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NH6.5

EDI
Interferometric Synthetic Aperture Radar added value products for Natural & Anthropogenic hazard assessment at local, regional and national scale.

Synthetic aperture radar (SAR) remote sensing is an established tool for natural and anthropogenic hazards mapping and monitoring. The new generation of radar satellite constellations along with a consistent repository of historical observations is fostering comprehensive multi-sensor hazard analyses. New constellations’ capabilities rely on innovative techniques based on high-resolution/wide-swath and short-temporal Interferometric SAR (InSAR). While acknowledging the benefits brought by these recent developments, the scientific community is now defining a new paradigm of techniques capable of: extracting relevant information from SAR imagery, designing proper methodologies for specific hazards, managing large SAR datasets (e.g. National ground motion services, Copernicus EGMS), and integrating radar data with multispectral satellite observations.

Co-organized by ESSI4/GI3
Convener: Alessandro Novellino | Co-conveners: Roberta BonìECSECS, Marta Béjar-Pizarro, Pietro Milillo
Presentations
| Thu, 26 May, 08:30–11:50 (CEST)
 
Room 1.31/32, Thu, 26 May, 17:00–18:30 (CEST)
 
Room E2

Thu, 26 May, 08:30–10:00

Chairpersons: Pietro Milillo, Marta Béjar-Pizarro

08:30–08:35
block #1 (8,30-10) introduction

08:35–08:45
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EGU22-6544
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solicited
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Highlight
Cathleen Jones et al.

NASA’s NISAR mission, expected to launch in early 2023, will provide SAR observations of nearly all Earth’s land surfaces and selected ocean and sea ice areas on both ascending and descending orbits at a 12-day orbit repeat interval.  In this talk, mission plans to support both sustained and event-driven observations for hazard assessment are presented.  The NISAR satellite will carry both L- and S-band instruments, with the L-band instrument providing the near-global coverage and the S-band acquisitions concentrated in southern Asia and the polar regions.  In addition, the mission system will be capable of accepting and implementing requests for rapid processing to support disaster response.  Most land observations are part of the standard observation plan, so requested scenes will be marked for rapid processing and delivery, with the goal of providing information within hours of acquisition.  In the event that new acquisitions are needed, e.g., over the ocean as major tropical storms develop, the instrument can be retasked to acquire new scenes.

In addition, we present information about efforts on the part of the mission to enable realistic simulation of NISAR’s capabilities across a broad range of science and applications topics.  To that end, L-band quad-polarimetric and repeat pass SAR data acquired with the airborne UAVSAR instrument, which has ~3-m single look resolution, has been processed to be ‘NISAR-like,’ with the noise level and spatial resolution of NISAR’s planned acquisition modes.  To date, more than 400 NISAR-like products from 70 different UAVSAR scenes acquired in North America and Greenland have been produced, and the UAVSAR project is continuing to generate more products specifically to support hazard assessment for fires and landslides.  Examples of anticipated NISAR performance will be shown with comparison to results using the full resolution UAVSAR products. 

This work was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA.

How to cite: Jones, C., An, K., and Staniewicz, S.: Hazard assessment with SAR – What to expect from the NISAR mission, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6544, https://doi.org/10.5194/egusphere-egu22-6544, 2022.

08:45–08:52
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EGU22-12444
Riccardo Lanari et al.

The widespread availability of large SAR data volumes systematically acquired during the last 3 decades by several space-borne sensors, operating with different spatial resolutions, footprint extensions, revisit times and bandwidths (typically X-, C-, or L-band), has promoted the development of advanced Differential Interferometric SAR (DInSAR) techniques providing displacement time series relevant to wide areas with rather limited costs. These techniques allow us to carry out detailed analyses of the Earth surface deformation effects caused by various natural and anthropic phenomena and also to investigate the displacements affecting man-made structures. In particular, with reference to the latter issue, the increasing need to assess, preserve and mitigate the health conditions of buildings and infrastructures, due to the high vulnerability of the built-up environment, has fostered over the last decades an intense exploitation of the advanced DInSAR techniques. In this context, a new frontier for the development of these methodologies is related to their effective exploitation in operational contexts, requiring the use of up-to-date interferometric processing techniques and advanced HPC infrastructures to precisely and efficiently generate value-added information from the available, multi-temporal large SAR data stacks.

Among several advanced DInSAR algorithms, a widely used approach is the Small BAseline Subset (SBAS) technique which has largely demonstrated its effectiveness to retrieve deformations relevant to natural and anthropic hazard scenarios, through the generation of spatially dense mean velocity maps and displacement time series with millimetric accuracy, at different spatial resolution scales (both regional and local ones). Moreover, a parallel algorithmic solution for the SBAS approach, referred to as the parallel Small BAseline Subset (P-SBAS) technique, has been recently developed.

In this work, we present some new advances of the full resolution P-SBAS DInSAR processing chain that allow us to effectively retrieve, in reasonable time frames (less than 24 hours), the spatial and temporal patterns of the deformation signals associated to the built-up heritage. This is achieved through a dedicated implementation of the full resolution P-SBAS processing chain permitting to efficiently exploit HPC resources, also accessible through Cloud Computing environments. In particular, we make an extensive use of innovative hardware and software parallel solutions based on GPUs, which are able to efficiently store, retrieve and process huge amounts of full resolution DInSAR products, with high scalability performance.

To demonstrate the capability of the implemented solution we show the results of the massive full resolution P-SBAS processing relevant to several urban areas of the Italian territory. This is done by exploiting the overall, full frame SAR image stacks of ascending and descending X-band SAR data acquired by the sensors of the Italian COSMO-SkyMed (CSK) constellation, operated through the Stripmap mode (with about 3m x 3 m spatial resolution), and those of the C-band Sentinel-1 twin sensors of the Copernicus Programme, exploiting the Interferometric Wide Swath TOPS mode (with about 15 m x 4 m spatial resolution). Moreover, we also benefit from the availability of the first data acquired by the second generation COSMO-SkyMed constellation (CSG), which allows continuity with the CSK data in the monitoring of the detected deformation phenomena.

How to cite: Lanari, R., Bonano, M., Buonanno, S., Manunta, M., Striano, P., Yasir, M., and Zinno, I.: New advances of the P-SBAS algorithm for the efficient generation of full resolution DInSAR products through scalable HPC infrastructures , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12444, https://doi.org/10.5194/egusphere-egu22-12444, 2022.

08:52–08:59
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EGU22-8397
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ECS
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Virtual presentation
Yuankun Xu et al.

To date, mainstream SAR (Synthetic Aperture Radar) systems dominantly operate in X/C/L bands (wavelengths of 3.1–24.2 cm), which commonly experience low coherence and thereby degraded InSAR accuracy over densely vegetated terrains. The long wavelength (69.7 cm) P-band SAR, in contrast, holds the potential to address this challenge by penetrating through dense forests to collect highly coherent data takes. Here, we experimented using the NASA JPL (Jet Propulsion Laboratory)’s P-band AirMOSS (Airborne Microwave Observatory of Subcanopy and Subsurface) radar system to acquire repeat-pass SAR data over diverse terrains (14 flight segments) in Washington, Oregon, and California (USA), and comprehensively evaluated the performance of P-band InSAR for ground deformation surveying. Our results show that the AirMOSS P-band InSAR could retain coherence two times as high as the L-band satellite ALOS-2 (Advanced Land Observing Satellite-2) data, and was significantly more effective in discovering localized geohazards that were unseen by the ALOS-2 interferograms in forested areas. Additionally, P-band InSAR could better avoid phase aliasing to resolve high-gradient deformation. However, despite these advantages, P-band InSAR were less sensitive to subtle deformation than X/C/L band radars and faced similar challenges posed by waterbodies, thick snow covers, shadow and layover effects, and the side-looking configuration. Overall, our results suggest that P-band InSAR could be a revolutionary tool for measuring relatively high-gradient deformation under dense forest canopies.   

