Displays

Land subsidence and its subsequent hazardous effects on buildings and urban infrastructure are important issues in many cities around the world. The city of Uppsala in Sweden is undergoing significant subsidence in areas that are located on clay. Underlying clay units in parts of Uppsala act as mechanically weak layers, which for instance, cause sinking of the ground surface and tilting buildings. In this study, a Persistent Scatterer InSAR (PSI) analysis was performed to map the ongoing ground deformation in Uppsala. The subsidence rate measured with PSI was validated with precise leveling data at different locations. Two ascending and descending data sets were analyzed using SARPROZ software, with Sentinel-1 data from the period March 2015 to April 2019. After the PSI analyses, comparative permanent scatterer (PS) points and metal pegs (measured with precise leveling) were identified creating validation pairs. According to the PSI analyses, Uppsala was undergoing significant subsidence in some areas, with an annual rate of about 6 mm/year in the line-of-sight direction. Interestingly, the areas of great deformation were exclusively found on postglacial clay.

How to cite: Nilfouroushan, F. and Fryksten, J.: Analysis of Clay-Induced Land Subsidence in Uppsala City Using Sentinel-1 SAR Data and Precise Leveling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7322, https://doi.org/10.5194/egusphere-egu2020-7322, 2020.

Monitoring the deformation of large scale man-made structures is of vital importance for avoiding catastrophic loss of infrastructure and life. Many structures that require monitoring may span distances from few hundred meters, e.g. dams, to many tens of kilometers, e.g. dikes and levees. The widespread deterioration and some recent collapses of these man-made structures have highlighted the importance of developing effective structures monitoring strategies that can help identify structural problems before they become critical and endanger public safety. Moreover, the rapid pace of development has led to the establishment of a large number of linear-shaped structures such as reservoir dams. Spatial steadiness and operational security of these man-made facilities are becoming the focus of attention since deformation implies potential hazards or risks developing within or around these structures. Measuring and monitoring deformations of these man-made objects and structures is a key task of applied geodesy and geomatics engineering; however these deformation measurements techniques, though undeniably very accurate and reliable, are based on detecting the changes at specific points with the prior interest and investments in human resources or special equipment. The deformation monitoring schemes may vary greatly since they are targeted towards different deformation scenarios and mechanisms. In the last years, significant efforts have been undertaken by international researchers to find an efficient way for deformation monitoring of man-made structures. However, dams monitoring is still being a challenging task. In the case of dams, due to the high risk they represent, the supervision is regulated by national authorities. The main goal of the public supervision is to ensure a uniform high level of dams and appurtenant structures safety, and thereby to ensure that these structures are not posing a threat to life, property or the environment. Despite the fact that only little attention has been given to remote sensing technologies, the rapid development of space technology, occurred in the last decades, has allowed the detection of the displacement of Earth surfaces from space with high precision and unexpected benefits for Earth observation and related global studies. This progress has been possible thanks to microwave images obtained through Synthetic Aperture Radars (SAR) mounted on satellites and the development of Multi-Temporal Interferometry (MTI) techniques. MTI has the potential to support the development of new and more effective means of monitoring and analyzing the health of dams and add redundancy, at low cost, for their monitoring to support and assist warning systems. With SAR Interferometry specific dams can be monitored to identify and investigate targets with suspicious displacement on a monthly or weekly time-scale. As a result, timely identification of potential problems can help mitigate their impact on structural health and lower infrastructure rehabilitation costs.This paper presents the current status of RemoDams project, which is devoted to the monitoring of dam structural stability from space using satellite radar interferometry.

How to cite: Ruiz-Armenteros, A. M., Delgado-Blasco, J. M., Bakon, M., Sousa, J. J., Lamas-Fernández, F., Gil, A. J., Marchamalo-Sacristán, M., Sánchez-Ballesteros, V., Papco, J., González-Rodrigo, B., Lazecky, M., and Perissin, D.: Monitoring dams structural stability from space using differential SAR interferometry, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21356, https://doi.org/10.5194/egusphere-egu2020-21356, 2020.

The study of flooding events resulting from bank over-flooding and levee breaching is of large interest for both society and environment, because flood waves, resulting from levee failure, might cause loss of lives and destruction of properties and ecosystems. Understanding the subsoil mechanics and the fluid-solid interplay allows the stability condition estimate of dams, embankments and slopes and the development of early warning alarm systems. Changes in soil and hydraulic parameters are usually monitored by geotechnical and geophysical investigations that also provide the basic assumptions for developing hydraulic models. Nowadays, remote sensing approaches, including satellite techniques, are mainly used for flooding simulation studies. Indeed, remote sensing observations, such as discharge, flood area extent and water stage, have been used for retrieving flood hydrology information and modeling, calibrating and validating hydrodynamic models, improving model structures and developing data assimilation models. Although all these studies have contributed significantly to the recent advances, uncertainty in observations, as well as in model parameters and prediction, represents a critical aspect for using remote sensing data in the flooding defence. Compared to past and current methods for monitoring the fluvial levee failure, we propose a new procedure that provides a wide and fast alert system. The proposed methodological path is based on presumed relationships between ground level deformation and hydrological and surface soil properties, due to physical mechanisms and exhibited by geodetic and hydrological time series. The procedure is accomplished first through multi-methodological comparative analyses applied to geodetic, hydrological and soil-properties patterns, then through the mapping of the river zones prone to failure. Since the input consists of time series satellite-derived data, the geospatial Artificial Intelligence is applied for extracting knowledge from spatial big data and for increasing the performance of data computing. In particular, machine learning is initially developed for selecting the relevant geographical areas (i.e. rivers, levees and riverbanks) from large geo-referential datasets. Then, since the spatial-distributed points are also time-dependent, the trends of different datasets are compared point by point by selected analytical techniques. Finally, in accordance with the acquired knowledge from previous steps, the system extracts information on the correlation indexes in order to make sense of patterns in space and time and to identify hierarchic orders for the realization of hazard maps. The proposed method is “wide” because, unlike other direct surveys, it is able to monitor large spatial areas since it is based on satellite-derived data. It is also “fast” because it is based on the Earth’s surface observation and is not connected with Earth’s inland investigations (such as the geotechnical and geophysical ones) or with forecasting models (e.g. hydraulic and flooding simulations). Due to these peculiarities, the method can support flood protection studies and can be used for driving the localization of river portions prone to failure, where focusing detailed geotechnical and geophysical surveys.

How to cite: Di Maio, R., Vitagliano, E., and Salone, R.: Monitoring of levee breaching through remote sensing and artificial intelligence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3324, https://doi.org/10.5194/egusphere-egu2020-3324, 2020.

Today, the joint phenomena of rapid urbanization and population growth has resulted in an increase in the number of cities of over 10 million inhabitants, or megacities, worldwide.  While western megacities such as Los Angeles have been relatively stable in recent years, the developing world saw an increase from two to thirteen between 1975 and 2000 (http://www.igbp.net). In 2011, sixteen of the 23 global cities that fell into that category were coastal (UN-DESA 2012). Their growth is often coupled with unplanned urbanization and sprawl, with important effects on coastlines, demographics and ecosystems (Angel et al. 2011; Allison et al., 2016).  The associated risk is exacerbated by anthropogenic coastal subsidence processes and sea-level rise due to climate change, potentially increasing inundation, flooding, storm surges and infrastructure damage. Ground deformation phenomena, either uplift and/or subsidence, can arise from volcanic and tectonic processes, hydrocarbon exploitation, groundwater pumping and shallow compaction of sediments, particularly along coastal deltas. A better understanding of the processes affecting coastal megacities can be achieved through the combination of satellite and ground-based measurements.  Here we combine both high-resolution topography, in the form of optical digital surface models (DSMs), and differential interferometric synthetic aperture radar (DInSAR), to better characterize the effects of local and regional subsidence, coastal erosion, sea-level rise and urbanization in several megacities from around the developing world.   DInSAR time series from Sentinel-1A/B images, coregistered to high-resolution DSMs, are used to constrain local and regional ground deformation, while those same DSMs can be used to better model inundation due to sea level rise.  Here we present results for a number of cities, including but not limited to Mumbai, Lagos and Dhaka.

How to cite: Tiampo, K., Willis, M., Nerem, R. S., Eduard, H., and Joel, J.: Combining Sentinel-1A/B InSAR and high-resolution topography in the study of coastal megacities, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4267, https://doi.org/10.5194/egusphere-egu2020-4267, 2020.

The use of satellite interferometry (InSAR) is exponentially growing for the detection and monitoring of geohazard related movements. InSAR technique allows to process large areas and to extract high number of displacement measurements at low cost. By the way, the outputs consist of high volumes of information whose interpretation can be complex and time-consuming, mostly for users who are not familiar with radar data. Moreover, the use of InSAR have been moving from local to national, and now we are going towards a European application. In this scenario, the development of methodologies and tools to automatize the extraction of significant information and to facilitate the interpretation of the results, is more and more needed in order to increase their operational use. In this work we present a series of tools developed in the framework of the projects DEMOS (CGL2017- 83704-P), Momit (S2R-H2020/777630), Safety (ECHO/SUB/2015/718679) and U-Geohaz (UCPM-2017-PP-AG/783169). The so-called ADA (Active Displacement Areas) tools have been developed with the aim of ease the management, the use and the interpretation of wide areas results. Starting from the semi-automatic extraction of the most significant Active Displacement Areas (ADAFinder tool) we move to an automatic preliminary assessment of the phenomena that is behind the detected movement (ADAClassifier tool). All these tools go in the same direction of the European Ground Motion Service (EU-GMS) project, which will provide consistent, regular and reliable information regarding natural and anthropogenic ground motion phenomena all over Europe.

