scholarly journals Application of a Small Baseline Subset Time Series Method with Atmospheric Correction in Monitoring Results of Mining Activity on Ground Surface and in Detecting Induced Seismic Events

2019 ◽  
Vol 11 (9) ◽  
pp. 1008 ◽  
Author(s):  
Wojciech Milczarek
Keyword(s):  
Time Series ◽  
Underground Mining ◽  
Ground Surface ◽  
Mining Activity ◽  
Seismic Events ◽  
Atmospheric Delay ◽  
Small Baseline Subset ◽  
Sar Data ◽  
Small Baseline ◽  
Surface Changes

The article presents the results of applying a Small Baseline Subset (SBAS) method to the monitoring of the influence of underground mining exploitation on terrain surface. Calculations were performed on the basis of two large SAR data sets. Calculations of time series additionally employed the Tymofyeyeva and Fialko empirical method for estimating atmospheric delay. A series of test calculations allowed verifying the potential of the method. The SBAS calculations were based on theoretical data prepared with the use of the Mogi model. This approach allowed simulating both underground mining exploitation and induced tremors. The results indicate that the model is useful in detecting sudden ground surface deformations. In such a situation, the image of a tremor can be observed in the atmospheric component. The actual data used in the analysis covered a region of underground copper ore extraction in southwest Poland. The calculations were based on SAR data obtained from the Sentinel 1A/B satellites, for the period between the end of 2014 and May 2018, from paths 22 and 73. In both cases, the total number of images exceeded 120. They served to calculate over 420 interferograms for each set. The results of ground surface displacements allowed precise identification of areas affected by underground mining activity. Over the acquisition period of six days, sufficient amount of SAR data was obtained to precisely monitor surface changes in the analyzed area. The employed empirical atmospheric delay reduction method was demonstrated to enable the detection of sudden ground surface changes due to mining tremors. This feature makes the method useful in detecting induced seismic events in areas characterized by intensive mining activity. It allows determining tremor locations in cases when acquisition dates are greater than the optimal value of 6–12 days (in the case of Sentinel 1A/B).

scholarly journals Time-Series InSAR Analysis of the Small Baseline Subset to Estimate Surface Deformation at Mt. Bromo Indonesia

Teknik ◽  
2019 ◽  
Vol 39 (2) ◽  
pp. 126
Author(s):  
Arliandy Pratama Arbad ◽  
Wataru Takeuchi ◽  
Yosuke Aoki ◽  
Achmad Ardy ◽  
Mutiara Jamilah
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Sar Interferometry ◽  
Alos Palsar ◽  
Small Baseline Subset ◽  
Sar Data ◽  
Small Baseline

Penginderaan jauh kini memainkan peranan penting dalam pengamatan perilaku gunung api. Penelitian ini bertujuan untuk mengamati deformasi permukaan Gunung Bromo, yang terletak di Jawa bagian Timur, Indonesia, yang masuk dalam rangkaian sistem volkanik di Taman Nasional Bukit Tengger Semeru (TNBTS). Penggunaan algoritma SAR Interferometry (InSAR) yang disebut sebagai pendekatan Small Baseline Subset (SBAS) memungkinkan perancangan peta kecepatan deformasi rata-rata dan and peta time series displacement di wilayah kajian. Teknik SBAS yang biasa menghasilkan rangkaian observasi tahap interferometrik. Ini tercatat sebagai kombinasi linear dari nilai fase SAR  scene untuk setiap pixel secara tersendiri. Analisis yang dilakukan terutama berdasarkan 22 data SAR data yang diperoleh melalui sensor ALOS/PALSAR selama kurun waktu 2007–2011. Beberapa penelitian menunjukkan bahwa kemampuan analisis InSAR dalam menyelidiki siklus gunung api, terutama Gunung Bromo yang memiliki karakteristik erupsi stratovolcano dalam satu hingga lima tahun. Analisis hasil memperlihatkan adanya kemajuan dari kajian sebelumnya akan InSAR wilayah tersebut, yang lebih fokus  kepada deformasi yang berpengaruh kepada kaldera. Hal ini menunjukkan bahwa penelitian ini bisa diimplementasikan pada manajemen risiko atau manajemen infrastruktur

Continental scale SBAS-DInSAR processing for the generation of Sentinel-1 deformation time series within a cloud computing environment: achieved results and lessons learned