How to cite: Xu, Y., Lu, Z., and Kim, J.-W.: P-band SAR for deformation surveying: advantages and challenges, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8397, https://doi.org/10.5194/egusphere-egu22-8397, 2022.

08:59–09:06
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EGU22-5719
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On-site presentation
Carolina Guardiola-Albert et al.

The problem of predicting terrain deformation time series from radar interferometry (InSAR) data is one of the biggest current challenges for the prevention and mitigation of the impact of geological risks (e.g. earthquakes, volcanoes, subsidence, slope landslides) that affect both urban (e.g. building movement) and non-urban areas. Generating spatio-temporal alert systems on the processes of deformation of the terrain based on predictive models is one of the great current challenges in the face of the prevention and management of geological risks. Within machine learning techniques, deep learning offers the possibility of applying prediction models of deformation time series on images using convolutional neural networks (Ma et al., 2020).

The objective of the present study is to develop a methodology to obtain predictive models of time series of terrain deformation from InSAR images using machine learning algorithms (e.g. deep convolutional neural networks). Data to train the algorithm will be time series of terrain deformation contained in InSAR images processed by the Geological Survey of Spain (IGME-CSIC). Different architectures and parameterizations of machine learning will be tested.

This work is performed within the framework of the SARAI Project PID2020-116540RB-C22 funded by MCIN/ AEI /10.13039/501100011033.

Reference:

Ma, P., Zhang, F., Lin, H. (2020). Prediction of InSAR time-series deformation using deep convolutional neural networks. Remote Sensing Letters, 11:2, 137-145.

 

How to cite: Guardiola-Albert, C., Aguilera, H., Arias Patiño, J., Fullea Urchulutegui, J., Ezquerro, P., and Bru, G.: Ground deformation time series prediction based on machine learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5719, https://doi.org/10.5194/egusphere-egu22-5719, 2022.

09:06–09:13
block #1 Q&A

09:13–09:18
block #2 (8,30-10) introduction

09:18–09:25
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EGU22-11733
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Highlight
Tim Wright et al.

The European Commission’s Sentinel-1 constellation, operated by ESA, has been a game changer for operational monitoring of our hazardous planet. When fully operational, the Sentinel-1 mission is a two-satellite constellation; currently consisting of Sentinel-1A (launched in 2014) and Sentinel-1B (launched in 2016), the mission provides at least one SAR image for the whole land surface every 12 days, with both ascending and descending data acquired in tectonic/volcanic areas globally every 12 days, and images acquired in both geometries every 6 days over all of Europe. The narrow orbital tube, consistent imaging geometry, and long time series are optimised for ground deformation measurements with InSAR. Sentinel-1C and -1D have been built and will replace the existing satellites in due course. Perhaps the most important game changer has been the Copernicus data policy, which mandates fully free and open distribution of Sentinel-1 products for all applications, whether they are for research or commercial purposes. Sentinel-1 InSAR data has quickly become the primary data set for monitoring ground movement in our hazardous planet. Several research organisations/collaborations now process enormous quantities of Sentinel-1 data to produce deformation products that are made freely available through organisations like COMET in the UK, EPOS and the new European Ground Motion Service in Europe, and the Alaska SAR Facility in the US. Commercial providers are processing data at scales ranging from individual bridges/dams through to whole countries. In this presentation we will focus on Sentinel-1 results produced academically by COMET and commercially by SatSense Ltd. COMET now responds routinely to all continental earthquakes bigger than M5.5 and provides interactive tools and machine-learning-based alerting for global volcanoes. COMET is combining Sentinel-1 InSAR with GNSS to map tectonic strain at high spatial resolution on a continental scale, in areas including Anatolia, Tibet and Iran, and using the results to improve our understanding of seismic hazard. SatSense have demonstrated the value of Sentinel-1 InSAR for applications including dam monitoring, water pipe failures and railway infrastructure. The SatSense processing approach allows InSAR ground movement data to be kept continuously up to date for entire countries. We conclude the presentation by discussing prospects for the future of InSAR beyond Sentinel-1.

How to cite: Wright, T., Hooper, A., Lazecky, M., Maghsoudi, Y., Spaans, K., and Ingleby, T.: Operational monitoring of our hazardous planet with Sentinel-1, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11733, https://doi.org/10.5194/egusphere-egu22-11733, 2022.

09:25–09:32
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EGU22-9733
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Virtual presentation
Mario Costantini et al.

Satellite interferometric SAR (InSAR) has demonstrated to be a powerful technology to perform millimeter-scale precision measurements of ground motions. The European Ground Motion Service (EGMS), funded by the European Commission as an essential element of the Copernicus Land Monitoring Service (CLMS), constitutes the first application of the InSAR technology to high-resolution monitoring of ground deformations over an entire continent, based on full-resolution processing of all Sentinel-1 (S1) satellite acquisitions over most of Europe (Copernicus Participating States).

Upscaling from existing national precursor services to pan-European scale is challenging. EGMS employs the most advanced persistent scatterer (PS) and distributed scatterer (DS) InSAR processing algorithms, and adequate techniques to ensure seamless harmonization between the Sentinel-1 tracks. Moreover, within EGMS, a Global Navigation Satellite System (GNSS) high-quality 50 km grid model is realized, in order to tie the InSAR products to the geodetic reference frame ETRF2014.

The millimeter-scale precision measurements of ground motions provided by EGMS will enable mapping and monitoring of landslides, subsidence and earthquake or volcanic phenomena all over Europe, and the stability of slopes, mining areas, buildings and infrastructures. The first release of EGMS products will be in March 2022, with annual updates to follow.

To foster as wide usage as possible, EGMS foresees tools for visualization, exploration, analysis and download of the ground deformation products, as well as elements to promote best practice applications and user uptake.

The new European geospatial dataset provided by EGMS will hopefully also stimulate the development of value-added products/services for the analysis and monitoring of ground motions and stability of structures based on InSAR measurements, as well as other InSAR products with higher spatial and/or temporal resolution.

This work will describe all the qualifying points of EGMS. Particular attention will be paid to the characteristics and the accuracy of the realized products, ensured in such a huge production by advanced algorithms and quality checks.

In addition, many examples of EGMS products will be shown to discuss the great potential and the (few) limitations of EGMS for mapping and monitoring landslides, subsidence and earthquake or volcanic phenomena, and the related stability of slopes, buildings and infrastructures.

How to cite: Costantini, M., Minati, F., Trillo, F., Ferretti, A., Passera, E., Rucci, A., Dehls, J., Larsen, Y., Marinkovic, P., Eineder, M., Brcic, R., Siegmund, R., Kotzerke, P., Kenyeres, A., Proietti, S., Solari, L., and Andersen, H.: EGMS: a New Copernicus Service for Ground Motion Mapping and Monitoring, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9733, https://doi.org/10.5194/egusphere-egu22-9733, 2022.

09:32–09:39
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EGU22-6040
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Highlight
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Virtual presentation
Lorenzo Solari et al.

Satellite interferometry (InSAR) is a reliable and proven technique to monitor and map geohazards over wide areas. In the last years, InSAR is increasingly becoming an everyday tool for geoscientific and applicative analyses; many different users, ranging from academia to the industry, work and rely on InSAR products.