How to cite: Monserrat, O., Barra, A., Tomás, R., Navarro, J., Solari, L., Herrera, G., and Crosetto, M.: Tools for fast analysis of InSAR based displacement maps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18944, https://doi.org/10.5194/egusphere-egu2020-18944, 2020.

Satellite radar interferometry is widely considered as one of the most robust and reliable techniques for ground motion monitoring at local scale and over wide areas. In the recent years, satellite radar interferometry has undergone a rapid evolution thanks to the launch of the Sentinel-1 constellation, to the refinement of algorithms, and to the increased computational capability offered by cloud computing platforms. All these factors allow for the development of national or regional services based on satellite interferometric data. Italy, Norway, Germany, Denmark, and the Netherlands are the first European countries working to develop their own Ground Motion Service (GMS) at regional or national scale. Each service has its own characteristics, defined by the user needs and by the deformation regimes to be captured: some GMS work at regional scale with a high update frequency while other capture ground motions with e.g. one-year update frequencies over the entire nation. These examples demonstrate the high demand for interferometric products as wide area mapping or monitoring tools which are a direct request from national/regional entities and administrations involved in e.g. geohazard risk management or infrastructures monitoring.

As of November 2016, the European Ground Motion Service (EGMS) Task Force laid the foundation for a new Copernicus service aimed to perform Sentinel-1-based ground motion monitoring which relies on satellite interferometric products at continental scale. The work of the EGMS Task Force led to the creation of the EGMS White Paper (https://land.copernicus.eu/user-corner/technical-library/egms-white-paper), which is considered the conceptual baseline for the EGMS. In 2017, the Copernicus User Forum and the Copernicus Committee unanimously approved the addition of the EGMS to the Copernicus Land Monitoring Service’s product portfolio. The European Environment Agency (EEA) was designated to be responsible for the Service implementation. The EGMS will provide consistent, regular, standardized, harmonized and reliable information regarding natural and anthropogenic ground motion phenomena over Europe. Moreover, the entire product portfolio will be freely available for every private or public user, following the Copernicus data access concept. The EGMS will stimulate a wider use of PSI products all around Europe. As such, it is expected to act as a baseline for those nations already having an operational GMS and as primary data for countries that do not.

How to cite: Solari, L., Crosetto, M., Balasis-Levinsen, J., Casagli, N., Frei, M., Moldestad, D. A., and Oyen, A.: The European Ground Motion Service: a continental scale map of ground deformation., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3148, https://doi.org/10.5194/egusphere-egu2020-3148, 2020.

How to cite: Yu, C. and Li, Z.: Towards a new generation of Generic Atmospheric Correction Online Service for InSAR (GACOS 2.0), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9307, https://doi.org/10.5194/egusphere-egu2020-9307, 2020.

Rapid mapping of the extent of the affected area as well as type and grade of damage after a landslide event is crucial to enable fast crisis response, i.e., to support rescue and humanitarian operations. Change detection between pre- and post-event very high resolution (VHR) optical imagery is the state-of-the-art in operational rapid mapping of landslides. However, the suitability of optical data relies on clear sky conditions, which is not often the case after landslides events, as heavy rain is one of the most frequent triggers of landslides. In contrast to this, the acquisition of synthetic aperture radar (SAR) imagery is independent of atmospheric conditions. SAR data-based landslide detection approaches reported in the literature use change detection techniques, requiring VHR SAR imagery acquired shortly before the landslide event, which is commonly not available. Modern VHR SAR missions, e.g., Radarsat-2, TerraSAR-X, or COSMO-SkyMed, do not systematically cover the entire world, due to limitations in onboard disk space and downlink transmission rates. Here, we present a fast and transferable procedure for mapping of landslides in vegetated areas, based on change detection between pre-event optical imagery and the polarimetric entropy derived from post-event VHR polarimetric SAR data. Pre-event information is derived from high resolution optical imagery of Landsat-8 or Sentinel-2, which are freely available and systematically acquired over the entire Earth’s landmass. The landslide mapping is refined by slope information from a digital elevation model generated from bi-static TanDEM-X imagery. The methodology was successfully applied to two landslide events of different characteristics: A rotational slide near Charleston, West Virginia, USA and a mining waste earthflow near Bolshaya Talda, Russia.

How to cite: Plank, S. and Martinis, S.: Combined analysis of polarimetric SAR data and optical imagery for rapid landslide mapping in vegetated areas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1301, https://doi.org/10.5194/egusphere-egu2020-1301, 2020.

Monitoring of slow landslide movement on a local scale with Interferometric Synthetic Aperture Radar (InSAR) observations can provide long-term deformation information and assist in identifying failure triggers. We combined three different tracks of satellite radar images spanning 12 years from ALOS-1 PALSAR-1, ALOS-2 PALSAR-2, and Sentinel-1 to assess the evolution of a landslide in Bolivia where the village of Independencia lies at the slope foot. For ALOS-1 PALSAR, SAR data was acquired on 15 dates during the period from 28 February 2007 to 11 March 2011 in ascending mode. For ALOS-2 PALSAR-2, eight acquisitions between 07 October 2015 and 29 November 2017 were available in ascending mode. The low temporal resolution of ALOS images makes the detection of deforming signal difficult though the L-band data captures more coherent pixels on vegetation areas than C-band. Sentinel-1 data with a minimum time interval of six days from 16 October 2014 to 08 September 2019 (144 images) is collected and processed to recover the dynamic behaviour of the landslide movement.

To explore the sensitivity of different InSAR time series analysis methods on revealing the deformation pattern of the landslide, we respectively used Persistent Scatterer Interferometry (PSI), Small Baseline Subset (SBAS) algorithm and Distributed Scatterer Interferometry (DSI) based on phase eigenvalue-decomposition to process the mentioned multiple satellite radar observations. Overlapping valid pixels from these three methods share similar temporal evolution while SBAS and DSI trace more measurement points than PSI in spatial distribution. Preliminary results show that the village central exhibits extremely slow movements (<= 10 mm/yr) with seasonal oscillation. The north edge of the village in the middle of the landslide body retains stable until 2018. Deformation time series after early 2018 perform an acceleration from about 5 mm/yr to 15 mm/yr. Such acceleration may result from artificial irrigation activities, precipitation or internal landslide reactivation, and we expect to collect more ground evidence to interpret the acceleration. To conclude, the failure risk of this landslide is relatively higher since 2018 and is more noteworthy than before.

How to cite: Song, C., Li, Z., Utili, S., and Yu, C.: Twelve-Year Landslide Risk Assessment in Villa de Independencia, Bolivia, with Sentinel-1 and ALOS-1/2 InSAR Observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20193, https://doi.org/10.5194/egusphere-egu2020-20193, 2020.

Polders in the western Netherlands are often covered by pastures. Around 30 percent of the pastures are situated on peat soils, which are artificially drained. Consequently, the exposure to oxygen leads to a decomposition (oxidation) of the material and desiccation leading to shrinking. This results in a decadal subsidence, up to a few centimeters per year, which causes increasingly severe socio-economic impact. However, this long-term subsidence signal has a high spatial variability due to local soil morphology, and possibly high intra-annual temporal variability which is caused by precipitation and evaporation. The problem is that there are currently no geodetic methods that can reliably measure these soil dynamics over wide areas and with high temporal revisits.

Here we show how Sentinel-1 SAR interferometry (InSAR) can potentially be used to estimate the surface displacements, given prior information on precipitation and temperature. We observe intra-annual dynamics of surface elevation which seem to be one order of magnitude stronger than the decadal long-term subsidence. InSAR surface elevation measurements show  discontinuities (hysteresis) in late summer and early autumn due to strong vegetation and changes in temperature and precipitation patterns. As soil moisture variability appears to be the main driving mechanism for the observed surface elevation dynamics, we investigate whether we can use the amplitude of the identical SAR acquisitions to estimate the soil moisture directly, to reduce the dependency on external precipitation and temperature data.

The analysis is performed on time series of the European Space Agency’s Sentinel-1 mission. Subsidence and upheaval are estimated using a novel InSAR algorithm, which was specially designed for peat soil dynamics. The surface elevation dynamics are compared to surface soil moisture estimates from Sentinel-1 amplitude  data. Soil moisture is retrieved from backscatter time series using a first-order radiative transfer model (RT1) developed at TU Wien. This model describes the scattering behaviour of both soil- and vegetation by using linear combinations of idealized scattering distribution functions. Clay Soil swelling and subsidence are likely influenced by soil layers much deeper than those associated with the surface soil moisture estimates. Therefore, the subsidence estimates are also compared to Soil Water Index (SWI) derived from the surface soil moisture product. This is considered an indicator of moisture availability in the top 100 cm. These results show that the same complex SAR data acquisitions can be used simultaneously, but independently, for estimating soil moisture and for estimating surface elevation dynamics. An integrated application is proposed and evaluated for further exploration.

How to cite: Bentvelsen, F., Heuff, F., Steele-Dunne, S., Wagner, W., Quast, R., and Hanssen, R.: On the influence of soil moisture on intra-annual peat soil dynamics as observed from SAR amplitude and phase data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18234, https://doi.org/10.5194/egusphere-egu2020-18234, 2020.

