NH6.5

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.