The European Ground Motion Service (EGMS) was conceived and is being implemented as a direct response to growing user needs. The EGMS is implemented under the responsibility of the European Environment Agency in the frame of the Copernicus Programme. The EGMS products are part of the portfolio of the Copernicus Land Monitoring Service. The EGMS provides consistent, regular, standardized, harmonized, and reliable information regarding natural and anthropogenic ground motion phenomena over the Copernicus Participating States and across national borders, with millimeter accuracy. The EGMS distributes three levels of products: (i) basic, i.e. line of sight (LOS) velocity maps in ascending and descending orbits referred to a local reference point; (ii) calibrated, i.e. LOS velocity maps calibrated with a geodetic reference network (a velocity model derived from thousands of global navigation satellite systems time series is used for calibration so that measurements are no longer relative to a local reference point) and (iii) ortho, i.e. components of motion (horizontal and vertical) anchored to the reference geodetic network. The products are generated from the multi-temporal interferometric analysis of Sentinel-1 images in ascending and descending orbit at full resolution.  The data is available and accessible to all and free of charge through a dedicated viewer and download interface.

The accessibility to EGMS accurate and validated interferometric data offers the geoscientific and professional communities the opportunity to study geohazards at the European level, including difficult-to-reach areas or where the availability of ground motion data has so far been scarce or null. The EGMS provides, for example, information useful for the identification and monitoring of slow-moving landslides, natural subsidence, or subsidence due to groundwater exploitation or underground mining activities and volcanic unrest. In addition, the Service establishes a baseline for studies dedicated to localized deformation affecting buildings and infrastructure in general. This presentation will offer a first evaluation of the EGMS products under geoscientific aspects. Case studies from different European environmental contexts will be shown to demonstrate how the EGMS products can be successfully used for geohazards-related studies.

How to cite: Solari, L., Crosetto, M., Balasis-Levinsen, J., Bateson, L., Casagli, N., Comerci, V., Guerrieri, L., Frei, M., Mróz, M., Moldestad, D. A., Oyen, A., and Andersen, H. S.: A first appraisal of the European Ground Motion Service, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6040, https://doi.org/10.5194/egusphere-egu22-6040, 2022.

09:39–09:46
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EGU22-9443
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ECS
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On-site presentation
Balint Magyar and Roland Horvath

One of the main objectives of the GeoSES* project to investigate dangerous natural and anthropogenic geo-processes and aim hazard assessment using space geodetic technologies and concentrating on the Hungary-Slovakia-Romania-Ukraine cross-border region. The monitoring of such natural hazards and emergency situations (e.g. landslides and sinkholes ) are also additional objectives of the project. In the framework of the presented project, our study utilizes one of the fastest developing space-borne remote sensing technology, namely InSAR, which is an outstanding tool to conduct large scale ground deformation observation and monitoring. According this, we utilized ascending and descending Sentinel-1 Level-1 SLC acquisitions since 2014 until 2021 over the indicated cross-border area, focusing the Transcarpathian Region.

We also present an automated processing chain of Sentinel-1 interferometric wide mode acquisitions to generate long-term ground deformation time-series. The pre-processing part of the workflow includes the migration of the input data from the Alaska Satellite Facility (ASF), the integration of precise orbits from S1QC, as well as the corresponding radiometric calibration and mosaicing of the TOPS mode data, furtheromore the geocoding of the geometrical reference. Subsequently all slave acquisition have be co-registered to the geometrical reference using iterative intensity matching and spectral diversity methods, then subsequent deramping has been also performed. To retrieve deformation time series from co-registered SLCs stacks, we have implemented multi-reference Interferometric Point Target Analysis (IPTA) using singe-look and multi-look phases using the GAMMA Software. After forming differential interferometric point stacks, we conducted the iterative IPTA processing. According this both topographical and orbit-related phase component, as well as the atmospheric phase, height-dependent atmospheric phase and linear phase term supplemented with the deformation phase are modeled and refined through iterative steps. To retrieve recent deformations of the investigated area, SVD LSQ optimization has been utilized to transform the multi-reference stack to single-reference phase time-series such could be converted to LOS displacements within the processing chain. Involving both ascending and descending LOS solutions also supports the evaluation of quasi East-West and Up-Down components of the surface deformations. Results are interpreted both in regional scale and through local examples of the introduced cross-border region as well.

* Hungary-Slovakia-Romania-Ukraine (HU-SK-RO-UA) ENI Cross-border Cooperation Programme (2014-2020) “GeoSES” - Extension of the operational "Space Emergency System"

How to cite: Magyar, B. and Horvath, R.: Regional scale monitoring results of surface deformation in the Transcarpathian Region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9443, https://doi.org/10.5194/egusphere-egu22-9443, 2022.

09:46–09:58
block #2 Q&A

Thu, 26 May, 10:20–11:50

Chairpersons: Roberta Bonì, Marta Béjar-Pizarro, Pietro Milillo

10:20–10:25
block #3 (10,20-11,50), introduction

10:25–10:32
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EGU22-5293
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On-site presentation
Faramarz Nilfouroushan et al.

The interest for using Interferometric Synthetic Aperture Radar (InSAR) for ground motion detection and monitoring is rapidly increasing, thanks to the Copernicus Senetinel-1 satellites which cover relatively large areas with a 6-days revisit time. Ground motion of many locations, especially urban areas around the world have been studied using Sentienl-1 data and the rate and distribution of the ground movements have been reported. For Sweden, for example, Fryksten and Nilfouroushan (2019) and Gido et al. (2020) studied the active ground subsidence in Uppsala and Gävle cities using the Senetinel-1 data collected between 2015-2020. The Persistent Scatterer Interferometry (PSI) technique was used to estimate the subsidence rate and the results were validated with the help of precise levelling data and correlated with the geological observations. Today, fortunately, we have the nationwide GMS of Sweden (https://insar.rymdstyrelsen.se) covering almost the entire country, which provides an opportunity to compare and cross-check the results of this new service with previous studies, for example the ones reported for Uppsala and Gävle cities. The temporal coverage of satellite data used for the GMS of Sweden has an overlap with the data used in previous studies for Uppsala and Gävle cities, and the same PSI technique has been used to generate the displacement map and time series.

In this study, we used the previous PSI results of Uppsala and Gävle cities to validate the newly launched nationwide GMS of Sweden. The Line Of Sight (LOS) displacement time-series at some deforming locations  were compared for both PSI-results. Although the number and imaging date of Senetinel-1 data, and the parameters used for PSI processing are not completely the same, the compared results show a good agreement between corresponding studies on the localization and rate of the subsidence in those two cities in last  ~5 years. The validation phase of the new GMS of Sweden is in progress and our study shows the promising results, at least for urban areas in those two cities.  

References

Fryksten J., Nilfouroushan F., Analysis of Clay-Induced Land Subsidence in Uppsala City Using Sentinel-1 SAR Data and Precise Leveling. Remote Sens. 2019, 11, 2764. https://doi.org/10.3390/rs11232764

Gido N.A.A., Bagherbandi M., Nilfouroushan F., Localized Subsidence Zones in Gävle City Detected by Sentinel-1 PSI and Leveling Data. Remote Sens. 2020, 12, 2629. https://doi.org/10.3390/rs12162629

How to cite: Nilfouroushan, F., Gido, N. A. A., and Darvishi, M.: Cross-checking of the nationwide Ground Motion Service (GMS) of Sweden with the previous InSAR-based results: Case studies of Uppsala and Gävle Cities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5293, https://doi.org/10.5194/egusphere-egu22-5293, 2022.

10:32–10:39
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EGU22-2842
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ECS
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Virtual presentation
Alessandro Zuccarini et al.