The Sentinel-1 constellation of the Copernicus Program already represents a big revolution within the Earth Observation (EO) scenario. This result is mainly due to the capability of this constellation to acquire huge volumes of SAR data all over the globe, with a wide spatial coverage, a short revisit time (12 or 6 days in the case of one or two operating satellites, respectively), and a free and open access data policy. In particular, the availability of such a large amount of SAR data acquired through the TOPS mode, characterized by a short “orbital tube” (with a 200m nominal diameter) and a specific design for ensuring differential SAR interferometry (DInSAR) applications, has opened the possibility to investigate Earth surface deformation phenomena at unprecedented spatial scale and with a high temporal rate.

Among several advanced DInSAR algorithms, a widely used approach is the Small BAseline Subset (SBAS) technique, which has already proven its effectiveness to investigate surface displacements with centimeter- to millimeter-level accuracy in different scenarios. Moreover, a parallel algorithmic solution for the SBAS approach, referred to as Parallel Small BAseline Subset (P-SBAS), has been recently developed. This approach permits to generate, in an automatic and unsupervised way, advanced DInSAR products by taking full benefit from parallel computing architectures, such as cluster, grid and, above all, cloud computing infrastructures.

In this work we present the results of a DInSAR experiment, based on the P-SBAS approach, carried out at the European scale. In particular, we exploited the entire available Sentinel-1 dataset collected through the TOPS acquisition mode between March 2015 and September 2018 from descending orbits over large part of Europe. Moreover, the overall analysis wasbcarried out by using the Copernicus Data and Information Access Services (DIAS) and, in particular, those provided by the ONDA DIAS platform, which was selected through a public tender. This activity, carried out as stress test of the EPOSAR service included in the Satellite Data Thematic Core Service of the EPOS infrastructure, permitted to investigate the DIAS capacity to operationally serve systematic and automatic DInSAR processing services, such as the one based on the P-SBAS approach.

Our experiment was successfully completed, allowing the retrieval of the deformation time-series of the overall investigated area with the final products having the main characteristics summarized in the following:

• Exploited Sentinel-1 data: ~72.000
• Covered Area: ~4.500.000 km²
• Coherent (multilook) SAR pixels: ~120.000.000
• Final products pixel dimension: ~80 m
• Time elapsed: ~6 months

The presented discussion will highlight the main pros and cons of the exploited solution for such wide area DInSAR experiment. Moreover, the analysis of the achieved results will also show the high quality of the retrieved DInSAR results, that can be of interest for the Solid Earth scientific community, and the potentially positive impact of the presented solution for what concerns the future development of the European Ground Motion Service.

This work is supported by: the 2019-2021 IREA-CNR and Italian Civil Protection Department agreement; the H2020 EPOS-SP project (GA 871121); the I-AMICA (PONa3_00363) project; and the IREA-CNR/DGSUNMIG agreement.

How to cite: Lanari, R., Bonano, M., Buonanno, S., Casu, F., De Luca, C., Fusco, A., Manunta, M., Manzo, M., Onorato, G., Zeni, G., and Zinno, I.: Continental scale SBAS-DInSAR processing for the generation of Sentinel-1 deformation time series within a cloud computing environment: achieved results and lessons learned, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17944, https://doi.org/10.5194/egusphere-egu2020-17944, 2020.

The exploitation of ever increasing Interferometric Synthetic Aperture Radar (InSAR) datasets to monitor the Earth surface deformation is an important goal of today’s geodesy. Surface geodetic deformation observations are often the result of the combination of a multitude of sources (either volcano-tectonic deformation associated with seismic events, post-seismic relaxation, aseismic transients, long-term creep loading, magma intrusions or non-tectonic deformation associated with hydrological loads, poroelastic rebound, anthropic activity and various sources of noise). In this regard, we are facing a so-called Blind Source Separation (BSS) problem. Natural approaches to tackle BSS problems are those multivariate statistical techniques which attempt to decompose the dataset into a limited number of statistically independent sources, under the assumption that the different physical mechanisms underlying the observations have independent footprints either in space or time. Multiple algorithms have been proposed to separate the various independent sources, and here we show the capabilities of a variational Bayesian Independent Component Analysis (vbICA) algorithm. In particular, we show through synthetic test cases its superiority with respect to other commonly used multivariate statistical techniques like the Principal Component Analysis (PCA) and the FastICA algorithm. Application of vbICA to InSAR time series from European Space Agency (ESA) Sentinel-1 satellite in the Central Valley and on the Central San Andreas Fault segment, California, spanning the time range 2015-2019, shows that the algorithm provides a viable way to separate elastic and inelastic deformation in response to the aquifer charge/discharge as well as creeping signal from seasonal loading.

How to cite: Gualandi, A. and Liu, Z.: Variational Bayesian Independent Component Analysis for InSAR displacement time series with application to California, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19567, https://doi.org/10.5194/egusphere-egu2020-19567, 2020.

Deformation of the Earth’s surface affects the maintenance of geodetic infrastructure and its reference frame to support e.g., construction, mineral exploration, telecommunications, and environmental monitoring. As the land deforms, the 3D coordinates of each position will change within the reference frame. Monitoring these changes is particularly challenging for local deformation occurring between GNSS continuously operating reference stations (CORS), as it is not directly measured. Hence, a deformation model to correct for this deformation is required, using radar interferometry (InSAR) to measure localised deformation occurring between the sparse GNSS CORS. The Australian Intergovernmental Committee for Surveying and Mapping’s (ICSM’s) Permanent Committee on Geodesy has recently identified the need for such a deformation model, leading to a project to develop a prototype deformation model combining radar interferometry with other geodetic measurements.

We present the first stage of this project where these data are analysed in the Latrobe Valley study area (south east Australia), where we have used 2.7 years (2015-2018) of Sentinel-1 and ~4 years (19 scenes; 2007-2011) of ALOS PALSAR SAR data to provide estimates of line of sight (LOS) velocity and uncertainties. Time series from five local GNSS CORS have been reprocessed in a consistent reference frame (ITRF2014) giving 3D velocities and uncertainties to which the InSAR time series are referenced. The InSAR rates are converted from LOS to vertical within the ITRF2014 reference frame so that the results are comparable to other geodetic measurements. Repeat levelling measurements from 1980 and 2015 and periodic (non-continuous) GNSS measurements were included for 2015.9 - 2018.5, which provided complementary information to constrain the rates in the study area in both time and space. We test methods to combine these data that relate to different time periods, spatial location, temporal and spatial frequency. We find that all of the data contribute to our understanding of deformation in the Latrobe Valley:  GNSS data shows temporal variations at specific sites, InSAR gives information about the spatial variation in deformation, periodic GNSS provides information at additional spatial locations but at limited points in time, and levelling extends the time series several decades into the past. Subsidence rates approaching 30 mm/yr are found near an open cut mining pit, but the deformation is non-linear in time and space across the study area, adding to the challenge of modelling the deformation where the geodetic observations are sparse. An important outcome of the project is to determine which types of observations best constrain the deformation model and how much new data is required.

How to cite: Filmer, M., Johnston, P., Fuhrmann, T., Garthwaite, M., and Woods, A.: Development of a land deformation model from InSAR: combination with heterogeneous geodetic measurements in the Latrobe Valley (Australia) test site, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1709, https://doi.org/10.5194/egusphere-egu2020-1709, 2020.

Rock glaciers are perennially frozen bodies of ice and rock debris that move downslope primarily due to deformation of internal ice. These features play an important role in alpine hydrology and landscape evolution, and constitute a significant water resource in arid regions. In the Uinta Mountains, Utah, nearly 400 rock glaciers have been identified on the basis of morphology, but the presence of ice has been investigated in only two. Here, I use satellite-based interferometric synthetic-aperture radar (InSAR) from the Copernicus Sentinel-1 satellites to identify and monitor active rock glaciers over a 10,000 km² area. I also compare the time-dependent motion of several individual rock glaciers over the summers of 2016-2019 to search for relationships with climatic drivers such as precipitation and temperature. Sentinel-1 data from the August-October of 2016-2019 are used to create 79 interferograms of the entire Uinta range and are processed with the NASA/JPL/Stanford InSAR Scientific Computing Environment (ISCE) software package. Temporal baselines of intrayear interferograms range from 6-72 days. We use average velocity maps to generate an active rock glacier inventory for the Uinta Mountains containing 196 active rock glaciers. Average rock glacier velocity is 3 cm/yr in the line-of-sight direction, but individual rock glaciers have velocities ranging from 0.3-15 cm/yr. Rock glacier speeds do have a seasonal component, and were fastest in August across all years. One rock glacier reached a speed of 40 cm/yr over a 12 day interval from August 5 to August 17 of 2017. Preliminary results suggest that active rock glaciers are found at altitudes 10 m higher on average than inactive and relic rock glaciers identified in the previous inventory. Rock glacier movement did not accelerate between 2016 and 2019, suggesting that rock glaciers in this part of the Rocky Mountains are not speeding up over time. Our results highlight the ability to use satellite InSAR to monitor rock glaciers over large areas and provide insight into the factors that control their kinematics.

How to cite: Brencher, G., Handwerger, A., and Munroe, J.: Using InSAR to asses rock glacier movement in the Uinta Mountains, Utah, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11395, https://doi.org/10.5194/egusphere-egu2020-11395, 2020.

