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.

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.

scholarly journals ANALYSIS OF THE TREND OF THE DEFORMATION AROUND KANTO REGION ESTIMATED BY TIME SERIES OF PALSAR-2 DATA

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 287-291
Author(s):  
T. Nonaka ◽  
T. Asaka ◽  
K. Iwashita ◽  
F. Ogushi
Keyword(s):  
Time Series ◽  
Natural Gas ◽  
Urban Areas ◽  
Large Scale ◽  
Maximum Displacement ◽  
Gas Field ◽  
Small Baseline Subset ◽  
Large Scale Land ◽  
Small Baseline ◽  
Kanto Region

<p><strong>Abstract.</strong> The South Kanto gas field contains natural gas dissolved in water. In the past, large-scale land subsidence has occurred due to the extraction of this natural gas. Therefore, continuous and accurate monitoring for subsidence using satellite remote sensing is essential to prevent any extreme subsidence events, particularly in urban areas, and ensure the safety of residences. In this study, we adopted the small baseline subset (SBAS) method to understand the subsidence trend. We used Advanced Land Observing Satellite (ALOS)-2 Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) data from 2015 to 2019 for this purpose. The results show that the maximum displacement around the Kujyukuri area is more than 10 mm/year and the mean displacement rate for 2015 to 2019 is -1.4 ± 3.2 mm/year; this value is not as large as some obtained with past PALSAR observations. Comparison of our results with PALSAR observations shows that the number of distributed targets is fewer and the root mean square error of each time-series displacement value is larger. Further quantitative analysis is required to discuss the reliability of the SBAS-derived displacement rates by PALSAR-2.</p>

scholarly journals Method Combining Probability Integration Model and a Small Baseline Subset for Time Series Monitoring of Mining Subsidence

2018 ◽  
Vol 10 (9) ◽  
pp. 1444 ◽  
Author(s):  
Hongdong Fan ◽  
Lu Lu ◽  
Yahui Yao
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Deformation Gradient ◽  
Mining Area ◽  
Mining Subsidence ◽  
Interferometric Synthetic Aperture Radar ◽  
Integration Model ◽  
Small Baseline Subset ◽  
Maximum Subsidence ◽  
Small Baseline

Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) has high accuracy for monitoring slow surface subsidence. However, in the case of a large-scale mining subsidence areas, the monitoring capabilities of TS-InSAR are poor, owing to temporal and spatial decorrelation. To monitor mining subsidence effectively, a method known as Probability Integration Model Small Baseline Set (PIM-SBAS) was applied. In this method, mining subsidence with a large deformation gradient was simulated by a PIM. After simulated deformation was transformed into a wrapped phase, the residual wrapped phase was obtained by subtracting the simulated wrapped phase from the actual wrapped phase. SBAS was used to calculate the residual subsidence. Finally, the mining subsidence was determined by adding the simulated deformation to the residual subsidence. The time series subsidence of the Nantun mining area was derived from 10 TerraSAR-X (TSX) images for the period 25 December 2011 to 2 April 2012. The Zouji highway above the 9308 workface was the target for study. The calculated maximum mining subsidence was 860 mm. The maximum subsidence for the Zouji highway was about 145 mm. Compared with the SBAS method, PIM-SBAS alleviates the difficulty of phase unwrapping, and may be used to monitor large-scale mining subsidence.

scholarly journals Subsidence Monitoring of Fill Area in Yan’an New District Based on Sentinel-1A Time Series Imagery

2021 ◽  
Vol 13 (15) ◽  
pp. 3044
Author(s):  
Mingjie Liao ◽  
Rui Zhang ◽  
Jichao Lv ◽  
Bin Yu ◽  
Jiatai Pang ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Ground Deformation ◽  
Dynamic Change ◽  
Deformation Monitoring ◽  
Chinese Loess Plateau ◽  
Ground Subsidence ◽  
Shanxi Province ◽  
Environment Change ◽  
Loess Area

In recent years, many cities in the Chinese loess plateau (especially in Shanxi province) have encountered ground subsidence problems due to the construction of underground projects and the exploitation of underground resources. With the completion of the world’s largest geotechnical project, called “mountain excavation and city construction,” in a collapsible loess area, the Yan’an city also appeared to have uneven ground subsidence. To obtain the spatial distribution characteristics and the time-series evolution trend of the subsidence, we selected Yan’an New District (YAND) as the specific study area and presented an improved time-series InSAR (TS-InSAR) method for experimental research. Based on 89 Sentinel-1A images collected between December 2017 to December 2020, we conducted comprehensive research and analysis on the spatial and temporal evolution of surface subsidence in YAND. The monitoring results showed that the YAND is relatively stable in general, with deformation rates mainly in the range of −10 to 10 mm/yr. However, three significant subsidence funnels existed in the fill area, with a maximum subsidence rate of 100 mm/yr. From 2017 to 2020, the subsidence funnels enlarged, and their subsidence rates accelerated. Further analysis proved that the main factors induced the severe ground subsidence in the study area, including the compressibility and collapsibility of loess, rapid urban construction, geological environment change, traffic circulation load, and dynamic change of groundwater. The experimental results indicated that the improved TS-InSAR method is adaptive to monitoring uneven subsidence of deep loess area. Moreover, related data and information would provide reference to the large-scale ground deformation monitoring and in similar loess areas.

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

&lt;p&gt;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, &amp;#160;previously reported to exhibit post-construction settlements, at places reaching 13 cm/yr. Therefore, during and after the flood,&amp;#160; significant concerns were raised about their health and stability.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

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 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 GROUND DEFORMATION MONITORING IN QINGDAO COASTAL AREAS BY TIME-SERIES TERRASAR-X IMAGES

2016 ◽  
Vol XLI-B7 ◽  
pp. 29-33
Author(s):  
A. Y. Hou ◽  
X. Qiao ◽  
D. Li
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Ground Deformation ◽  
Small Deformation ◽  
Coastal Areas ◽  
Deformation Monitoring ◽  
Rate Of Change ◽  
Short Period ◽  
Radar Satellite ◽  
Ground Deformation Monitoring

As a new generation of high resolution and short revisit period of radar satellite, TerraSAR-X is not only able to meet the requirements of monitoring large scale surface subsidence, but also make it possible to monitor the small deformation of the short period. This articles takes the coastal areas of the west coast of Qingdao as the research object. With Small baselines subsets interferometry synthetic aperture radar (SBASI), this paper obtained the period the average annual rate of change from the time series analysis of TerraSAR-X data from April 2015 to October 2014.In order to enrich the historical deformation data of the study area, it analyse the time series of ALOS images from December 2010 to October 2008 with the same method. Finally,it analyse and demonstrate the experimental results.

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.

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