Since the beginning of the 1960s, the urban area of Bologna has experienced land subsidence due to excessive groundwater withdrawals. Sinking reached its peak in the 70s of the last century when the subsidence rate attained the maximum value of about 10 cm/year, and significant damages to structures and infrastructures occurred. This process has been intensively monitored over the years, and extensive ground displacement data were collected employing various increasingly sophisticated techniques, ranging from topographic levelling to GNSS surveys and, since 1992, to satellite interferometry. Satellite data, in particular, allowed an accurate reconstruction of the land subsidence process. The available interferometric data are the results of three different SAR campaigns undertaken by local authorities in which the PSInSAR technique was adopted: 1992 – 2000 (ERS), 2002 – 2006 (ENVISAT) and 2006 – 2011 (RADARSAT). Within this work, a new InSAR survey from the free SENTINEL1 2014 – 2020 ascending and descending orbits data was undertaken by the UniBo spin-off “Fragile”. The software GMTSAR was used to process each interferogram and then a Small Baseline (SBAS) approach was followed to resolve the ground displacements over time. Great attention was paid to the choice of reference pixels on the existing buildings and structures, in order to maximise their density in the study area, and to the definition of the considered time span ranging from 6 to 365 days, allowing to analyse both quicker and slower ground movements. Compared to previous surveys, the displacement map obtained by Sentinel has a much higher spatial and temporal resolution, thus leading to a detailed interpretation of the ongoing subsidence. Results show that the displacement field well agrees with the 3D geological model of the area and that the temporal evolution of the subsidence rate nicely matches the piezometric level and groundwater pumping temporal series.

How to cite: Zuccarini, A., Bayer, B., Franceschini, S., Giacomelli, S., Di Paola, G., and Berti, M.: Exploiting Sentinel-1 InSAR capabilities for studying the land subsidence process in an urban area , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2842, https://doi.org/10.5194/egusphere-egu22-2842, 2022.

10:39–10:46
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EGU22-12646
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ECS
Shagun Garg et al.

Risk assessment and zoning are very important to risk management as it indicates how severe the hazard can be, and who would be most affected. It plays a crucial role in risk management, especially for densely populated areas. 

Delhi- the capital of India, is the fifth most populous city in the world, with a population density of nearly 30,000 people per square mile. Like other global megacities, Delhi is also facing a looming water crisis due to urbanization and rapid population expansion. The increasing demand for water has translated into the extraction of larger quantities of groundwater in the region. One of the many consequences of groundwater over-extraction is land subsidence. Amongst all other ways to monitor land subsidence, Interferometric Synthetic Aperture Radar (InSAR) is considered to be the most effective and widely used technique.  We used the InSAR technique and analyzed Sentinel-1 data acquired during 2014 - 2020 and identified some localized subsidence zones in the region. In addition to that,  a risk assessment was also performed by considering hazards and vulnerability approach.

In this study, a land subsidence risk assessment index was proposed based on the Disaster Risk Index. The cumulative subsidence volume, the land subsidence velocity, subsidence gradient, and the groundwater exploitation intensity were collected, analyzed, and put together to create a land subsidence hazard evaluation map in the National capital region India. The population density, land cover, and population estimates were adopted as indexes to create the vulnerability map. Finally, the land subsidence risk map was created by combining the hazard and vulnerability maps using the matrix multiplication approach. Specifically, the final risk map was classified into three levels, i.e., high, medium, and low. The analysis highlights an approximate area of 100 square kilometers to be subjected to the highest risk level of land subsidence, demanding urgent attention. The findings of this study are highly relevant for government agencies to formulate new policies against the over-exploitation of groundwater and to facilitate a sustainable and resilient groundwater management system in Delhi NCR.

How to cite: Garg, S., Motagh, M., Jayaluxmi, I., Karanam, V., Selvakumaran, S., and Marinoni, A.: Assessment of Land Subsidence Hazard, Vulnerability and Risk: A case study for National Capital Region in India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12646, https://doi.org/10.5194/egusphere-egu22-12646, 2022.

10:46–10:56
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EGU22-1467
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solicited
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Virtual presentation
Francesca Cigna and Deodato Tapete

The use of satellite Interferometric Synthetic Aperture Radar (InSAR) for land subsidence assessment is already a well established scientific research approach. Although several studies analyze subsidence patterns via integration of InSAR output maps with geospatial layers depicting hazard factors or elements at risk (e.g. surface and bedrock geology, cadastral and infrastructure maps), still limited is the body of literature attempting to generate value-added products. These not only have the potential to be used by stakeholders in urban planning, but also can be updated as new InSAR data are made available. With this scope in mind, this work presents the experience gained across Central Mexico, where land subsidence due to groundwater resource overexploitation is a pressing issue affecting many urban centers and expanding metropolises. Groundwater availability and aquifer storage changes provided by the National Water Commission are analyzed in relation to surface deformation data from wide-area surveys based on InSAR. The Parallel Small BAseline Subset (P-SBAS) method integrated in ESA’s Geohazards Exploitation Platform (GEP) is used to process Sentinel-1 IW big data stacks over a region of 550,000 km2 encompassing the whole Trans-Mexican Volcanic Belt (TMVB) and several major states, including Puebla, Federal District, México, Hidalgo, Querétaro, Guanajuato, Michoacán, Jalisco, San Luis Potosí, Aguascalientes and Zacatecas. A number of hotspots affected by present-day subsidence rates of several cm/year are identified across the TMVB, with extents ranging from localized bowls up to whole valleys or metropolitan areas spanning hundreds of square kilometers. Surface faulting hazard and induced risk on urban properties are assessed and discussed with a focus on: (i) Mexico City metropolitan area, one of the most populated and fastest sinking cities globally (up to −40 cm/year vertical, and ±5 cm/year E-W rates) [1]; (ii) the state of Aguascalientes, where a structurally-controlled fast subsidence process (−12 cm/year vertical, ±3 cm/year E-W) affects the namesake valley and capital city [2]; and (iii) the Metropolitan Area of Morelia, a rapidly expanding metropolis where population doubled over the last 30 years and a subsidence-creep-fault process has been identified (−9 cm/year vertical, ±1.7 cm/year E-W) [3]. InSAR results and the derived risk maps prove valuable not only to constrain the land deformation process at the hotspots, but also to quantify properties and population at risk, hence an essential knowledge-base for policy makers and regulators to optimize groundwater resource management, and accommodate existing and future water demands.

 

[1] Cigna F., Tapete D. 2021. Present-day land subsidence rates, surface faulting hazard and risk in Mexico City with 2014-2020 Sentinel-1 IW InSAR. Remote Sensing of Environment, 253, 112161, https://doi.org/10.1016/j.rse.2020.112161

[2] Cigna F., Tapete D. 2021. Satellite InSAR survey of structurally-controlled land subsidence due to groundwater exploitation in the Aguascalientes Valley, Mexico. Remote Sensing of Environment, 254, 112254, https://doi.org/10.1016/j.rse.2020.112254

[3] Cigna F., Tapete D. 2022. Urban growth and land subsidence: Multi-decadal investigation using human settlement data and satellite InSAR in Morelia, Mexico. Science of the Total Environment, 811, 152211. https://doi.org/10.1016/j.scitotenv.2021.152211

How to cite: Cigna, F. and Tapete, D.: Land subsidence hotspots in Central Mexico: from Sentinel-1 InSAR evidence to risk maps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1467, https://doi.org/10.5194/egusphere-egu22-1467, 2022.