For a multi-look polarimetric synthetic aperture radar (POLSAR) image, each pixel corresponds to a polarimetric coherency matrix. Model-based incoherent polarimetric decomposition is a technique which is widely used to analyze multi-look POLSAR data. Traditional model-based incoherent polarimetric decomposition algorithms have some inherent drawbacks such as negative power components, polarimetric information loss, and non-model-based decomposition results. This study tries to completely interpret a polarimetric coherency matrix by the incoherent sum of four scattering mechanisms. Therefore, the proposed algorithm can be regarded as a new type of model-based incoherent polarimetric decomposition. All the four scattering models are firstly derived with polarimetric symmetry. The four scattering models correspond to surface scattering, double-bounce scattering, volume scattering and helix scattering, respectively. Then a new four-component model-based incoherent decomposition algorithm is found. After extracting the helix scattering component and the maximum possible volume scattering component, the remaining coherency matrix is decomposed into two components with an orientation angle difference of 45°. With the new algorithm, most pixels of a real POLSAR image can be completely decomposed into four components which are exactly consistent with helix scattering, volume scattering, surface scattering, and double-bounce scattering, respectively. Moreover, the proposed decomposition algorithm fully utilizes the polarimetric information, and all scattering component powers are nonnegative. Experiments with E-SAR, RADARSAT-2, and GF-3 data are presented to illustrate the effectiveness of analyzing the scattering mechanisms of real terrain targets with the proposed decomposition algorithm. The proposed decomposition algorithm is also compared with classic four-component model-based incoherent polarimetric decomposition algorithms.

How to cite: An, W. and Lin, M.: The Interpretation of a Polarimetric Coherency Matrix with Four Scattering Models Considering Polarimetric Symmetry, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2538, https://doi.org/10.5194/egusphere-egu2020-2538, 2020.

On June 17, 2019, an Ms 6.0 earthquake occurred in Changning, Sichuan, China (the Changning event), which is the largest earthquake within 50 km of the area since records began. It has attracted great attentions as this region is one of the largest shale gas production areas in China. The cause, the fault structure, and the earthquake effects remain the center of debates.

Using Interferometric Synthetic Aperture Radar (InSAR) data, we measure the coseismic deformation and build the fault models of the Changning event and two earlier Ms>5.0 earthquakes (P1:2018/12/16 Ms5.7 and P2:2019/1/3 Ms5.3) using Sentinel-1 and ALOS2 satellite data. From the coseismic interference of ALOS2, the deformation caused by P1, P2, and the Changning event as well as some of their aftershocks can be clearly identified. The deformation caused by the Changning event affects an area of about 150 km² and the surface deformation is mainly uplift with a maximum of 17.2 cm (towards the satellite). We obtain two fault models for the Changning event. The model inclining southwest has a smaller fitting error than the model inclining northeast and is more consistent with the distribution characteristics of aftershocks and local underground structure. The final model shows that the Changning event was caused by a fault with left-lateral strike and thrust slip. The strike is 124.9° with a dip angle of 49.8°. The inversed seismic moment is 4.79×10¹⁷ Nm, corresponding to Mw 5.75.

On the basis of the fault models, we analyze the cause of the Changning earthquake from the following three aspects: (1) Stress change. The cumulative stress change of P1 and P2 on the Changning event fault is less than 0.1 MPa, which is too small to trigger an Ms 6.0 earthquake. Therefore, there is no direct triggering relationship between the Changing event and event P1 or P2. (2) Aftershock distribution. The aftershocks of the Changning event are negatively correlated with time. The Time-Number curve of the aftershocks well obeys the Omori-type aftershocks law. It is inconsistent with the characteristics of a triggered or induced earthquake which has more pre-earthquakes and rapidly decreasing aftershocks. (3) Tectonic backgrounds. The movement of the Changning earthquake fault is accord with the local tectonic motion. Moreover, the causative fault we inferred coincides with a fault located in the basement, which was found by the seismic reflection profile analysis. The fault in the basement is likely to be related to the Changning earthquake.

Therefore, there is no direct evidence showing that the Changning earthquake was induced by shale gas production or other human activity. We consider that the event is a naturally tectonic earthquake.

How to cite: Gao, H., Liao, M., Xu, W., and Liu, X.: Was the 2019 Ms6.0 Changning earthquake in Sichuan, China caused by human activities? —— Analysis of fault structure and seismogenic mechanism based on InSAR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3291, https://doi.org/10.5194/egusphere-egu2020-3291, 2020.

Valleys in the epicentre of Wenchuan Earthquake (Sichuan Province, China) are severely subjected to landside risks partially due to the persistent influences of the serious earthquake in 2008. Without enough regionally in-situ monitoring measures, the method of multi-temporal, differential interferometric synthetic aperture radar (D-InSAR) provides an efficient to monitor the surface subsidence and thus the landslide vulnerability. In this study, we used the Sentinel Satellite Images (2015-2018) to extract the subsidence information along river valleys near the Wenchuan Earth epicentre, which was well validated by the in-situ observation of one GPS station (RSME=1.6 cm, p<0.01). Our results showed the persistent ground subsidence (1.5 mm yr^-1, p<0.01) at many places, which was also related to terrain aspect besides to the well-proved conditions of slope, vegetation cover and soil layer. This fact that implied the terrain aspect should be taken into accounts in landside vulnerability analyses, because precipitation is locally more abundant in windward places. Results emphasized the higher vulnerability of landslide in summer, which could be attributed to more precipitation during summer in the study area. Our study extracted over 100-km valleys (and especially ~50 places) with high landslide vulnerability (subsidence rate > 1.20 mm yr^-1), which should be paid high-prior careful attentions so as to avoid potential geological disasters.

How to cite: Zhang, W.: Detecting the landslide vulnerability in the epicentre of Wenchuan Earthquake via SBAS-InSAR method, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3907, https://doi.org/10.5194/egusphere-egu2020-3907, 2020.

The advances of Sentinel-1 SAR data, like its open access policy and short revisit time, gives an outstanding opportunity to conduct in-situ mapping of large scale deformations. After the requisite calibrations and corrections (radiometric, terrain), geocoding, coregistration and phase unwrapping; the unwrapped phase can be converted to Line-of-site (LOS) displacements. Although it gives a characteristic picture of the investigated phenomena only in one-dimension, but to obtain tree-dimensional (East/North/Up – ENU) deformation, it requires a more complex approach.

To obtain the complete tree-dimensional displacement field, both ascending and descending LOS displacements shall be retrieved. As well as, the corresponding unit-vector of LOS look-vectors and its parallel, along-track azimuth vector in the direction of the azimuth offsets, from the SAR sensor to all measurements (pixel) in ENU format. This lead to four observations with different incident angles for each measurements, which can be generalized as an over-determined inverse problem. The estimated model vector of the complete tree-dimensional displacement can be obtained, if the Jacobi-matrix can be represented as the look-vectors in ENU basis and the observation vector as LOS deformations acquired from the unwrapped phase of the interferogram. Then the over-determined linear equation system can be solved in the L2 norm via the Gaussian Least Squares (LSQ) approach combined with Singular Value Decomposition (SVD).

Demonstrating the aforementioned, we present the continuation of DInSAR results of the two strike-slip earthquakes between 2019.07.04-06. with foreshock M_W =6.5 and mainshock M _W =7.1 in the Eastern Californian Shear Zone near Ridgecrest (US).

How to cite: Horvath, R., Magyar, B., and Kenyeres, A.: Derivation of 3D deformation fields for the 2019 Ridgecrest Earthquakes (USA) based on Sentinel-1 TOPS data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4806, https://doi.org/10.5194/egusphere-egu2020-4806, 2020.

Three Gorge area landslide hazards developed very fast after the Dam started to impound the water since 2007. There were lots of research literatures concentrated on the Badong Huangtupo Landslide area for the whole city center had to change its position in 2009. Several literatures used Envisat SAR images time series to monitoring the surface deformation from 2008~2010. The results showed good consistent with the water level changes and precipitation.  The high resolution TerraSAR Spotlight images had been used to monitoring the Shuping landslide and Fanjiaping landslide area in Zigui country from 2009~2012,the InSAR results showed good details of the landslide boundary and deformation rate with DInSAR technology.

This paper studies several landslide area in the Three Gorge by InSAR technology in the past few years, such as Huangtupo, Huanglashi , Daping and  Baiheping landslide area , etc. al . The high resolution SAR images covered Badong and Wushan area have been collected, including the Sentinel-1, TerraSAR, RadarSAT-2, ALOS-2 SAR images. The high resolution topography in those landslide area have been collected both by UAV lidar and high resolution topography map.

The Huangtupo landslide area changed a lot in the past 3 years with the buildings ruins cleared and red soil covered by the local government. The time series results by Sentinel data in this area shows the big changes but could not derive reasonable deformation results.

Three Gorges Research Center for Geo-hazards (TGRC) of China University of Geosciences(CUG) built the Badong field test site in Huangtupo landslide area. This test site is composed with a tunnel group and a series of monitoring system including the inside sensors, surface deformation monitoring sensors and so on. In this paper, we mounted several new designed dihedral corner reflectors on the Huangtupo landslide area for high precision deformation monitoring by InSAR. Both the  ascending and the  descending orbit data of RadarSAT-2 high resolution SAR image  and TerraSAR Spotlight images have been collected in this field.