2020 ◽  
Author(s):  
Riccardo Lanari ◽  
Manuela Bonano ◽  
Sabatino Buonanno ◽  
Francesco Casu ◽  
Claudio De Luca ◽  
...  
Keyword(s):  
Time Series ◽  
Cloud Computing ◽  
Surface Deformation ◽  
Stress Test ◽  
Sar Interferometry ◽  
Continental Scale ◽  
Spatial Coverage ◽  
Small Baseline Subset ◽  
Sar Data ◽  
Small Baseline

<p>The Sentinel-1 constellation of the Copernicus Program already represents a big revolution within the Earth Observation (EO) scenario. This result is mainly due to the capability of this constellation to acquire huge volumes of SAR data all over the globe, with a wide spatial coverage, a short revisit time (12 or 6 days in the case of one or two operating satellites, respectively), and a free and open access data policy. In particular, the availability of such a large amount of SAR data acquired through the TOPS mode, characterized by a short “orbital tube” (with a 200m nominal diameter) and a specific design for ensuring differential SAR interferometry (DInSAR) applications, has opened the possibility to investigate Earth surface deformation phenomena at unprecedented spatial scale and with a high temporal rate.</p><p> </p><p>Among several advanced DInSAR algorithms, a widely used approach is the Small BAseline Subset (SBAS) technique, which has already proven its effectiveness to investigate surface displacements with centimeter- to millimeter-level accuracy in different scenarios. Moreover, a parallel algorithmic solution for the SBAS approach, referred to as Parallel Small BAseline Subset (P-SBAS), has been recently developed. This approach permits to generate, in an automatic and unsupervised way, advanced DInSAR products by taking full benefit from parallel computing architectures, such as cluster, grid and, above all, cloud computing infrastructures.</p><p> </p><p>In this work we present the results of a DInSAR experiment, based on the P-SBAS approach, carried out at the European scale. In particular, we exploited the entire available Sentinel-1 dataset collected through the TOPS acquisition mode between March 2015 and September 2018 from descending orbits over large part of Europe. Moreover, the overall analysis wasbcarried out by using the Copernicus Data and Information Access Services (DIAS) and, in particular, those provided by the ONDA DIAS platform, which was selected through a public tender. This activity, carried out as stress test of the EPOSAR service included in the Satellite Data Thematic Core Service of the EPOS infrastructure, permitted to investigate the DIAS capacity to operationally serve systematic and automatic DInSAR processing services, such as the one based on the P-SBAS approach.</p><p> </p><p>Our experiment was successfully completed, allowing the retrieval of the deformation time-series of the overall investigated area with the final products having the main characteristics summarized in the following:</p><p> </p><ul><li>Exploited Sentinel-1 data: ~72.000</li> <li>Covered Area: ~4.500.000 km<sup>2</sup></li> <li>Coherent (multilook) SAR pixels: ~120.000.000</li> <li>Final products pixel dimension: ~80 m</li> <li>Time elapsed: ~6 months</li> </ul><p> </p><p>The presented discussion will highlight the main pros and cons of the exploited solution for such wide area DInSAR experiment. Moreover, the analysis of the achieved results will also show the high quality of the retrieved DInSAR results, that can be of interest for the Solid Earth scientific community, and the potentially positive impact of the presented solution for what concerns the future development of the European Ground Motion Service.</p><p>This work is supported by: the 2019-2021 IREA-CNR and Italian Civil Protection Department agreement; the H2020 EPOS-SP project (GA 871121); the I-AMICA (PONa3_00363) project; and the IREA-CNR/DGSUNMIG agreement.</p>

Detecting land deformation due to groundwater changes with InSAR observations - the case of the island of Gotland, Sweden

2021 ◽  
Author(s):  
Mehdi Darvishi ◽  
Fernando Jaramillo
Keyword(s):  
Land Subsidence ◽  
Groundwater Level ◽  
Ground Deformation ◽  
Soil Depth ◽  
Ground Surface ◽  
Groundwater Depletion ◽  
Groundwater Levels ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
The Baltic