10:56–11:03
block #3 Q&A

11:03–11:08
block #4 (10,20-11,50), introduction

11:08–11:15
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EGU22-935
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ECS
Paola Rizzoli et al.

Covering about 30 percent of the Earth’s surface, forests are of paramount importance for the Earth’s ecosystem. They act as effective carbon sinks, reducing the concentration of greenhouse gas in the atmosphere, and help mitigating climate change effects. This delicate ecosystem is currently threatened and degraded by anthropogenic activities and natural hazards, such as deforestation, agricultural activities, farming, fires, floods, winds, and soil erosion. In an era of dramatic changes for the Earth’s ecosystems, the scientific community urgently needs to better support public and societal authorities in decision-making processes. The availability of reliable, up-to-date measurements of forest resources, evolution, and impact is therefore of paramount importance for environmental preservation and climate change mitigation.

In this scenario, Synthetic Aperture Radar (SAR) systems, thanks to their capability to operate in presence of clouds, represent an attractive alternative to optical sensors for remote sensing over forested areas, such as tropical and boreal forests, which are hidden by clouds for most of the year.

In this work, we will investigate the potential of SAR interferometry (InSAR) for mapping forests worldwide and retrieve important biophysical parameters, such as canopy height and above ground biomass. We will compare pros and cons of single-pass (bistatic) versus repeat-pass InSAR, discussing their main peculiarities and limitations. In particular, we will concentrate on the analysis of the interferometric coherence and on the relationship between volume and temporal decorrelation with respect to forest parameters estimation. We will present the work done at DLR for mapping forests worldwide at high spatial resolution using the TanDEM-X bistatic coherence, together with the potential of Sentinel-1 InSAR time-series for a regular monitoring of vegetated areas. We will discuss the algorithms which currently under development for the estimation of above ground biomass, by fusion of InSAR and multi-spectral optical data, based on the latest advances in the field of artificial intelligence and, in particular, of deep learning, presenting the first promising results for a more effective exploitation of current EO datasets.

 

How to cite: Rizzoli, P., Bueso-Bello, J.-L., Dal Molin, R., Carcereri, D., Gonzalez, C., Martone, M., Dell'Amore, L., Gollin, N., Milillo, P., and Zink, M.: The value of InSAR Coherence in TanDEM-X and Sentinel-1 for monitoring world’s forests, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-935, https://doi.org/10.5194/egusphere-egu22-935, 2022.

11:15–11:22
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EGU22-4919
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ECS
|
On-site presentation
Francesco Falabella and Antonio Pepe

Multi-temporal interferometric synthetic aperture radar (InSAR) algorithms represent nowadays mature tools to analyze the Earth’s ground deformation with high accuracy. Among them, a significant role is played by those algorithms based on the use of small-baseline (SB) multi-look interferograms, which are less affected by decorrelation noise artefacts. Recently, there is a great concern on the studying the sources of some inconsistencies in the InSAR products (i.e., ground deformation time-series and mean deformation velocity maps) that happen when sets of multi-look SAR interferograms with very short temporal baselines are processed, compared to those obtained using interferograms with longer temporal baselines. Concerning the interferometric SAR analyses for the study of the Earth's surface displacements, such spurious signals lead to systematic biases that, if not adequately compensated for, might lead to unreliable InSAR ground displacement products.

In this study, we propose a methodology to estimate and correct a set of multi-look SB interferograms that is based on computing and analyzing sets of (wrapped) non-closure phase triplets. The developed phase estimation method works on every single SAR pixels independently, assuming the (unknown) phase bias signal could be approximated as the sum of a constant phase velocity term v and a time-dependent (i.e., dependent on the interferograms temporal baseline) phase velocity difference terms Δv(Δti ), where Δti is the temporal baseline of the generic i-th interferogram. Once the whole set of triplets that could be formed using short baseline ML interferograms is identified, and considering the mathematical properties of the triplets non-closure phases, we can write an overdetermined system of linear equations, where the known terms are the measured wrapped non-closure phases over the set of identified triplets, namely ΔΦtriplets , and the unknowns are the temporal-baseline-dependent phase velocity difference terms Δv . For example, considering the Sentinel1-A/B sensors, the temporal baseline is sampled with an atomic sampling time of six days; accordingly, if we accept, for instance, a threshold of 96 days for the maximum allowed temporal baseline of the selected SB interferograms, we have 16 unknowns to be estimated. Once the linear system is solved in the Least-Squares sense, the phase biases at the different temporal baselines, namely ΔΦbias , are iteratively retrieved by integrating the phase acceleration terms, assuming as the initial condition that the phase bias at the maximum considered temporal baseline is zero, that is Δφbiasmax_baseline = 0.

Preliminarily experiments, performed on sets of Sentinel1-A/B SAR data in different geo-morphological conditions, demonstrate the effectiveness of the developed methodology. Additionally, we performed some simulations and experiments to test the validity of an extension of the developed method to the non-stationary case, e.g., when the phase bias signals depend on the specific single time acquisitions of the SAR images involved in the SB interferograms generation, and not only on their temporal baselines. Our work is propaedeutic for further investigations aiming at retrieving/analyzing the ground properties of the imaged targets on the terrain, such as the soil moisture content or other local ground properties that are usually not considered appropriately by conventional InSAR analyses.

How to cite: Falabella, F. and Pepe, A.: A Method for the Correction of Non-Closure Phase Artefacts in Triplets of Multi-look SAR Interferograms, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4919, https://doi.org/10.5194/egusphere-egu22-4919, 2022.

11:22–11:29
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EGU22-26
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Virtual presentation
Fabio Bovenga et al.

Multi-temporal SAR interferometry (MTInSAR),  allows analysing wide areas, identifying critical ground instabilities, and studying the phenomenon evolution in a long time-scale.  The identification of MTInSAR displacements trends showing non-linear kinematics is of particular interest since they include warning signals related to pre-failure of natural and artificial structures. Recently, the authors have introduced two innovative indexes for characterising MTInSAR time series: one relies on the fuzzy entropy and measures the disorder in a time series [1], the other performs a statistical test based on the Fisher distribution for selecting the polynomial model that more reliably approximate the displacement trend [2].

This work reviews the theoretical formulation of these indexes and evaluate their performances by simulating time series with different characteristics in terms of kinematic (stepwise linear with different breakpoints and velocities), level of noise, signal length and temporal sampling. Finally, the proposed procedures are used for analysing displacement time series derived by processing Sentinel-1 and COSMO-SkyMed datasets acquired over Southern Italian Apennine (Basilicata region), in an area where several landslides occurred in the recent past. The MTInSAR displacement time series have been analysed by using the proposed methods, searching for nonlinear trends that are possibly related to relevant ground instabilities and, in particular, to potential early warning signals for the landslide events. Specifically, the work presents an example of slope pre-failure monitoring on Pomarico landslide, an example of slope post-failure monitoring on Montescaglioso landslide, and few examples of structures (such as buildings and roads) affected by instability related to different causes.

References

[1] Refice, A.; Pasquariello, G.; Bovenga, F. Model-Free Characterization of SAR MTI Time Series. IEEE Geosci. Remote Sens. Lett. 2020, doi:10.1109/lgrs.2020.3031655.

[2] Bovenga, F.; Pasquariello, G.; Refice, A. Statistically‐based trend analysis of mtinsar displacement time series. Remote Sens. 2021, doi:10.3390/rs13122302.

Acknowledgments

This work was supported in part by the Italian Ministry of Education, University and Research, D.D. 2261 del 6.9.2018, Programma Operativo Nazionale Ricerca e Innovazione (PON R&I) 2014–2020 under Project OT4CLIMA; and in part by Regione Puglia, POR Puglia FESR-FSE 204-2020 - Asse I - Azione 1.6 under Project DECiSION (p.n. BQS5153).