The preliminary results from those new acquiring SAR data series show that the traditional landslide area such as Huanglashi , Daping, Baiheping are all moving slowly with good coherence in SAR image series.  The poor vegetation coverage in those landslide area helped to get the credible  InSAR results. The high resolution DEM is the critical elements for the DInSAR techniques in those landslide area. The steep  topography in those landslide area distorted the SAR images correspondingly.

Our results shows that it is possible to use ascending and descending high resolution SAR images to monitor the landslide area with mm level precision, while the vegetation is not so dense. High resolution SAR interferometry helped a lot for the landslide boundary detection and detailed analysis. The lower resolution SAR images such as Sentinel-1 still could provide some deformation results in landslide area, but it need more auxiliary data to interpret the results.

How to cite: Li, T., Wen, Y., Chen, L., and Wang, J.: Monitoring Three Gorge Area Landslide currently movement by Mutilplatform SAR Interferometry, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5334, https://doi.org/10.5194/egusphere-egu2020-5334, 2020.

SAR imaging geodesy is a new technique in the field of geodesy and remote sensing that enables the 3D localization of specifically designed radar targets. The absolute 3D position of a radar target in the ITRF can be estimated by means of least squares adjustment, when combining at least two sets of radar coordinates extracted from SAR images and the corresponding orbital arcs given by precise orbit determination. The installation of permanent radar targets allows for long-term position monitoring, making the technique a particularly interesting candidate for displacement and height change observations. While the principle of geodetic positioning with SAR is well-established, the selection of the radar target suitable for an application is subject to discussion. Parameters to be considered are the resolution of the radar images which can be provided by satellites like Sentinel-1 or TerraSAR-X, the size of the radar target with respect to the image resolution, the required localization accuracy of the selected application, and possible environmental and/or technical limitations at the installation site. Two main categories of artificial radar targets can be identified: passive reflectors and active transponders. Examples of passive reflectors that have been tested at geodetic observatories are corner reflectors, octahedron reflectors and tophats, while an example of active transponders is the experimental Electronic Corner Reflector (ECR).

The poster illustrates the first results acquired from the testing of ECRs operating in C-band, and their 3D localization using the IW medium resolution products of Sentinel-1A and 1B. The operation principle, the installation and mounting options, and the use of the ECRs as a small and portable alternative to passive reflectors are additionally discussed.

How to cite: Oikonomidou, X., Eineder, M., Gisinger, C., Gruber, T., Heinze, M., and Sdralia, V.: SAR Imaging Geodesy with Electronic Corner Reflectors (ECR) and Sentinel-1 – First Experiences, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5608, https://doi.org/10.5194/egusphere-egu2020-5608, 2020.

Rapid evaluation of building earthquake disaster information is of great significance for earthquake emergency rescue. Although polarimetric SAR has rich polarimetric information, there are still clear texture information in polarimetric SAR that could not be ignored, especially the intact artificial buildings show regular texture features in the image, and the texture distribution in the collapsed building area is disordered, so combining the texture information can also extract the building information well. In this paper, the full polarization SAR data of Yushu area in 2010 is taken as the research object, and the building area in SAR image is extracted by using the volume scattering component P_V in Yamaguchi decomposition. On this basis, the intact building area and collapsed building area are extracted based on the variogram value. Comparing and analyzing the result with the intact building area is extracted by using the secondary scattering component P_D in Yamaguchi decomposition. Finally, verified the accuracy by combing the optical remote sensing image after the earthquake, the extraction accuracy of intact buildings is 80.18%, collapsed buildings is 84.54%, and road water system is 77.58%.

Firstly, buildings and non-buildings are distinguished in SAR image. 100 sample matrixes are selected in building area and non-building area on P_V component image respectively. After calculating the mean value of sample matrixes, the threshold values of building and non-building area are obtained based on the minimum error, and the building area and non-building area are extracted respectively according to the threshold values. Secondly, in the building area, the sample matrix of intact buildings and collapsed buildings is selected to calculate the variograms value, and then the variograms curve is drawn. When the range a = 11, the variograms value of the building area is calculated, and the FCM algorithm is used to extract the calculation results of intact buildings and collapsed buildings respectively; In order to compare and analyze the classification results, based on P_D component, use K-means algorithm to extract intact buildings and the collapsed building areas are extracted separately, and the results are compared with the results based on the variogram texture feature method. Finally, the intact buildings and collapsed buildings extracted are calibrated and the extraction accuracy is calculated by combining the Google Earth historical image.

At the end of this paper, the shortcomings of extraction results based on Yamaguchi four component decomposition method and variogram method are discussed, and the idea of combining geographic information data to further improve the accuracy of earthquake damage assessment is proposed.

How to cite: Zhai, W., Xiao, X., and Zhang, H.: Building Damage Information Extraction From Fully Polarimetric SAR Images Based on Variogram Texture Feature , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7235, https://doi.org/10.5194/egusphere-egu2020-7235, 2020.

Since launching Sentinel 1 satellites, the European Space Agency has been providing a huge amount of repeated SAR data. Thanks to 6-days revisiting time, it creates a perfect possibility for the monitoring of ground deformation, caused by underground mining activity, by using Differential SAR interferometry (DInSAR).

Because, DInSAR exploits single interferometric SAR pairs, the accuracy of this technique is limited by spatial and temporal decorrelation and atmospheric artifacts. To minimize the atmospheric influence on DInSAR results, we investigated precipitation and relative humidity data acquired from the Institute of Meteorology and Water Management (IMGW). Theoretically, the summed atmospheric LOS errors due to relative humidity for 106 ascending and 112 descending images are -3.5 cm and 7,5 cm, respectively.  In fact, we observed that there is a moderate correlation between precipitation/relative humidity and “bad” acquisition in relatively small study area. Nevertheless, we were able to remove 33 ascending and 15 descending images from the queue of consecutive DInSAR. Finally, it allowed to estimate up to 1m subsidence in the period of 1 Jan 2017–8 Oct 2018 in the Rydułtowy mine located in the southwest part of the Upper Silesian Coal Basin (USCB), Poland.

To evaluate our DInSAR accuracy due to atmospheric artefacts, we decided to compare the results with “atmospheric-free” results acquired by SBAS technique. SBAS separates diverse interferometric components that correspond to deformation, topographic error, atmospheric error, and orbital errors.

The Root-Mean-Square Error (RMSE) has been calculated between SBAS and DInSAR for selected subsidence profiles. The maximal RMSE was found to be 3.6 cm and 4.1cm for ascending and descending LOS displacements, respectively. This shows that DInSAR cannot be used for monitoring millimeter-level deformation. On the contrary, it can be effectively used to assess quick nonlinear deformations reaching several decimeters /year such as in the presented study case.

How to cite: Pawłuszek-Filipiak, K. and Borkowski, A.: InSAR techniques to determine mining-related deformations using Sentinel-1 data: the case study of Rydułtowy mine in Poland., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10510, https://doi.org/10.5194/egusphere-egu2020-10510, 2020.

Geodetic data provide useful information on surface deformation over long period of time. Applying time series methods to geodetic data, several phenomena were studied. In particular, the potentials of geodetic data were exploited to detect and measure slow tectonic signals such as interseismic strain accumulation. During the interseismic period, when the faults are locked, an accumulation of deformation can occur in response to active tectonic stresses. Considering that such energy can be released through earthquakes, the estimation of surface deformation and the long-term strain rate reveals itself a useful approach for seismic hazard investigations. In this study, we used remote sensing Synthetic Aperture Radar data to evaluate the ground deformation in the Southeastern Alps (Northeastern Italy), an area characterized by an active convergent regime (Adria plate motion is ~ 2mm/yr) as well as several active tectonic structures. We used SAR images provided by Sentinel-1A/B satellites spanning the 2015-2019 temporal interval by applying the multi temporal Small Baseline Subset Interferometry (SBAS) technique. The method is based on a combination of a large number of interferograms characterized by small temporal and geometric baseline in order to reduce decorrelation effects and increase the spatial coverage over the area of interest. The outcomes consist of displacement time series and a mean ground velocity map for each coherent pixels with respect to the satellite Line-of-Sight (LoS). Some detected patterns can be attributed to subsidence phenomena, affecting the plain in the area under analysis, and due to the compaction of the sediments.

How to cite: Areggi, G., Tolomei, C., Bonini, L., and Pezzo, G.: Surface Deformation in Northeast Italy by using time series InSAR techniques with Sentinel-1 data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10549, https://doi.org/10.5194/egusphere-egu2020-10549, 2020.

The level of intensity of induced seismic phenomena occurring in areas of mining activity is very diverse. Induced shocks may be directly related to the exploitation carried out or to mining and tectonic factors. In the case of impact on the surface, two types of mining tremors are distinguished: energetically weak shocks, not causing surface deformation, and shocks exceeding a certain energy level, which cause terrain deformations. Surface displacements are the most common form of the effects of underground mining operations, including induced seismicity. Geological research uses Sentinel-1 imagery to determine the geometry of surface displacements that were caused by induced shocks by satellite radar interferometry. In this research four induced shocks with magnitude M>4.0 was used, which occurred in the Legnica-Glogow Copper District in the Rudna mine. This area is one of the most seismically active places in Poland due to the underground exploitation of copper ore. For calculations, the differential satellite radar interferometry (DInSAR) method was used. The DInSAR technique allowed the determination of surface displacement towards the Line of Sight (LOS) between two images acquired at different times (before and after induced shock) with millimeter accuracy. In the presented research calculations were carried out separately for observations acquired in descending and ascending orbits. The Sentinel-1 satellites are a constellation of two radar satellites that observe the surface of lands and oceans at a time interval of 6 days. Therefore, 6 days, 12 days, 18 days and 24 days were assumed as the time intervals between the images. Vertical displacements were calculated based on the generated LOS displacement maps. In addition, charts of subsidence in the N-S and W-E directions were prepared, 3D models of subsidence were made, and deformation geometry was analyzed for individual shocks. As a result of the research, the spatial extent of deformation in the horizontal surface was determined: N-S and W-E, which in both directions was over 2 km. However, surface displacements caused by induced shocks reached values up to 10 cm.

