accuracy of approximately 1 cm for the corrected interferograms. Indicators describing the model’s performance including (i) GPS network and ECMWF cross-RMS, (ii) phase-delay correlations, (iii) ECMWF time differences, and (iv) topography variations, were developed to provide quality control for subsequent automatic processing, and provide insights of the confidence level with which the generated atmospheric correction maps may be applied.

We have released the Generic Atmospheric Correction Online Service (GACOS) based on the proposed model (http://ceg-research.ncl.ac.uk/v2/gacos/). This service aims to provide InSAR atmospheric correction maps in a convenient way with all features discussed above. The website was released on 6th June 2017 and has received over 10 thousand requests from all over the world. Given the convenience and the real time availability, the website has rapidly responded to recent events such as the Maoxian Landslide (24 June 2017) and the Xinjiang Earthquake (8 August 2017) by providing the atmospheric corrections used in the generation of near real time deformation fields to identify surface damages and contribute to rescue and recovery operations, which have been reported and highlighted by over 20 social medias and organizations.

Seismic indirect economic loss assessment not only has a major impact on regional economic recovery policies, but also it is related to the economic assistance at the national level. However, due to the Cross-regional economic activities and the difficulty of obtaining data, the seismic indirect economic loss are often predicted based on the direct loss of buildings and life lines. Although this method takes into account the impact of production factor stock on economic flows, the effects of disasters on economic activity are neglected and the economic losses in the tertiary industry are seriously underestimated.

The Defense Meteorological Satellite Program (DMSP) provides global images of 4 periods which from morning to night. Since the Operational Linescan System of DMSP (DMSP-OLS) can observe the city night light, it was widely used in population distribution analysis, economic development monitoring and so on. This paper took Sichuan Province as an example to evaluate the impact of earthquake on economic activities on large spatial scale based on DMSP/OLS, and then estimated the recovery of the economy in the disaster area on the view of time and space by analyzing a series of data from pre-event 5 years to post-event 5 years. First, the county economic evaluation model is established. Upon image registration and correction, the nighttime light images are clipped by the county boundaries. Afterwards, counting the nightlight index of all counties, comparing with Sichuan Statistical yearbook, the corresponding relations between nightlight index and economic activities was finally established. Second, a seismic indirect loss Assessment method are presented. Through the analysis of the area and spatial distribution of night-time light around 2008, the spatial migration and change characteristics of economic activities were summarized, which were caused by Wenchuan earthquake. Then a functional relationship between seismic indirect economic loss and night-time light changes of post-earthquake was established. Third, the economic recovery of affected areas was evaluated. The economic recovery of Sichuan Province was evaluated in time and space by comparing with the cumulative growth of night-time light within the 5 years from 2009 to 2013 and the value of per-earthquake.

In this paper, more attention should be paid to the impact of earthquake on social economic activities. Especially in some areas dominated by the service industry, indirect economic losses can better reflect the impact of the disaster on the area. At the same time, it is also hoped that the application of night-time light data in the evaluation of earthquake disaster damage and restoration will also help the government to formulate a policy on regional economic assistance.

Abstract: In November 2017, a strong Mw7.3 earthquake occurred at the Iran Iraq border. The earthquake caused the surface to rise and settlement on both sides of the fault zone, and the maximum displacement of LOS was about 0.85m. The fault rupture begins in the northwest and continues along the fault to the southeast. The coseismic deformation field is retrieved based on ALOS-2 satellite data and Sentinel-1 satellite data. Using the two step inversion algorithm to do the seismic source mechanism inversion, the inversion results are compared with the USGS results and both of them have good coincidence degree, and the inversion of the seismic source mechanism is more fine. It can better analyze and describe the earthquake. The seismogenic structure laid the foundation for studying the fault structure in the area.

Keywords: Iran Iraq earthquake, D-InSAR, Seismic source mechanism inversion

1. research status

In November 12, 2017, a strong earthquake of magnitude Mw7.3 occurred on the Iraqi border in Iran. The epicenter was located at (34.886°N, 45.941° E) and the focal depth was 19km. The earthquake caused more than 500 deaths, thousands of injured, more than 7000 homeless and thousands of houses collapsing, causing huge economic losses and casualties to the local people.

The earthquake occurred at the front of the collision zone between the two large plates - the Arabia plate and the Eurasian plate, along the Iran and Iraq border in the northwest of the Zagros belt. The Zagros thrust belt is a long 1500km fold thrust belt which extends to the west of Iran and extends to northern Iraq. Although Iran and Iraq are earthquake prone areas, there has not been an earthquake above Mw5.0 for many years. The earthquake damage was relatively light on November 12 of 2017, because before the occurrence of the Mw7.3 earthquake, the region had 4.4 levels of pre-earthquake, and most of the people moved to the relatively safe area after the occurrence of the pre-earthquake.

After the earthquake, by collecting the SAR data before and after the earthquake, the coseismic deformation field can be analyzed and processed. Because the acquired SAR data can cover the focal area completely, so the differential interference measurement technique is used to deal with the very clear deformation field after the earthquake. Through the analysis of the coseismic deformation field, it can be seen that the earthquake caused a relative decline of the upper plate and uplifting of the footwall on both sides of the fault, and the maximum displacement of the satellite's flight direction is up to 0.85m.

The two step inversion algorithm is used to estimate the fracture set parameters and the slip distribution of the fault under the constraint of the InSAR result. Firstly, the fault is assumed to be a homogeneous fault model, and the geometric parameters of the fault are calculated. Then the distributed fault model is used to calculate the distributed slip on the fault surface. Using PSOKINV software to inverse the source parameters, the software uses an improved group cooperative stochastic search particle swarm optimization (Particle Swarm Optimization, PSO) algorithm, which mainly solves the optimal solution through a group of random solutions by iterative method.