How to cite: Bovenga, F., Refice, A., Argentiero, I., Nutricato, R., Nitti, D. O., Pasquariello, G., and Spilotro, G.: Detection of nonlinear kinematics in InSAR displacement time series for hazard monitoring, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-26, https://doi.org/10.5194/egusphere-egu22-26, 2022.

11:29–11:36
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EGU22-9194
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ECS
|
|
On-site presentation
Marta Zocchi et al.

A-DInSAR (Advanced Differential Synthetic Aperture Radar Interferometry) is widely acknowledged as one of the most powerful remote sensing tools for measuring Earth’s surface displacements over large areas, and in particular landslides. The Persistent Scatterer Interferometry (PS-InSAR or PSI) is a common A-DInSAR multitemporal technique, which allows retrieving displacement measurements with sub-centimetric precision. Characterization and interpretation of landslides can greatly benefit from the application of A-DInSAR post-processing tools, especially when extremely slow-moving phenomena are not detectable by classical geomorphological investigations, or when complex displacement patterns need to be highlighted. Detailed representations of the spatial and temporal evolution of the processes provide useful constraints during the planning stages of reconstructions and for land use purposes.
The present study is part of a broader national project, focused on updating and monitoring landslide-prone slopes interacting with urban centres in the Central Apennines (Italy), by using both geomorphological and A-DInSAR analysis. Therefore, although field surveys permitted the systematic updating of the available landslide inventories, in most cases, clear indications of displacement were outlined only by the SAR interferometry results. In this regard, the preliminary results of the ongoing research focus on specific post-processing analyses of interferometric data performed in the study area. 
A specific PS-toolbox software, developed by NHAZCA S.r.l. as a set of post-processing plugins for the open-source software QGIS, was specifically designed to enhance spatial and temporal deformation trends of the PSI results, as well as for visualizing the differences between multi-satellite datasets. Moreover, the PS-toolbox allowed depicting subtle surface patterns within the landslide area, shedding light on kinematics and style of activity of slope instabilities.  
In complex morphological conditions, as the Apennines mountainous regions, the geometric distortions and the site coverage percentage can lead to a lack of information. Therefore, we compared the coverage of PSs and the accuracy of the surface velocity maps produced using different InSAR tool packages on both Sentinel-1 and COSMO-SkyMed scenes. Thus, the comparison of the resulting datasets allowed their validation in terms of measured displacements and reliability for further processing.

How to cite: Zocchi, M., Antonielli, B., Marini, R., Masciulli, C., Pantozzi, G., Troiani, F., Mazzanti, P., and Scarascia Mugnozza, G.: The importance of InSAR data post-processing for the interpretation of geomorphological processes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9194, https://doi.org/10.5194/egusphere-egu22-9194, 2022.

11:36–11:50
block #4 Q&A,

Thu, 26 May, 17:00–18:30

Chairpersons: Alessandro Novellino, Roberta Bonì, Marta Béjar-Pizarro

17:00–17:05
block #5 (17-18,30), introduction

17:05–17:15
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EGU22-6817
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ECS
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solicited
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On-site presentation
Alexander Handwerger et al.

Slow-moving landslides are hydrologically driven and respond to changes in precipitation over daily to decadal timescales. Open-access satellite InSAR data products, which are becoming increasingly common, can be used to investigate landslides (and other ground surface deformation) over large regions. Here we use standardized open-access satellite radar interferometry data processed by the Advanced Rapid Imaging and Analysis (ARIA) team at NASA’s Jet Propulsion Laboratory to identify 247 active landslides in California, USA. These landslides occur in both wet and dry climates and span more than ~2 m/yr in mean annual rainfall. We quantify the sensitivity of 38 landslides to changes in rainfall, including a drought and extreme rainfall that occurred in California between 2015 and 2020. Despite the large differences in climate, we found these landslides exhibited surprisingly similar behaviors and hydrologic sensitivity, which was characterized by faster (slower) than normal velocities during wetter (drier) than normal years. Our study documents the first application of open-access standardized InSAR products from ARIA to identify and monitor landslides across large regions. Due to the large volume of open-access InSAR data that is currently available, and will continue to increase with time, especially with the upcoming launch of the NASA-ISRO SAR (NISAR) satellite, standardized InSAR products will become one of the primary ways to deliver InSAR data to the broader scientific community. Thus, it is important to continue to explore new approaches to analyze these InSAR products for scientific research.

How to cite: Handwerger, A., Fielding, E., Sangha, S., and Bekaert, D.: Tracking slow-moving landslides over large regions using open-access standardized InSAR products produced by the Advanced Rapid Imaging and Analysis (ARIA) Center for Natural Hazards project, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6817, https://doi.org/10.5194/egusphere-egu22-6817, 2022.

17:15–17:22
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EGU22-1327
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On-site presentation
Matteo Del Soldato et al.

In 2016, a first worldwide continuous monitoring was proposed and implemented over the Tuscany Region (central Italy). It was the first application of SAR (Synthetic Aperture Radar) images for continuous monitoring of on-going ground deformations and, thanks to a PS (Permanent Scatterers) time-series data-mining for identifying changes in the trend, i.e. sudden accelerations or decelerations. The data-mining algorithm was devoted to automatically recognize trend variations higher than a velocity threshold in a determined time span. The continuous monitoring approach benefits from the launch, in 2014, of the Sentinel-1 constellation that allows having a constant flux of images every 12 days (halved to 6 days since 2016 considering the twin satellite at 180° on the same orbit). Two years after Tuscany, in April 2018, the Valle d’Aosta Region, north-western Italy, implemented a similar system to monitor its territory. The challenge was to apply the same approach, with very few changes adopted, in a region with completely different geological and geomorphological features, also considering the snow and glacial covering in winter. In fact, the Tuscany territory is characterized by wide plains, gentle slopes, and mountainous ridges limited to the eastern border in concomitants with the Northern Apennines. Consequently, the ground deformation phenomena in Tuscany are related to active and dormant landslides and subsidence phenomena, mainly due to groundwater extraction and, less commonly, geothermal activity. Valle d’Aosta Region, on the contrary, is almost all characterized by steep slopes with a central close valley. For this reason, the ground deformations to recognize and monitor are almost totally related to landslides, DSGSDs (deep-seated gravitational slope deformation) or rock glaciers. Then, a year later, in July 2019, the continuous monitoring was activated also over the Veneto Region, North-East of Italy. Its territory has partially similar characteristics to Tuscany, in the southern portion, and to the Valle d’Aosta features, in the northern part. Considering the geological and geomorphological properties, the detected ground deformations from Veneto Region share many similarities with the ones from the other two regions. These three laboratories were critically investigated, and after one-year of life, the benefits and the drawbacks of this approach over different environments were highlighted. For all the regions, separately (i) the spatial distribution of the anomalies regions, considering the slope, the aspect, the land cover, and the height, (ii) the persistency of the anomalies along time, (iii) and the correspondence between highlighted moving areas and known inventories, were investigated. At the end, considerations about the benefits evidenced by the use of this approach, considering also the good feedback of the regional administrative personnel, and the required improvements were critically taken into account.

How to cite: Del Soldato, M., Confuorto, P., Festa, D., Bianchini, S., and Raspini, F.: Considerations on regional continuous Sentinel-1 monitoring services over three different regions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1327, https://doi.org/10.5194/egusphere-egu22-1327, 2022.

17:22–17:29
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EGU22-12583
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ECS
Benedetta Dini et al.