How to cite: Owczarz, K., Kopeć, A., and Głąbicki, D.: Geometry of surface deformations caused by induced shocks in the area of underground copper exploitation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11185, https://doi.org/10.5194/egusphere-egu2020-11185, 2020.

The work focuses on time series analysis application through the high temporary resolution imagery from the SENTINEL 1A/1B mission. The analysis of surface subsidence in open pit mining area was performed by the selected InSAR approach - small baseline InSAR. This methodology allows for continuous monitoring of the mining area. The study was performed in the 700 km^2 mining area of the PGE GiEK KWB Belchatow mine in Central Europe (Area Of Interest, AOI). The SAR imageries acquired by the SENTINEL 1A/1B satellite for the 124-descending track in two years period - 10.2015 and 01.2017 have been used in the analysis. The post-proceed satellite LOS (Line of Sight) displacement indicates vertical changes of the surface within the dumping and excavation area. The analyzed AOI shows total subsidence of ca. -500 mm, whereas the excavation area shows a trend of terrain uplift ca. +250 mm during the analyzed periods. The presented processing pathway allows for the early detection of landslides in near real-time. Future work will focus on the accuracy assessment of analyzed data and detection of horizontal displacements of the AOI.

How to cite: Wajs, J. and Milczarek, W. J.: Detection of surface subsidence using SAR SENTINEL 1A imagery and the short baseline InSAR method – a case study of the Belchatow open pit mine, Central Poland., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11226, https://doi.org/10.5194/egusphere-egu2020-11226, 2020.

We quantify deformation patterns resulting from tectonic motions and surface processes across the central Tibetan Plateau (29–45ºN, 83–92ºE) since late 2014 using ascending and descending passes of the Sentinel-1A and -1B radar satellites. The broad spatial extent of these data (> 10⁶ km²), fine spatial resolution (originally 90 m pixels, resampled to 270 m pixels), and high rate of temporal sampling (12–24-day orbit repeat time) offer unprecedented resolution of surface deformation in space and time. To process such an extensive data set – including more than 100 dates and 300 interferograms per track thus far – we leverage the Advanced Rapid Imaging and Analysis (ARIA) standardized interferometric synthetic aperture radar (InSAR) products and toolbox. We construct time series of surface deformation constrained from our Sentinel-1 interferograms using the small baseline subset approach implemented by the Miami InSAR time series software in Python (MintPy). Our preliminary results from three Sentinel-1 orbits (two descending and one ascending; each comprising 10 frames along track) allow us to quantify deformation in the satellite lines of sight. Combinations of ascending and descending track measurements are used to approximate east-west and vertical ground velocities. The resulting velocity fields will provide a more complete and accurate picture of interseismic strain accumulation rates across active faults in the region such as the Altyn Tagh and Kunlun faults, and allow us to study surface processes such as permafrost active layer dynamics and isostatic adjustment due to lake level changes in unparalleled scope and detail.

How to cite: Zinke, R., Peltzer, G., Fielding, E., Sangha, S., Bekaert, D., and Owen, S.: Tectonic Deformation and Surface Processes of the Tibetan Plateau Constrained by Time Series Analysis of Sentinel-1 InSAR Data , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11930, https://doi.org/10.5194/egusphere-egu2020-11930, 2020.

Musan mine in North Korea is the largest open-pit iron mine in Asia with the proved reserves of about 2.06 billion tons and more than 9 square kilometers. Open-pit mining is one of the surface mining technique extracting minerals from the surface. Vegetation is rarely distributed at the mining site because the topsoil is removed and the ore is mined directly from the surface. Therefore, it is effective to observe surface displacement at the mining site using Interferometric Synthetic Aperture Radar (InSAR) technology. InSAR coherence detects random surface change that measures the activity or stability of the interferometric phase of InSAR data. High coherence will be maintained on the surface where there is no movement and only surface scattering. On the other hand, the surface where there is a lot of movement and volumetric scattering has low coherence value. Therefore, using 12-days InSAR coherence images from Sentinel-1 satellites, for example, it is possible to analyze how active the open-pit mine is during the 12 days. Sentinel-1A satellite images were acquired from June 11, 2015 to May 24, 2016, followed by Sentine-1B satellite images from September 27, 2016 to April 21, 2019. A total of 102 SAR images were downloaded from European Space Agency (ESA) portal. There is a gap between May 24 and September 27, 2016 due to the transition of the data acquisition plan. Over 100 12-days coherence data were obtained by applying InSAR. Stable spots and target spots were selected through average and standard deviation of the entire coherence time series data. Coherence values include not only the mining activity but also the effects of perpendicular baseline, temporal baseline, and weather. Therefore, NDAI (Normalized Difference Activity Index) was newly defined to remove the noise and only the coherence value due to the influence of the mining activity was extracted. The degree of activities can be observed by the time series coherence and NDAI images. This study needs other references related to mining activities in order to analyze the mining activities in more detail. This method can be applied to other open-pit mine.

How to cite: Moon, J., Seo, H., and Lee, H.: Activities of Musan Mine observed by Sentinel-1 Coherence Imagery, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12625, https://doi.org/10.5194/egusphere-egu2020-12625, 2020.

Measurements of surface displacement have been used in order to learn about seismic cycles, volcanoes, and other tectonic and non-tectonic processes. Ideally, the requirements to obtain useful measurements associated with seismic cycles are related to having a good spatial and temporal resolution, as surface deformation can occur in expected and unexpected faults, and in time intervals which vary from seconds (e.g. earthquake) to hundreds of years or even more (interseismic deformation).

Nowadays, satellite imagery provided by Synthetic Aperture Radar (SAR) or optical satellites fulfills those two aspects. Satellite images can cover large areas so that the fault rupture can be partially or totally visible. The problem of the radar technique is that for large earthquakes with surface rupture it cannot provide displacement maps in the near-field of the fault due to the large displacement gradient which causes phase decorrelation. Moreover, it is less sensitive to the horizontal displacement than vertical displacement. On the other hand, the main advantage of radar observing technique over the optical one is that the waves, emitted from a pulse-generating device, propagate through the atmosphere with almost no signal loss. This means that radar techniques operate under all weather conditions. Additionally, radar sensors are active, providing their own energy source, while optical are passive sensors that depend on external energy sources. Considering the benefits and the drawbacks of both sensing techniques, the opportunity of combining them helps the determination of a three-dimensional displacement field, illustrating a complete map of a seismic event.

In consequence, the objective of this study is to provide a methodology, using radar (Sentinel-1) and optical (Sentinel-2) data, that leads to the determination of the three-dimensional displacement field associated with the 7^th of July 2019, M_w 7.1 Ridgecrest earthquake. The interferometric and offset tracking processing were computed using SNAP and GAMMA software, respectively, and for ascending and descending tracks products. For the optical data, cross-correlation using MicMac software was applied so that the displacement in the same area of interest was also derived. After obtaining the displacement for radar and optical data independently, a Least Square Adjustment (LSA) allowed to properly combine them considering the associated weight of each observation and finally compute the three-dimensional decomposition. Finally, it was possible to have a fully covered ground displacement measured from radar and optical sensors, and to better analyze the behavior of the tectonics in the area of study.

How to cite: Canizares, C., Motagh, M., and Haghshenas Haghighi, M.: Resolving 3D coseismic deformation of the 2019 Mw 7.1 Ridgecrest earthquake using radar and optical data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13659, https://doi.org/10.5194/egusphere-egu2020-13659, 2020.

Human activity, in particular mining operations are the cause of terrain changes, manifesting on the terrain surface in form of subsidence troughs. Presence of subsidence troughs in inhabited areas may be the cause of significant damage to the structure of buildings, roads and other man-made objects. Both vertical and horizontal terrain displacements occuring inside the trough could be the reason for deterioration of mentioned objects. Hence the need to measure the impact of mining activity on the terrain surface. Current measurement techniques used to determine terrain displacements include GNSS, leveling and SAR interferometry. One of the limitations of interferometric measurements is that displacement values are in the satellites Line-of-Sight (LOS). The fact that the values are only quasi-vertical causes an ambiguity when it comes to determining whether the dominating component of displacement is vertical or horizontal. Projecting the one-dimentional LOS motion to the vertical direction using only the incidence angle can cause significant errors if the magnitude of horizontal motion is considerable. However, the specific 3-dimentional diplacement components can be derived using different acquisition geometries. In order to determine all 3 components (horizontal North-South, East-West and vertical Up-Down), 3 different viewing geometries have to be used so that the equation can be solved. However, the North-South component can be neglected due to low sensitivity of Sentinel-1 SAR instrument to displacement in that direction. Following that, 2 different viewing geometries can be sufficient to derive the East-West and vertical components.