<p>In the recent years, southern Sweden has experienced drought conditions during the summer with potential risks of groundwater shortages. One of the main physical effects of groundwater depletion is land subsidence, a geohazard that potentially damages urban infrastructure, natural resources and can generate casualties. We here investigate land subsidence induced by groundwater depletion and/or seasonal variations in Gotland, an agricultural island in the Baltic Sea experiencing recent hydrological droughts in the summer. Taking advantage of the multiple monitoring groundwater wells active on the island, we explore the existence of a relationship between groundwater fluctuations and ground deformation, as obtained from Interferometric Synthetic Aperture Radar (InSAR). The aim in the long-term is to develop a high-accuracy map of land subsidence with an appropriate temporal and spatial resolution to understand groundwater changes in the area are recognize hydroclimatic and anthropogenic drivers of change.</p><p>We processed Sentinel-1 (S1) data, covering the time span of 2016-2019, by using the Small BAseline Subset (SBAS) to process 119 S1-A/B data (descending mode). The groundwater level of Nineteen wells distributed over the Gotland island were used to assess the relationship between groundwater depletion and the detected InSAR displacement. In addition to that, the roles of other geological key factors such as soil depth, ground capacity in bed rock, karstification, structure of bedrock and soil type in occurring land subsidence also investigated. The findings showed that the groundwater level in thirteen wells with soil depths of less than 5 meters correlated well with InSAR displacements. The closeness of bedrock to ground surface (small soil depth) was responsible for high coherence values near the wells, and enabled the detection land subsidence. The results demonstrated that InSAR could use as an effective monitoring system for groundwater management and can assist in predicting or estimating low groundwater levels during summer conditions.</p>

Monitoring stability of embankment dams in response to 2019 Iran Flood event

2021 ◽  
Author(s):  
Mahmud Haghshenas Haghighi ◽  
Mahdi Motagh
Keyword(s):  
Time Series ◽  
Flood Event ◽  
Zagros Mountains ◽  
High Resolution Data ◽  
Khuzestan Province ◽  
Embankment Dams ◽  
Before And After ◽  
Small Baseline Subset ◽  
Small Baseline

<p>In April 2019, large parts of Khuzestan province in Iran were affected by intense record rainfall in the Zagros mountains. Persian Gulf catchment received approximately 30% of its long-term average rainfall over the course of a few days. Karkheh and Dez, two of the major rivers in this catchment, overflowed their banks. As several dams, including Karkheh, with the country's largest capacity, reached their limits, the water had to be released from the reservoirs, which resulted in flooding downstream of the dams. Several cities and more than 200 villages were flooded, and many people had to be evacuated. Many of the dams affected by the 2019 flood were embankment dams,  previously reported to exhibit post-construction settlements, at places reaching 13 cm/yr. Therefore, during and after the flood,  significant concerns were raised about their health and stability.</p><p>In this study, we use Sentinel-1 InSAR to monitor embankment dams' response in Khuzestan to the 2019 flood event. We process the full archive of Sentinel-1 using the Small Baseline Subset approach and estimate the time series of displacement for three different embankment dams in Khuzestan province. The first two studied dams are Karkheh and Gotvand, which have the country's largest capacities and became operational in 2001 and 2012, respectively. The third studied dam is the Masjed-Soleyman dam, previously reported to sustain a high displacement rate since its operation in 2002.</p><p>The Sentinel-1 InSAR displacement results indicate that all observed dams exhibit long-term post-construction settlement before the flood, with rates varies from approximately 1 cm/yr for the Karkheh dam to 5 cm/yr for Gotvand dam and 8 cm/yr for Masjed-Soleyman dam. The time series of displacement for Karkheh and Gotvand dams show gentle changes of displacement in response to the increase in water level following the flood. However, for the Masjed-Soleyman dam, the movement accelerates sharply after the flood with more than 2 cm of displacement on the crest in only two months. For the Masjed-Soleyman dam experiencing the most severe effect of the flood, we also analyzed high-resolution data from TerraSAR-X and COSMO-SkyMed. The results provide a detailed picture of the displacement pattern over the crest and the dam's body before and after the flood.</p>

scholarly journals The Joint Use of Multiple Satellite SAR Data and Geotechnical Models for the Study of the Shanghai Ocean-Reclaimed Lands

2016 ◽  
Author(s):  
Antonio Pepe ◽  
Manuela Bonano ◽  
Qing Zhao ◽  
Tianliang Yang ◽  
Hanmei Wang
Keyword(s):  
Temporal Evolution ◽  
Alluvial Deposits ◽  
Surface Displacements ◽  
Time Period ◽  
Small Baseline Subset ◽  
Dependent Model ◽  
Time Gap ◽  
Sar Data ◽  
Small Baseline