In the last few decades, InSAR has been used to identify ground deformation related to slope instability and to retrieve time series of landslide displacements. In some cases, retrospective retrieval of time series revealed acceleration patterns precursory to failure. This suggests that, the higher temporal sampling of new generation satellites, may indeed offer the opportunity to detect motion precursory to failure with viable lead time.

However, the possibility to retrieve continuous time series over landslides is often impaired by factors such as unfavourable orientation or landcover and fast movements, which make phase unwrapping difficult if not, in certain cases, impossible.

One way to retrieve precursors of destabilisation for landslides that present characteristics unfavourable to unwrapping and to time series inversion is to analyse in detail changes in successive interferograms in the phase domain in combination with interferometric coherence.  

We generated and analysed 102 Sentinel-1 interferograms, covering the period between April 2015 and February 2021, at high spatial resolution (8 and 2 looks in range and azimuth respectively) over the Achoma landslide in the Colca valley, Peru. This large, deep-seated landslide, covering an area of about 40 hectares, previously unidentified, failed on 18th June 2020, damming the Rio Colca and giving origin to a lake.

We developed a method to analyse the changes through time of the unwrapped phase difference between a stable point and points within the landslide. In combination with this, we investigated patterns of coherence loss both within the landslide and in the surrounding area.

We observed that, in the weeks prior to the landslide, there was an increase of the phase difference between a stable reference and points within the landslide, indicating an acceleration of the downslope displacements. In addition to that, seasonal coherence loss is seen both within the landslide and in the surrounding area, in correspondence with wet periods. However, we observed also significant, local coherence loss outlining the scarp and the southeastern flank of the landslide, intermittently in the years before failure, in periods in which coherence was overall higher. Moreover, we observe a sharp decrease in the ratio between the coherence within the landslide and in the surrounding area, roughly six months before the failure.

This type of approach is promising with respect to the extraction of relevant information from interferometric data when the generation of accurate and continuous time series of displacements is hindered by the nature of landcover or of the landslide studied, such in the case of the Achoma landslide. The combination of key, relevant parameters and their changes through time obtained with this methodology may prove necessary for the identification of precursors over a wider range of landslides than with time series generation alone.

 

How to cite: Dini, B., Lacroix, P., and Doin, M.-P.: InSAR application for the detection of precursors on the Achoma landslide, Peru, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12583, https://doi.org/10.5194/egusphere-egu22-12583, 2022.

17:29–17:36
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EGU22-11186
Mylene Jacquemart and Andrea Manconi

Deep-seated slope instabilities pose a significant hazard to infrastructure and livelihoods in mountain regions all around the world. Increasingly accesible data from synthetic aperture radar (SAR) satellites, such as ESA’ Copernicus Sentinel-1 mission, offer easier access to displacement data that can be used to detect, delineate, and monitor landslides in mountainous terrain. However, displacement measurements retrieved from differential interferometric processing (DInSAR) can be biased by the terrain geometry, which can lead to an underestimation of the true displacement. In addition, the quality of DInSAR results is highly susceptible to changes of surface geometry and moisture conditions, for example due to snow melt, hillslope erosion, or vegetation changes. Furthermore, the relative nature of DInSAR measurements can lead to underestimation of displacements due to phase aliasing. These factors may severely impact the accuracy of landslide velocities quantification. However, landslide velocities are often directly used in hazard assessment.

 

In Switzerland, mean and maximum landslide velocities are key factors used to assess the hazard intensity of unstable slopes, and thus to determine the slope hazard potential and consequently hazard zonation. The latter has direct implications for land use and land-use planning. In this study, we use two exemplary large deep-seated instabilities at Brienzauls (canton of Grisons) and Spitzer Stein (canton of Bern), both in Switzerland, to showcase the challenges of relying on DInSAR derived velocities for hazard mapping. We attempt to disentangle effects of terrain and orbit geometry on the measurable velocities from those caused by transient changes to surface geometry and conditions, and explore ways by which the value of DInSAR-derived displacement measurements can nevertheless be maximized for hazard zonation mapping. 

How to cite: Jacquemart, M. and Manconi, A.: Values and challenges of DInSAR derived velocity estimates for landslide hazard assessment and mapping, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11186, https://doi.org/10.5194/egusphere-egu22-11186, 2022.

17:36–17:43
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EGU22-12898
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ECS
Josefa Sepúlveda et al.

Iceland is in a Mid Ocean Ridge, where the North American Plate is moving far away from Eurasian Plate at a relative rate of 18-19 mm/yr. The boundary between plates is marked by an active neovolcanism expressed by different volcanoes centres and fissures swarms. Askja volcano is located in the North Volcanic Zone of Iceland. It has an area of 45 km3 and hosts three calderas. Three main eruptions have been observed during different periods: i) 1874 to 1876, ii) 1921-1929, and iii) 1961. Monitoring data have shown a period of alternance between subsidence and uplift between 1966 to 1972. Thereafter, since at least 1983 the caldera has been subsiding at a rate of 5 cm/yr, but this rate has been decaying slowing with time. Additionally, tomography data has revealed a possible deeper zone (between 9 and 15 km depth) below the volcano where melting is storage and also the seismicity between 20 and 25 km depth may be interpreted like a magma movement in this area. However, there are still questions about what is producing the subsidence at Askja. In this work, we present Interferometry Synthetic Aperture Radar (InSAR) results during the period of 2015 to 2021 in Askja. This data will help to constraint what is it causing the subsidence at Askja Caldera.

How to cite: Sepúlveda, J., Hooper, A., Ebmeier, S., and Novoa, C.: Subsidence in Askja Caldera between 2015 to 2021, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12898, https://doi.org/10.5194/egusphere-egu22-12898, 2022.

17:43–17:50
block #5 Q&A

17:50–17:55
block #6 (17-18,30), introduction

17:55–18:02
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EGU22-1690
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On-site presentation
Oriol Monserrat et al.

In the last few years, satellite interferometry (InSAR) has become a consolidated technique for the detection and monitoring of ground movements. InSAR based techniques allows to process large areas providing a high number of displacement measurements with low cost. However, the outputs provided by such techniques are usually not easy, hampering the interpretation and time-consuming. This is critical for users who are not familiar with radar data. European Ground Motion Service (Copernicus) is a new public service that will bring a step forward in this context. However, the capability of exploiting it will still rely on the user experience. In this context, the development of methodologies and tools to automatize the information retrieval and to ease the results interpretation is a need to improve its operational use. Here we propose a set of tools and methodologies to detect and classify Active Deformation Areas, and to map the potential damages to anthropic elements, based on differential displacements. We present the results achieved in the coast of Granada, which is strongly affected by slope instabilities. The methodology is applied at a regional scale and allows to go to a detailed local scale of analysis. The presented results have been achieved within the framework of the Riskcoast Project (financed by the Interreg Sudoe Program through the European Regional Development Fund (ERDF)).

 

How to cite: Monserrat, O., Barra, A., Reyes-Carmona, C., Mateos, R. M., Galve, J. P., Tomas, R., Herrera, G. H., Bejar, M. B., Azañón, J. M., Navarro, J., and Sarro, R.: Tools for supporting Sentinel-1 data interpretation: the coast of Granada (Spain), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1690, https://doi.org/10.5194/egusphere-egu22-1690, 2022.

18:02–18:09
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EGU22-10347
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ECS
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On-site presentation
Gauhar Meldebekova et al.