2. research significance

The Iraq Iran border is located in the collision zone between the Arabia plate and the Eurasian continent plate. The energy of collisions is cumulative and released and then resulting the earthquakes. This area is a shallow source area at most time. Due to frequent devastating earthquake, the Iran government has formulated corresponding building regulations to ensure the safety of the lives and property of the residents. The earthquake magnitude is relatively large, but the casualties are relatively not very serious. It also indicates the necessity of the construction of earthquake resistant buildings and the study at the same time. The seismogenic background and fault structure of the area have important research significance for earthquake disaster prevention in this area.

One of the largest inland earthquakes in Taiwan happened on 21 September 1999, the Mw 7.6 Chi-Chi event. It struck the Taipei Basin, in the Central western part of the island, killing more than 2400 people and damaging 100 000 structures. The rupture was complex with several dislocations along the 100-km long Chelungpu thrust fault. An improved study of this earthquake will allow better understanding of regional fault properties.

Six ERS images from the descending track 232 and covering the period from 21 January 1999 to 25 May 2000 were processed to investigate the co-seismic deformation. The Interferometric Synthetic Aperture Radar (InSAR) technique was used and via the ESA open-source software SNAP. With InSAR, only the footwall can be analysed because the hanging-wall, which likely experiences the main deformation, is densely vegetated resulting in very low coherence in the interferograms. Co-seismic interferograms show about 10-11 fringes which is equivalent to a displacement variation of approximately 30 cm.

We used PSOKINV (Particle Swarm Optimization and Okada Inversion package), a geodetic inversion package, to determine the fault geometry and the slip distribution. First, the non-linear problem is to use the Particle Swarm Optimization (PSO) for geodetic modelling with the assumption of a uniform slip on a rectangular fault. Second, a joint inversion of InSAR and geodetic data (GNSS and levelling) is realised. The GNSS enables us to get information about the hanging-wall of the fault and to improve the modelling. The slip distribution is determined as a linear problem, optimally-smoothed parameters are obtained.

Sub-pixel offset tracking has been used in various applications, including measurements of volcanic activities, glacier movement, earthquakes, landslides, etc., as a complementary method to time series InSAR. In this work, we explore the use of a small baseline subset (SBAS) Offset Tracking approach to monitor very slow landslides with centimetre-level annual displacement rate, and in challenging
areas characterized by high humidity, dense vegetation cover, and steep slopes. This approach, herein referred to as SBAS Offset Tracking, is used to minimize temporal and spatial de-correlation in offset pairs, in order to achieve high density of reliable measurements. This approach is applied to a case study of the Tanjiahe landslide in the Three Gorges Region. Using the TerraSAR-X Staring Spotlight (TSX-ST) data. With sufficient point density, we estimate the precision of the SBAS offset
tracking approach to be 2–3 cm on average. The results are demonstrated accord well with corresponding GPS measurements.

The key point of earthquake emergency is to quickly grasp the disaster, that is, earthquake damage assessment, in which the seismic hazard assessment of buildings is closely related to human life and property, which is the main content of seismic hazard assessment. Bad weather will generally follow the earthquake, the polarization of synthetic aperture radar (PolSAR) which is an active microwave radiation source, can penetrate many materials such as the rain,clouds,fogs,etc, thus it can imaging for the disaster areas in all weather and in all time, withal, the acquisition of target polarization scattering characteristic is relevant to the shape and physical property of the ground target, which benefits to ground-object identification, therefore PolSAR is widely applied in earthquake emergency. Compared with early single-polarization and multi-polarization SAR, full polarization SAR obtain the best effect of observation through flexible change of polarization state, it gets more complete polarization information, more abundant measurement information data, stronger performance for features classification. Earthquake damage buildings extraction can be divided into two kinds of methods: using multi-temporal change detection method and single phase post-earthquake image extraction method. The former one does polarization target classification firstly, then constructs seismic difference map to extract the earthquake damage buildings. Its core is to construct the difference graph, common methods such as establishing the polarization likelihood ratio model, defining polarization difference degree through combining scattering difference and power difference, Whishart distance change detection method etc. There is a difference of scattering mechanism between the collapsed buildings and intact buildings in the fully polarimetric SAR image after the earthquake, which is the theoretical basis for the single phase post-earthquake image extraction.
The current methods include: Polarization classification combined with the minimum heterogeneity criteria aggregation of hierarchical clustering algorithm, and template matching based on feature of image retrieval, the introduction of polarization orientation Angle compensation mechanism to improve and complete the structure of the the collapsed buildings and intact buildings.

On 24^th June 2017, a catastrophic landslide suddenly buried the Xinmo village (in Sichuan province, south-western China), resulting in heavy causalities. After the failure, the disaster assessment was in urgent need for the rescue and relief work. Except the field observation or UAV, spaceborn SAR data could provide valuable information to the disaster assessment.

In this study, we proposed a method that used the SAR interferometry coherence map to identify the landslide boundary and source area. With use of Sentinel-1 SAR images acquired on 12^th, June 2017 and 24^th June, 2017 (13 hours after the failure), the landslide boundary and source area were mapped by this method. It was revealed that the source area of this landslide was not at the top of the mountain. Compared with the UAV image acquired on 26^th June 2017, the location of the landslide boundary and source area were consistent.

This results show that, this first Sentinel-1 interferogram, together with its corresponding coherence and amplitude maps, not only helped us identify the source area of this massive landslide, but also assisted with mapping the landslide boundary. Spaceborn SAR data could help the disaster assessment to some degree.