This paper is aimed at studying the temporal evolution of the surface displacements occurred over the past few years in the ocean-reclaimed platforms of the Shanghai megacity (China), which are mainly ascribable to consolidation processes of large dredger fills and alluvial deposits. With respect to previous analyses carried out over the same area, this work provides a joint multi-platform differential interferometry synthetic aperture radar (DInSAR) analysis, based on the application of the advanced Small BAseline Subset (SBAS) algorithm. This led us to retrieve long-term deformation time-series that are helpful for a better understanding of the on-going deformation phenomena. To this aim, we have exploited two sequences of SAR data collected by the ASAR/ENVISAT and by the COSMO-SkyMed (CSK) sensors, respectively, spanning the whole time period from 2007 to 2016. Unfortunately, the large time gap (of about three years) existing between the available ASAR/ENVISAT and CSK datasets gave rise to additional difficulties for their combination. Nevertheless, this problem has been faced by benefiting from the knowledge of a time-dependent model describing the temporal evolution of the expected deformations affecting the Shanghai ocean-reclaimed platforms.

scholarly journals LAND SUBSIDENCE MONITORING USING PS-InSAR TECHNIQUE FOR L-BAND SAR DATA

2016 ◽  
Vol XLI-B7 ◽  
pp. 995-997 ◽  
Author(s):  
S. Thapa ◽  
R. S. Chatterjee ◽  
K. B. Singh ◽  
D. Kumar
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Land Surface ◽  
Surface Deformation ◽  
Underground Mining ◽  
Ground Surface ◽  
Sar Interferometry ◽  
Persistent Scatterer Interferometry ◽  
Long Time ◽  
Subsidence Monitoring

Differential SAR-Interferometry (D-InSAR) is one of the potential source to measure land surface motion induced due to underground coal mining. However, this technique has many limitation such as atmospheric in homogeneities, spatial de-correlation, and temporal decorrelation. Persistent Scatterer Interferometry synthetic aperture radar (PS-InSAR) belongs to a family of time series InSAR technique, which utilizes the properties of some of the stable natural and anthropogenic targets which remain coherent over long time period. In this study PS-InSAR technique has been used to monitor land subsidence over selected location of Jharia Coal field which has been correlated with the ground levelling measurement. This time series deformation observed using PS InSAR helped us to understand the nature of the ground surface deformation due to underground mining activity.

scholarly journals Multitemporal and Multisensor InSAR Analysis for Ground Displacement Field Assessment at Ischia Volcanic Island (Italy)

2021 ◽  
Vol 13 (21) ◽  
pp. 4253
Author(s):  
Lisa Beccaro ◽  
Cristiano Tolomei ◽  
Roberto Gianardi ◽  
Vincenzo Sepe ◽  
Marina Bisson ◽  
...  
Keyword(s):  
Time Series ◽  
Vertical Displacement ◽  
Slope Instability ◽  
Time Interval ◽  
Ground Displacement ◽  
Ground Deformations ◽  
Field Assessment ◽  
Small Baseline Subset ◽  
Volcanic Islands ◽  
Small Baseline

Volcanic islands are often affected by ground displacement such as slope instability, due to their peculiar morphology. This is the case of Ischia Island (Naples, Italy) dominated by the Mt. Epomeo (787 m a.s.l.), a volcano-tectonic horst located in the central portion of the island. This study aims to follow a long temporal evolution of ground deformations on the island through the interferometric analysis of satellite SAR data. Different datasets, acquired during Envisat, COSMO-SkyMed and Sentinel-1 satellite missions, are for the first time processed in order to obtain the island ground deformations during a time interval spanning 17 years, from November 2002 to December 2019. In detail, the multitemporal differential interferometry technique, named small baseline subset, is applied to produce the ground displacement maps and the associated displacement time series. The results, validated through the analysis and the comparison with a set of GPS measurements, show that the northwestern side of Mt. Epomeo is the sector of the island characterized by the highest subsidence movements (maximum vertical displacement of 218 mm) with velocities ranging from 10 to 20 mm/yr. Finally, the displacement time series allow us to correlate the measured ground deformations with the seismic swarm started with the Mw 3.9 earthquake that occurred on 21 August 2017. Such correlations highlight an acceleration of the ground, following the mainshock, characterized by a subsidence displacement rate of 0.12 mm/day that returned to pre-earthquake levels (0.03 mm/day) after 6 months from the event.

Sign in / Sign up

Export Citation Format

Share Document