Strata deformation associated with underground longwall coal mining can induce large magnitudes of ground surface subsidence. The Karagandy basin, one of the largest coal mining regions in Kazakhstan, is located in close proximity to urban areas and critical infrastructure, necessitating detailed investigation into the spatial distribution and temporal dynamics of subsidence. Synthetic aperture radar interferometry (InSAR) is recognised as a powerful tool to detect, map and quantify ground deformation. In this research, C-band Sentinel-1 products were used to implement interferometric and time-series analysis using the Small BAseline Subset (SBAS) algorithm. Subsidence bowls were detected over eight mining sites. The maximum annual velocity along line-of-sight, some ‑82 mm/year,  was detected at the Kostenko mine, whilst cumulative subsidence reached a maximum of 350 mm in five years.  Wavelet transform analysis was used to inspect the non-linear nature of the signal and confirmed the annual periodicity of ground deformation. Spatio-temporal analysis of subsidence patterns revealed the different drivers of deformation, with sites clustered accordingly. Results from the research offer considerable insight for facilitating decision-making in forward sustainable mining operations, both in Kazakhstan and further afield.

How to cite: Meldebekova, G., Yu, C., Mills, J., and Li, Z.: Monitoring mining-induced ground deformation in Karagandy mining basin using InSAR, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10347, https://doi.org/10.5194/egusphere-egu22-10347, 2022.

18:09–18:16
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EGU22-11969
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ECS
|
|
On-site presentation
Natalia Wielgocka et al.

Monitoring the deformation of the mining ground surface is crucial to ensuring the safety of residents, workers and the protection of all infrastructure in mining areas.The Polish realization of the European Plate Observing System project (EPOS-PL and its continuation EPOS-PL+) aims to build an infrastructure to monitor the deformation of the ground surface caused by extensive underground mining activities in the area of Upper Silesian Coal Basin in Southern Poland.  Among many geodetic and geophysical approaches for monitoring, two different Interferometric Synthetic Aperture Radar (InSAR) techniques have been applied, also taking the advantage of the big set of freely available and with shorter revisiting time (6 days) Sentinel-1 satellite data. In the current study the Differential InSAR (DInSAR) and the Persistent Scattered Interferometry (PSInSAR) approaches are compared, evaluated and integrated. Various processing strategies are tested aiming to increase the quality of the produced integrated deformation maps. The optimal processing strategy should accurately detect stable areas, estimate the small deformation, as well as the maximum deformation gradient occurring in the center of the subsidence bowl directly in the excavation area. 

One of the main error contributors to the Sentinel-1 data is the water vapor in the atmosphere that might slower the radar signal and modulate the results. Thus, the atmospheric artefacts have to be minimized since they are one of the main effects that limits the accuracy of interferometric products. In the PSInSAR approach high-pass and low-pass filtering has been used, while in the DInSAR approach – estimation of the Atmospheric Phase Screen has been made based on polynomial surface estimation using stable coherent points. Comparison of the one-year cumulated deformation for the area of Rydułtowy mine in Poland with ground truth data such as static GNSS measurement on reference points shows that PSInSAR results are more accurate. However, due to the linear deformation model required in the PSInSAR processing the areas in the center of the subsidence bowls were not estimated. Therefore, the difference between PSInSAR and DInSAR results was used for the refinement of the DInSAR deformation map. This refinement was made based on various statistical approaches (e.g. polynomial interpolation, kriging, inverse distance weighted-IDW). The results of IDW and kriging shows the best performance and allowed to minimize errors associated with DInSAR approach and provide a more accurate deformation map in the area of mining as well as provided the opportunity to capture maximal deformation gradient. 

How to cite: Wielgocka, N., Pawluszek-Filipiak, K., and Ilieva, M.: Combined DInSAR-PSInSAR approach for increasing the quality of deformation map estimation in the area of underground mining exploitation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11969, https://doi.org/10.5194/egusphere-egu22-11969, 2022.

18:16–18:23
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EGU22-12311
Wojciech Milczarek et al.

Measuring how the Earth’s surface deforms in response to natural and anthropogenic processes allows scientists to better understand them and the risks associated with them. Synthetic aperture radar interferometry (InSAR) enables monitoring the land surface in order to detect and trace changes of altitude which result from such phenomena as volcanic, seismic, landslides, or glacier movements (natural) and mining and post-mining, water pumping, or gas storage (anthropogenic). Simultaneously trace changes of land surfaces having an area up to approx. 48,000 km (in the case of Sentinel 1A/1B satellites for one scene) with an interval of between 6 and 12 days (due to the time required for SAR data acquisition) allows to monitor surface displacements in regional or national scale. 

We present results of measurements covering the entire Poland for the period 6  years, from 2015 to the end of 2020. The time series were developed based on the SBAS algorithm. Due to shifts of scenes in the azimuth direction in a given path, we developed an algorithm to crop and merge the raw imagery to predefined ranges. This allowed to formulate a series of interferometers with the same ranges, uniformly covering the entire area. Finally, we performed calculations of 32 frames (14 from ascending and 18 descending orbits). Based on time series, identified numerous areas where significant, anthropogenic or natural nature, surface displacement appears. The collected displacement observations allow not only to monitor areas where displacement occurs continuously, e.g. as a result of direct effects of mining operations, but also to identify regions of new, previously unidentified displacement, displacements occurring temporarily, or very slow movements of large areas.

How to cite: Milczarek, W., Kopeć, A., Głąbicki, D., Sompolski, M., Tympalski, M., and Bugajska, N.: Synthetic aperture radar interferometry in a subregional scale as a source for the monitoring of contemporary surface movements in the areas of Poland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12311, https://doi.org/10.5194/egusphere-egu22-12311, 2022.

18:23–18:30
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EGU22-7159
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ECS
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Virtual presentation
Maria Przyłucka et al.

The paper presents the results of long-term terrain subsidence monitoring in the mining area of the Upper Silesian Coal Basin (USCB) in Poland using Interferometry Synthetic Aperture Radar (InSAR), supplemented with differential analysis of digital elevation models. The work included analysis of mining-induced subsidence based on three archival surface models: historical terrain model obtained from the digitization of Messtischblatt topographic maps, representing the surface in 1919-1944; numerical terrain model DTED, derived from the vectorization of diaposites of topographic maps from the 90s of the twentieth century; LIDAR digital terrain model from 2013. Archival analyses were complemented by the newest PSInSAR database of Sentinel-1 data, processed for the entire area of USCB. The data covered a period of 6 years (October 26, 2014 - June 26, 2020), in which a total of 260 scenes from 124 descending paths were used. In the time domain, data were recorded at intervals of 12 days (for one Sentinel-1 satellite) or every 6 days for the full Sentinel-1 A / B constellation. The entire collection includes 8,139,901 PS points over 6,620 km2, giving an average density of about 1230 PS /sq km. The dataset enabled the analysis of contemporary vertical land movements. This huge set of various data was used to analyze the long-term influence of mining in the area broken down into time intervals, collectively covering the period from the mid-twentieth century to 2020. As a result of the analyzes, zones of mining-induced subsidence were developed, where the terrain surface was systematically changed in individual years. The data allowed for over 600 sq km identification under the influence of exploitation. Subsidence areas were matched with topographic data such as buildings and roads to estimate the effect of subsidence on urban areas. The work shows the great advantage of remote monitoring methods, which is the possibility of showing the long-term environmental impact to a large extent. The use of both historical and the latest data allowed for a comprehensive analysis of changes on the surface of the area now and in the past.

How to cite: Przyłucka, M., Perski, Z., and Kowalski, Z.: Long-term analysis of the environmental impact of mining in the Upper Silesia Coal Basin area based on historical and the latest remote sensing data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7159, https://doi.org/10.5194/egusphere-egu22-7159, 2022.