scholarly journals Assessment of Mitigation Strategies for Tropospheric Phase Contributions to InSAR Time-Series Datasets over Two Nicaraguan Volcanoes

2020 ◽  
Vol 12 (5) ◽  
pp. 782 ◽  
Author(s):  
Kirsten J. Stephens ◽  
Christelle Wauthier ◽  
Rebecca C. Bussard ◽  
Machel Higgins ◽  
Peter C. LaFemina
Keyword(s):  
Time Series ◽  
Correction Method ◽  
Mitigation Strategies ◽  
Ground Displacement ◽  
Tropical Regions ◽  
Different Types ◽  
Linear Correction ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
The Individual

Interferometric Synthetic Aperture Radar (InSAR) studies of ground displacement are often plagued by tropospheric artifacts, which are phase delays resulting from spatiotemporal variations in the refractivity of air within the troposphere. In this study, we focus on COSMO-SkyMed (X-band) InSAR products obtained over two different types of volcanoes in Nicaragua: the Telica stratovolcano and the Masaya caldera. We examine the applicability of an empirical linear correction method and three Global Weather Models (GWMs) with different spatial and temporal resolutions for removing the tropospheric phase component. We linearly invert the tropospheric-corrected interferograms using the Small BAseline Subset (SBAS) time-series technique to produce time-series of ground displacement. Statistical assessments were performed on the corrected interferograms to examine the significance of the applied corrections on the individual interferograms and time-series results. We find that the applicability of the correction methods is highly case-dependent and that in general, the temporal resolution of GWMs influences their ability to capture turbulent tropospheric phase delays. At the two target volcanoes, our study shows that none of the GWMs are able to accurately capture the tropospheric phase delays. Our study provides a guide for researchers using InSAR data in tropical regions who wish to use tropospheric model corrections to carefully assess the applicability of the different types of tropospheric correction methods.

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.

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 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

scholarly journals APPLICATION OF TIME SERIES INSAR TECHNIQUE FOR DEFORMATION MONITORING OF LARGE-SCALE LANDSLIDES IN MOUNTAINOUS AREAS OF WESTERN CHINA

2016 ◽  
Vol XLI-B1 ◽  
pp. 89-91
Author(s):  
T. Qu ◽  
P. Lu ◽  
C. Liu ◽  
H. Wan
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Deformation Monitoring ◽  
In Situ Monitoring ◽  
Western China ◽  
Surface Displacements ◽  
Landslide Hazards ◽  
Landslide Body ◽  
Small Baseline Subset ◽  
Small Baseline

Western China is very susceptible to landslide hazards. As a result, landslide detection and early warning are of great importance. This work employs the SBAS (Small Baseline Subset) InSAR Technique for detection and monitoring of large-scale landslides that occurred in Li County, Sichuan Province, Western China. The time series INSAR is performed using descending scenes acquired from TerraSAR-X StripMap mode since 2014 to get the spatial distribution of surface displacements of this giant landslide. The time series results identify the distinct deformation zone on the landslide body with a rate of up to 150mm/yr. The deformation acquired by SBAS technique is validated by inclinometers from diverse boreholes of in-situ monitoring. The integration of InSAR time series displacements and ground-based monitoring data helps to provide reliable data support for the forecasting and monitoring of largescale landslide.

TIME-SERIES SAR INTERFEROMETRY ANALYSIS OF SURFACE DEFORMATION AT MT. BROMO INDONESIA

2019 ◽  
Vol 3 ◽  
pp. 771
Author(s):  
Arliandy Pratama Arbad ◽  
Wataru Takeuchi ◽  
Yosuke Yosuke ◽  
Mutiara Jamilah ◽  
Achmad Ardy
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Sar Interferometry ◽  
Time Interval ◽  
Infrastructure Management ◽  
Alos Palsar ◽  
Volcanic System ◽  
Deformation Velocity ◽  
Small Baseline Subset ◽  
Small Baseline

One of the most active volcanoes in Indonesia is Mt. Bromo, volcanic activities at Mt. Bromo has been recorded in 1775. We observe the surface deformation of the Mt. Bromo which located at eastern Java Indonesia area that includes neighborhood volcanic system on TNBTS (Taman Nasional Bukit Tengger Semeru). Recently, remote sensing has played as an important role to observe volcano behavior. We apply the SAR Interferometry (InSAR) algorithm referred to as Small Baseline Subset (SBAS) approach that allows us to generate mean deformation velocity maps and displacement time series for the studied area. The common SBAS technique, the set of interferometric phase observations writes as a linear combination of individual SAR scene phase values for each pixel independently. Particularly, the proposed analysis is based on 22 SAR data acquired by the ALOS/PALSAR sensors during the 2007–2017 time interval. A fewer studies have been able to show capability of InSAR analysis for investigating cycle of volcano especially of Mt. Bromo which characterized eruption stratovolcano in ranging one to five years. The results expected in this work represent an advancement of previous InSAR studies of the area that are mostly focused on the deformation affecting the caldera. According to the result, we expected this study could implement on risk management or infrastructure management.

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>

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).

Sign in / Sign up

Export Citation Format

Share Document