The aim of the study is to determine how mining activity affects the surface in terms of both horizontal and vertical displacements. Radar pairs from Sentinel-1 ascending and descending orbit were used to create interferograms, based on which LOS displacement fields were calculated. The North-South and East-West components of displacement were solved through the inversion of the linear equation system based on incidence angles, headings and LOS displacements of ascending and descending radar pairs.

The horizontal and vertical components were determined for differential interferograms obtained with the DInSAR method using Sentinel-1 imagery, as well as for time series displacement fields derived from the Small Baseline Subset (SBAS) approach over selected mining areas in Poland. The results have shown that data from ascending and descending orbits can be successfully merged in order to obtain both the horizontal (East-West) and vertical components of displacement over mining areas. Obtained values of displacements from both DInSAR and SBAS have confirmed that areas affected by mining activity are under the influence of changes in height, as well as shifts in horizontal direction. Thus it is important to take into consideration multiple acquisition geometries when it comes to studying deformations over mining areas.

How to cite: Głąbicki, D., Kopeć, A., Milczarek, W., Bugajska, N., and Owczarz, K.: Determination of vertical and horizontal displacements of mining areas using the DInSAR and SBAS methods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13856, https://doi.org/10.5194/egusphere-egu2020-13856, 2020.

InSAR become more and more popular technique for monitoring mining excavation influence on terrain surface. Nowadays, research on the accuracy of InSAR measurements focuses on impact of external factors on SAR signal and process of phase unwrapping. SAR interferogram include information about a displacement in wrapped form – modulo 2π. Demodulation of phase (phase unwrapping) enable to restore true phase values and then correct interpretation of acquired information. Poor quality of data (low coherency) and large surface deformations cause phase discontinuities that make unwrapping process difficult and may generate incorrect results. Underground mining excavation, especially shallow or inducing seismic activity, may lead to large and abrupt surface displacements. Majority of unwrapping algorithms assume that the difference between any two adjacent samples in the continuous phase signal should not exceed a value of π. However, this assumption may be incorrect for large and abrupt surface displacements and lead to errors in the phase unwrapping and then to determination of incorrect values of surface displacements. Studies were conducted for areas where both natural and mining-induced seismic shocks occurred. DInSAR technique was used to create interferograms. Phase unwrapping processes were performed using Statistical-Cost, Network-Flow Algorithm for Phase Unwrapping (SNAPHU) for conventional parameters, modified discontinuity parameters and taking into account theoretical shock models (Mogi model). Research allowed to determine the impact of abrupt, large displacements on the phase unwrapping process.

How to cite: Kopeć, A., Głąbicki, D., Milczarek, W., Bugajska, N., and Owczarz, K.: Phase unwrapping issue in DInSAR measurements in the aspect of surface displacements on the mining areas , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13861, https://doi.org/10.5194/egusphere-egu2020-13861, 2020.

Satellite radar interferometry, in particular time series techniques, allow to monitor the activity of the surface of vast areas, making them a complement and alternative to traditional geodetic methods, the use of which in such areas is often associated with significant restrictions. The above-mentioned areas definitely include open-cast mines, among others the analyzed Bełchatów Brown Coal Mine (Poland).
During the studies, 216 satellite images acquired from the Sentinel-1A and Sentinel-1B satellites (path 175) for the period from October 17, 2014 to June 11, 2019 were used. Due to the fact that the research area was on two adjacent stages, it was necessary to combine data for the correct performance of the calculation process. The use of the SBInSAR imaging processing algorithm allowed to generate 839 interferograms carrying information about the difference in interferometric phases between pairs of images which satisfy the condition of the boundary size of the spatial and temporal base. As a consequence, it allowed to determine the displacements in the direction of the electromagnetic beam LOS (Line of Sight) that occurred in the mining area during this period.
Based on the carried out calculations, significant activity of the area around the open-pit mine was perceived. Dumping ground were analyzed - external Szczerców Fields and internal Bełchatów Fields, as well as excavations where mineral extraction is currently taking place. Continuous deformations (depressions and uplifts) associated with intensively conducted mining exploitation and complicated geological and mining conditions occurring in this area were observed (arrangement of rock layers, faults, the Dębina salt debris separating the Bełchatów Field from the Szczerców Field).

How to cite: Bugajska, N., Milczarek, W., Kopeć, A., and Głąbicki, D.: Long-term Changes in the Surface Area in the Surroundings of the Open-cast Brown Coal Mine in Bełchatów (Poland), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13862, https://doi.org/10.5194/egusphere-egu2020-13862, 2020.

The eastern Central Andes of northwestern Argentina is characterized by a steep topographic gradient with elevations ranging from 1000m in the foreland to more than 6000m in the eastern Andean Cordillera. This setting furthermore shows high topographic relief with deeply incised river valleys that are frequently impacted by strong rainfall events driven by the South American monsoon. Additionally, a strong vegetation cover contrast from dense coverage in the low elevation foreland to sparse coverage at high elevation defines the environmental gradient in this area. This area is impacted by several types of hillslope instabilities and landsliding: at some high elevations above 5000m hillslope instability are related to solifluction processes, whereas shallow and deep seated landsliding affect geologically preconditioned areas.

Here we use a combination of different radar sensors and wavelengths to describe the 3D deformation signal of instable hillslopes: TerraSAR-X, Sentinel-1, and ALOS2. To mitigate the tropospheric delay from InSAR measurements, phase-based and weather model approaches are applied to improve the spatial and temporal variations of displacement signals.  We use persistent and small baseline subsets (SBAS) category of distributed scatterer approaches to derive deformation fields and we invert for 3D deformation fields using several look angles in combination with GNSS data under different assumptions including that the horizontal component has a motion parallel to the downhill slope. We analyze Line-of-sight (LOS) time series and combine deformation fields with temperature and rainfall measurements to better understand driving forces of high-elevation hillslope instabilities We describe two deep-seated landslides with downslope velocities exceeding 5-10 cm/yr and we exploit image-cross correlation techniques of optical data to monitor seasonal and inter-annual changes. The periodic changes of InSAR deformation and temperature time series show freeze-thaw processes of the active layer thickness of the permafrost areas at elevations exceeding 5000m. We document that deep-seated, fast moving landslides are related to geologic preconditioning. The combination of SAR and optical approaches helps to describe hillslope regimes in steep and difficult to access terrain.

How to cite: M.Aref, M., Bookhagen, B., T. Smith, T., and R. Strecker, M.: Seasonal active landsliding and hillslope activity in the southern Central Andes of NW Argentina, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19679, https://doi.org/10.5194/egusphere-egu2020-19679, 2020.

Sanjiangyuan, as the Chinese ‘water tank’, is located in Qinghai province, China. It is the fountainhead of yellow river, Yangzi river and Lancang river. Therefore, it’s extraordinary valuable to the environment of China and Asia. The continuous permafrost spreads widely in this area. With the global warming process, the degradation of permafrost becomes faster and consequently changes the distribution of vegetation and hydrological cycle.

In this study, we use Persistent Scatterer InSAR (PSI) technique to efficiently detect the seasonal settlement around Elin lake and Zhaling lake, which are the main parts of Sanjiangyuan region. The subsidence was analyzed by processing 56 Sentinel-1 SAR images from 2015 to 2019 using SNAP and StaMPS. The results were then inverted to derive the corresponding active layer thickness over this region. Moreover, in order to investigate the detailed influence of degradation on infrastructures, we analyzed 3m resolution TerraSAR-X images in StripMap mode from May to October 2015 to get the heterogeneous subsidence along the Gonghe-Yushu road. Results indicate mean subsidence rates exceeding 4 cm/yr along the Gonghe-Yushu road .

How to cite: Ma, D., Motagh, M., and Liu, G.: Permafrost degradation monitoring by InSAR at different spatial resolution in Sanjiangyuan region, China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20173, https://doi.org/10.5194/egusphere-egu2020-20173, 2020.

In recent years, massive landslides and the related secondary hazards such as the dammed lakes occurred in the mountainous areas of southwestern China, e.g., the Wenchuan earthquake-triggered landslide dammed lake at Tangjiashan in 2008 and the Jinsha River Baige landslide in October and November 2018 near the junction of Sichuan and Tibet Province, has attracted wide attention of the geoscience community. Geologists and disaster scientists have recognized the important role of remote sensing technology in the early detection and deformation monitoring of geohazards. Some leading countries, such as Italy and Norway, have completed nationwide InSAR monitoring projects and the results have been well applied in the field of geohazards prevention and monitoring.
We applied InSAR technology in the detection and deformation monitoring of geological hazards in the Jinsha River, mainly including 1) General survey: the mean deformation rate from InSAR stacking with atmospheric corrections conducted for a wide-range area would be helpful to narrow down the area of detailed investigation, as well as to initially establish a geological hazard inventory. 2) Detailed investigation: For potential geohazards delineated in the general survey, or the areas require special attention, multi-temporal, multi-band and high-resolution InSAR should be utilized. The exhaustive deformation time series and the retrospect results provide information for geologists to carry out risk assessments. 3) Field monitoring: For the key areas, or in the rapid response for hazards, ground-based radar equipment can be used to carry out monitoring work to quickly obtain deformation over a relatively large area of interest in a short period of time.
In this work, we will provide general survey results of landslides on the scale of hundreds of kilometres along the Jinsha River, as well as detailed results of InSAR time series analysis of Baige Landslide, Woda Landslide, and some other potential landslide failures with rapid moving trends. The deformation monitoring results of Baige landslide using ground-based radar after the first failure will also be included in this work. Finally, we will also list several challenges at this stage and the possible solutions.

