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.

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 KINEMATIC ANALYSIS EVOLUTION OF EXTENDED LANDSLIDES: TWO CASE STUDIES FROM WESTERN GREECE

2017 ◽  
Vol 50 (2) ◽  
pp. 730
Author(s):  
K. Kavoura ◽  
S. Anagnostopoulou ◽  
K. Servou ◽  
N. Depoundis ◽  
K. Nikolakopoulos ◽  
...  
Keyword(s):  
Statistical Model ◽  
Temporal Evolution ◽  
Data Normalization ◽  
Time Period ◽  
Long Time ◽  
Triggering Factor ◽  
The Common ◽  
Western Greece ◽  
Heavy Rainfalls

Two of the most well known historical landslide occurrences are analyzed and their temporal evolution is presented. The sites of Panagopoula and Karya are often referred as the most representative cases of long term ground displacements based on inclinometer monitoring data. Regarding these cases, the heavy rainfalls constitute the main controlling (triggering) factor, while flysch is the critical landslide-prone formation which significantly contributes to landsliding. The inclinometer data through a long time period were analyzed and typical movement diagrams were compiled. A simple statistical model including data normalization through several active stages (phases) of movement is used to identify the common kinematic features as well as to estimate the velocity trend type of movement.

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.

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).

scholarly journals Long-Term Land Subsidence Monitoring of Beijing (China) Using the Small Baseline Subset (SBAS) Technique

2014 ◽  
Vol 6 (5) ◽  
pp. 3648-3661 ◽  
Author(s):  
Bo Hu ◽  
Han-Sheng Wang ◽  
Yong-Ling Sun ◽  
Jian-Guo Hou ◽  
Jun Liang
Keyword(s):  
Land Subsidence ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
Subsidence Monitoring ◽  
Beijing China

The temporal evolution of wildfire ash and implications for post-fire infiltration

2014 ◽  
Vol 23 (5) ◽  
pp. 733 ◽  
Author(s):  
Victoria N. Balfour ◽  
Stefan H. Doerr ◽  
Peter R. Robichaud
Keyword(s):  
Forest Fires ◽  
Temporal Evolution ◽  
Fire Hazard ◽  
Effective Porosity ◽  
Short Term ◽  
Infiltration Capacity ◽  
Time Period ◽  
Ash Layer ◽  
Wind And Water Erosion

Changes in the properties of an ash layer with time may affect the amount of post-fire runoff, particularly by the formation of ash surface crusts. The formation of depositional crusts by ash have been observed at the pore and plot scales, but the causes and temporal evolution of ash layers and associated crusts have not yet been thoroughly investigated. In the long term, ash crusting effects will decrease as the ash layer is removed by wind and water erosion, but in the short term ash crusting could contribute to the observed changes in post-fire runoff. This research addresses these topics by studying the evolution over time of highly combusted ash layers from two high-severity wildfires that occurred in Montana in 2011. More specifically, this research was designed to assess the potential for ash crusts to form and thereby contribute to the observed decreases in infiltration after forest fires. Results indicate that high-combustion ash can evolve due to post-fire rainfall. Plots that exhibited a visible ash crust also displayed a significant decrease in effective porosity and hydraulic conductivity. These decreases in ash layer characteristics were attributed to raindrop compaction and ash hydration resulting in the formation of carbonate crystals, which decreased effective porosity and flow within the ash layer. During this same time period, inorganic carbon content more than doubled from 11 to 26% and bulk density significantly increased from 0.22 to 0.39gcm–3 on crusted plots. Although raindrop impact increased the robustness of the ash crust, mineralogical transformations must occur to produce a hydrologically relevant ash crust. These results indicate that post-fire rainfall is an important control on the properties of the ash layer after burning and on crust formation. The observed temporal changes indicate that the timing of ash sampling can alter the predictions as to whether the ash layer is effecting post-fire infiltration and runoff. Despite the reduction in infiltration capacity, the formation of post-fire ash crusts could prove beneficial to post-fire hazard mitigation by stabilising the ash layer, and reducing aeolian mixing and erosion.

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.

Stability and Change in Emotional Intelligence: Exploring the Transition to Young Adulthood

2005 ◽  
Vol 26 (2) ◽  
pp. 100-106 ◽  
Author(s):  
James D.A. Parker ◽  
Donald H. Saklofske ◽  
Laura M. Wood ◽  
Jennifer M. Eastabrook ◽  
Robyn N. Taylor
Keyword(s):  
High School ◽  
Emotional Intelligence ◽  
Postsecondary Education ◽  
Life Transition ◽  
Full Time ◽  
Major Life ◽  
Long Term Stability ◽  
Time Period ◽  
Transition From High School

Abstract. The concept of emotional intelligence (EI) has attracted growing interest from researchers working in various fields. The present study examined the long-term stability (32 months) of EI-related abilities over the course of a major life transition (the transition from high school to university). During the first week of full-time study, a large group of undergraduates completed the EQ-i:Short; 32 months later a random subset of these students (N = 238), who had started their postsecondary education within 24 months of graduating from high school, completed the measures for a second time. The study found EI scores to be relatively stable over the 32-month time period. EI scores were also found to be significantly higher at Time 2; the overall pattern of change in EI-levels was more than can be attributed to the increased age of the participants.

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