Conference Agenda

The Swarm satellite mission were launched on 22 November 2013, it is the first European Space Agency’s constellation of three satellites, dedicated to monitoring geomagnetic field changes. The three satellites have delivered more than 7 year measurements to date, which provide an unprecedented opportunity for conducting a broad range of applications at global scale, including earthquake prediction study. However, for the past years, relatively little advancement has been achieved on establishing a systematic approach for detecting anomalies from the satellite data and integration with ground-based measurements for predicting earthquakes. In Dragon 3 we developed the Wavelet Maxima-based method, Geometric Moving Average Martingale (GMAM) based on the Martingale theory, the integration of Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) called CUSUM-EWMA, and applied these methods to analyse the Wenchuan and Lushan earthquakes.

This report will present the further development and comparative analysis results achieved in the Dragon 4 project. These include the development of a Fuzzy Inspired Approach to Seismic Anomaly Detection (FIAD), Anomaly Detection in Sequential Data Augmented with new features and Enhanced Martingale methods as well as analysis results of the Peru earthquake, Jinggu, Taoyuan, Ludian and Peloponnese earthquakes occurred in China and Greece, respectively. These results demonstrated possible automatic approaches for detecting anomalies from the satellite data and the effectiveness of these methods. The studies conducted have laid down a good basis for the project team to carry out large and more comprehensive studies of analyzing the data observed by China Seismo-Electromagnetic Satellite Mission (CSES) satellite and ground-based networks in order to improve understanding of earthquake preparation and occurrence processes.

Interferometric Synthetic Aperture Radar (InSAR) enables detailed investigation of surface landslide movements, but cannot provide information about subsurface structures. In this work InSAR measurements were integrated with seismic noise in-situ measurements to analyse both the surface and subsurface characteristics of a complex slow-moving landslide exhibiting multiple failure surfaces. The landslide body involves a town of around 6,000 inhabitants, Villa de la Independencia (Bolivia), where extensive damages to buildings have been observed. To investigate the spatial-temporal characteristics of the landslide motion, Sentinel-1 displacement time series from October 2014 to December 2019 were produced. A new geometric inversion method is proposed to determine the best-fit sliding direction and inclination of the landslide. Our results indicate that the landslide is featured by a compound movement, where three sub-blocks slide with diverse geometries and magnitudes. This is further evidenced by seismic noise measurements which identified that the different dynamic characteristics of the three sub-blocks were possibly due to the different properties of shallow and deep slip surfaces. Determination of the slip surface depths allows estimating the overall landslide volume (9.18·10⁷ m³). Furthermore, Sentinel-1 time series show that the landslide movements manifest substantial accelerations in early 2018 and 2019, coinciding with increased precipitations in the late rainy season which are identified as the most likely triggers of the observed accelerations. This study reveals the potential of integrating InSAR and seismic noise techniques to understand the landslide mechanism from ground to subsurface.

Reference:

Song, C., Yu, C., Li, Z., Pazzi, V., Del Soldato, M., Cruz, A. and Utili, S. (2021), Landslide geometry and activity in Villa de la Independencia (Bolivia) revealed by InSAR and seismic noise measurements, Landslides, https://doi.org/10.1007/s10346-021-01659-9.

The present project Three- and Four-Dimensional Topographic Measurement and Validation (ID: 32278) has been developed with continuity since Dragon-1. In Dragon­1 and Dragon­2, the focus was on DEM generation and surface motion estimation with medium resolution Synthetic Aperture Radar (SAR) data. Since Dragon­3, SAR datasets of high spatial and temporal resolution (TerraSAR­X, COSMO­SkyMed) were made available, and nowadays, thanks to the availability of dense time series from Sentinel­1, accurate and frequent global coverage has become reality. Moreover, the capabilities of SAR-based Earth Observation are on their way for a further improvement in the very near future, thanks to new low-frequency Missions such as BIOMASS and ROSE-L that will grant enhanced wave penetration in natural media such as forests and ice. This is the context in which this Dragon-4 project is framed. The overarching goal of the project is to develop new methodologies to deliver a most complete characterization of targets on land surfaces and deepen the current knowledge on the exploitation of SAR data. The project is split into three subprojects focused on specific tasks, namely:

• Validation of elevation and deformation maps produced by SAR Interferometry.
• Handling temporal effects on interferometric and tomographic analyses of natural scenarios.
• Near-real time target motion estimation, considering efficient algorithms to allow for the digestion of new acquisitions and for a change in the parameterization of the estimation problem.