How to cite: Xiao, R., Li, Y., Yu, C., Li, Z., and He, X.: Detection and deformation monitoring of landslides by InSAR: applications along Jinsha River, China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21040, https://doi.org/10.5194/egusphere-egu2020-21040, 2020.

Subsidence due to coal mining is an increasingly prominent concern in the management of the coalfields. Jharia coalfields, Jharkhand are the oldest and one of the largest coalfields in India. Due to poor management of the coal mines in the past, land subsidence due to coal fires has become a common phenomenon in Jharia. Throughout the year, several factors such as coal fires, seepage of rainwater into mines, and illegal settlements above the abandoned mines contribute to the mining-induced subsidence. Due to such varied causes, subsidence in mining areas is temporally and spatially irregular. Traditional techniques using GPS, leveling, and total station are tedious, time-consuming, and can measure subsidence only on a point basis.

From the past few years, Interferometric Synthetic Aperture Radar (InSAR) has become a powerful tool to calculate and monitor the land subsidence. Persistent Scatterer Interferometry (PSI) is an advanced time-series interferometry technique, which calculates temporal deformation rates at mm scale with the help of stable pixels in the dataset referred to as Persistent Scatterers. The study aims at the detection and estimation of land subsidence in Jharia coalfield, Jharkhand, India, using the Persistent Scatterer Interferometry (PSI) technique. We used 30 C Band Sentinel-1 SAR images acquired in TOPSAR mode for a period of two years from 2017 to 2019, captured in a descending direction. Data acquired during the dry season are preferred to ensure good coherence. Potential subsidence zones are identified and demarcated using the Differential Interferometry technique in SNAP. PSI analysis is carried out using the StaMPS method. High temporal decorrelation due to the surrounding agricultural land cover and atmospheric interference are significant challenges for the PSI analysis in mining areas. The temporal baseline is adapted accordingly to reduce de-correlation. Atmospheric interference is removed using the TRAIN toolbox using the GACOS correction model. The results show an average subsidence rate in Jharia coal mines of approximately 4 cm/yr. Among the 23 underground mines in Jharia, 6 mines are subsiding at the maximum rate of 12 cm/yr. We identified subsidence in several small coal mines in multiple locations surrounding settlements and agricultural areas that can lead to contamination of groundwater when collapsed. Kustore underground mine covering an area of 1.2 sq. km is the largest subsidence zone in the study area just 200 meters away from the settlements.

How to cite: Karanam, V. K. R., Motagh, M., and Jain, K.: Land Subsidence In Jharia Coalfields, Jharkhand, India – Detection, Estimation And Analysis Using Persistent Scatterer Interferometry, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21118, https://doi.org/10.5194/egusphere-egu2020-21118, 2020.

Groundwater induced land subsidence is a growing problem worldwide and has been documented in places like Mexico, Jakarta, Tehran, and China. India is the largest user of groundwater and pumps more than the USA and China combined. The National capital region(NCR) of India, due to rapid urbanization and illegal extraction, is facing severe groundwater depletion of the order of 0.5m-2m per year and is declared as a critical zone by the government of India. The looming crisis of groundwater depletion and supporting hydrogeology makes this region prone to land surface deformation.

Monitoring subsidence by conventional methods such as extensometers, leveling, hydrogeology modeling, and GPS requires precise field measurements and are time-consuming. With the advent of Interferometry, monitoring deformation precisely from the microwave sensors onboard satellite is possible. In our study, we demonstrate the result of the Persistent Scatterer InSAR (PS-InSAR) technique to monitor the subsidence in the Delhi NCR region using Sentinel -1 Interferometric wide swath (IW) mode. Descending pass datasets are used to identify the PSs over the study area. Fifty-six differential interferograms from Aug 2016 to Sep 2018 are formed after removing flat earth and topographic phase using SRTM 30m DEM. The PS-InSAR processing is done using Stanford Method for Persistent Scatterers (StaMPS), where an amplitude threshold index of 0.4 is selected for Initial PS candidate. The PS points are the stable targets which do not decorrelate much over time.  The deformation is calculated for all these PS points and a time series, and hence a velocity map is formed.

The rate of deformation in Southwest Delhi is found to be approximately 15 cm/year (max) in the radar line of sight direction. The in-situ data provided by the Central groundwater board (CGWB) India is not consistent and has many gaps. However, after applying Spatio-temporal interpolation, it follows the decreasing trend of Land subsidence which suggests that the groundwater extraction is the major cause for the subsidence in the southwest region of NCR during the observed period i.e., from 2016 -2018.

How to cite: Garg, S., Motagh, M., and Jayaluxmi, I.: Land Subsidence in Delhi, India investigated using Sentinel-1 InSAR measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21138, https://doi.org/10.5194/egusphere-egu2020-21138, 2020.

Man-made reservoirs and lakes are key elements in the terrestrial water system. The increased concern about the impact of anthropogenic interventions on and the dynamics of these water resources has given rise to various approaches for representing human-water interactions in land surface models. Synthetic aperture radar interferometry (InSAR) has become a powerful geodetic tool for this purpose, by evidencing changes of ground and water surfaces across time and space. In this research, the Lake Mead and associated Hoover Dam are studied using Small Baseline Subset (SBAS) technique. Lake Mead is the largest reservoir in the United States, in terms of water capacity, supplies water and hydropower for millions of people in Las Vegas, Los Angeles and southwestern part of the USA. In recent years, rising temperature, increasing evaporation and decreasing precipitation have decreased water levels substantially, and probably modified its surrounding groundwater and surface as well.

This study aims to identify a hydrology-induced ground deformation around the lake Mead and a probable Hoover dam movement displacement. For the reservoir, we used the SBAS technique using 138 SAR data, including ERS1/2, Envisat, ALOS PALSAR and Sentinel-1, covering a time-spam between 1995 and 2019. For the analysis on the dam, we used the SBAS technique from 2014 to 2019 with descending and ascending modes of Sentinel-1A/B imageries. We found two main deformation patterns around the lake associated with the water level changes. Firstly, ERS and Sentinel-1 data evidenced a ground deformation that manifested itself as as a subsidence pattern in 1995 that has gradually changed into an uplift up to 2019. Secondly, the correlation trend between the deformation and water level changes has changed from negative to positive, with a transition point around March 2008. A possible interpretation for this is that the ground has initially reacted to the water fluctuations in the reservoir before March 2008 but after no longer plays a dominant role in the deformation occurring around the lake. The findings will help us to have a better understanding over the changes happened around the lake due to the water level changes and provide the valuable information for more effective management and maintenance of hydraulic structures and facilities near by the lake and water control in the future.

How to cite: Darvishi, M., Destouni, G., and Jaramillo, F.: Lake Mead and Hoover Dam monitoring in Nevada and Arizona states, USA using InSAR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21582, https://doi.org/10.5194/egusphere-egu2020-21582, 2020.

Coal is the largest energy source for China, and over 90% coal production in China is from underground mining. However, underground mining usually trigger large-scale ground deformations, which tend to develop as hazards. Therefore, the central government of China issued the “green mine” policy in 2017, which requires to strictly implement scientific and orderly exploitation and keeping the disturbance to the mining area and surrounding environment within the limits of sustainable development in the whole process of coal mining. This policy necessitates accurate monitoring of ground deformations induced by underground mining. Satellite Interferometric SAR (InSAR), especially the multi-temporal InSAR techniques have been successfully used to monitor deformations associated with underground mining. But temporal decorrelation still remains a big challenge because many underground mining takes place beneath farmland or forested region. Given the advantages of Sentinel-1 (S-1) in short revisit time, small baselines and free accessibility, underground mining deformations can be monitored somehow with S-1 InSAR in vegetated areas. In this research we report such an application in an underground coal-mine site located in Xuzhou, Jiangsu province of China. Four working panels are investigated

The working panels are all beneath farmland where winter wheat is sowed before the end of October and reaped around next late May, then corn or rice is planted during the coming summer season from June to September. Therefore the C-band S-1 interferograms can keep good coherence only when both images are acquired in the period of late October to next early April (this period is called coherent period thereafter) when the newly planted winter wheat is in its early growing stage. Three subsets of S-1 images acquired during three consecutive coherent periods  are used to generate mining-induced ground deformations.

During each coherent period, all of the interferograms with 12-day separation and some of the interferograms with 24-day separation and good coherence are selected and phase-unwrapped. Then these two sets of unwrapped interferograms are stacked, and finally the temporal deformations along SAR line-of-sight (LOS) are calculated under the least square principle. The temporal and spatial characteristics of the LOS deformation time series (DTS) are analyzed by considering extraction stage and extraction parameters of the working panel. Based on the analysis, we can diagnose whether the underground exploitation overstepped its designed boundary, or whether the working panel has been exploited for longer time than the designed extraction period.

How to cite: Zhang, Y., Wu, H., Luo, Y., Kang, Y., and Fan, H.: Ground deformations associated with underground coal-mining observed by Sentinel-1 SAR images in vegetated area, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22428, https://doi.org/10.5194/egusphere-egu2020-22428, 2020.