Non-climate-related anthropogenic processes and frequently encountered natural hazards exacerbate the risk in coastal zones and megacities and amplify local vulnerability. Coastal risk is amplified by the combination of sea level rise (SLR) resulting from climate change, associated tidal evolution, and the local sinking of land resulting from anthropogenic and natural hazards. In this framework, the authors of this investigation have actively contributed to the joint European Space Agency (ESA) and the Chinese Ministry of Science and Technology (MOST) Dragon IV initiative through a project (ID. 32294) that was explicitly designed to address the issue of monitoring coastal and delta river regions through Earth Observation (EO) technologies. The project's primary goals were to provide a complete characterization of the changes in target scenes over time and provide estimates of future regional sea level changes to derive submerged coastal areas and wave fields. It also provided suggestions for implementing coastal protection measures to adapt and mitigate the multifactor coastal vulnerability. To achieve these tasks, well-established remote sensing technologies, based on the joint exploitation of multi-spectral information gathered at different spectral wavelengths, the exploitation of advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques for the retrieval of ground deformations, the realization of geophysical analyses, and the use of satellite altimeters and tide gauge data, have effectively been employed. The achieved results provide essential assets for planning present and future scientific activities devoted to monitoring such fragile environments. These analyses are crucial to assess the factors that will amplify the vulnerability of low-elevation coastal zones.

Geological disasters, or geohazards, can occur in remote and highly populated areas, causing several fatalities and high economic damage every year. Due to their wide spatial and temporal coverage, remote sensing data, acquired from most recent satellite missions, is the perfect tool for detailed reconstruction of past events and to monitor currently occurring phenomena. This Dragon-4 project aims to apply different techniques and methods for extensive exploitation and analysing of remote sensing data with special emphasis given to landslide hazard, risk management and disaster prevention. Multi temporal SAR interferometry, SAR tomography, high-resolution image matching and data modelling are extensively used to map landslides and other geohazards, and to evaluate their activity. In this project, various areas and various geohazard problems are explored, in the Chinese territory, including: (1) surface deformation of mountain slopes and glaciers in the Tibetan plateau; (2) land surface displacement in the Beijing region; (3) geohazards in the Longnan area; and (4) subsidence, landslides and ground fissure in the Benxi-Anshan/Shenyang-Fushun (BASF) region. Each of these themes is explored in four different sub-projects in which Chinese and European researchers collaboratively contribute. The results obtained from the processing and analysis of a huge dataset of earth observation (EO) multi-source data allow to conclude that geohazards can be identified, studied and monitored in an effective way using new techniques applied to EO data.

Improvement of InSAR time series analysis over the past years, combined with increased temporal resolution and spatial coverage of InSAR data, made it possible to explore in more detail and with more accuracy various surface deformation processes (tectonic, hydrological, related to human activities...). A major challenge associated with this is to better separate the different signal sources in InSAR velocity maps. We report here the main results obtained during our Dragon 4 project dedicated to the monitoring of seismic activity and the detection of lithospheric deformation by InSAR in China.

Starting from the analysis of the Envisat archive and moving toward exploiting the high-temporal resolution and wide coverage of Sentinel-1 data, we mainly focus on the recovery of small deformation signals associated with strain accumulation during the interseismic period along the main active fault systems on the northwestern and eastern edges of the Tibetan plateau (Altyn Tagh, Kunlun and Xianshuihe faults in particular). We present new methodological approaches to discriminate between such tectonic signals and non tectonic processes such as permafrost active layer’s response to climate forcing in sedimentary basins and other seasonal hydrological and atmospheric processes. We also show the potential of Sentinel-1 to capture such processes at the continental scale, presenting examples of average velocity maps obtained in eastern tibet by the FLATSIM automated processing chain. FLATSIM (ForM@Ter LArge-scale multi-Temporal Sentinel-1 InterferoMetry) is a service developed by CNES in the framework of the french Data and Services center ForM@Ter. The large scale products it provides enable refined 3D block modeling of joint GPS and InSAR data to discuss the present-day strain partitioning in eastern tibet. Finally, we present a case of investigation of potentially induced seismicity in the Sichuan basin : the occurrence of the 2019 Mw5.8 Changning earthquake in China.