scholarly journals Analysis of the Deformation Behavior and Sinkhole Risk in Kerdabad, Iran Using the PS-InSAR Method

2021 ◽  
Vol 13 (14) ◽  
pp. 2696
Author(s):  
Mahdi Khoshlahjeh Azar ◽  
Amir Hamedpour ◽  
Yasser Maghsoudi ◽  
Daniele Perissin
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Human Life ◽  
Groundwater Depletion ◽  
Driving Mechanism ◽  
Radar Images ◽  
Persistent Scatterers ◽  
Gradual Process ◽  
Hamedan Province ◽  
The One

The unexpected collapse of land surface due to subsidence is one of the most significant geohazards that threatens human life and infrastructure. Kabudrahang and Famenin are two Iranian plains experiencing several sinkholes due to the characteristics of the underground soil layers and extreme groundwater depletion. In this study, space-based Synthetic Aperture Radar images are used to investigate the ground displacement behavior to examine the feasibility of Sentinel-1 data in detecting precursory deformation proceeding before the sinkhole formation. The selected sinkhole occurred in August 2018 in the vicinity of Kerdabad village in Hamedan province with a 40 m diameter and depth of ~40 m. Time series of the European constellation Sentinel-1 data, spanning from January 2015 to August 2018, is analyzed, and the results revealed a 3 cm annual subsidence (–3cm/year) along with the line-of-sight direction. Time-series analysis demonstrated that the driving mechanism of the sinkhole formation had a gradual process. Displacement of persistent scatterers (PSs) near the cave area had an acceleration by approaching the sinkhole formation date. In contrast, other areas that are far from the cave area show linear subsidence behavior over time. Additionally, the one-kilometer deformation profile over the cave area indicates a high subsidence rate precisely at the location where the sinkhole was formed later on 20 August 2018.

scholarly journals INSAR TIME SERIES INVESTIGATION OF LAND SURFACE DEFORMATION IN AZAR OIL FIELD

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 733-736
Author(s):  
Z. Mirzaii ◽  
M. Hasanlou ◽  
S. Samieie-Esfahany ◽  
M. Rojhani ◽  
P. Ajourlou
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Surface Deformation ◽  
Oil Extraction ◽  
Oil Field ◽  
Oil Exploration ◽  
Persistent Scatterer Interferometry ◽  
Maximum Displacement ◽  
Envisat Asar ◽  
Persistent Scatterers

Abstract. Time-series interferometric synthetic aperture radar (InSAR) has developed as an influential method to measure various surface deformations. One of the generations of time-series InSAR methodologies is Persistent Scatterer Interferometry (PSI) that focuses on targets with a high correlation over time. In this study, we have measured the surface deformation in Azar Oil Field utilizing time series analysis. Azar Oil Field is one of Iran's oil fields. This oil field is located in the east of the city of Mehran, Ilam province. The reservoir of this oil field is shared by Iraq oil field whose name is Badra where oil extraction started in 201409. While Iran started oil exploration in 201709, Iraq has maximized its oil exploration ever since. The subsidence is mainly observed in the vicinity of the oil field. The Stanford Method for Persistent Scatterers (StaMPS) package has been employed to process 20 descending ENVISAT-ASAR images collected between 2003 and 2009, as well as 50 descending Sentinel-1A satellite images collected between 2014 and 2019. Sentinel-1 images bring new improvements due to their wide coverage and high revisiting time, which allows us to make a wide area processing. Due to the high depth of oil wells (4,300 meters), as well as the stone type of the region’s bed in some areas, we needed to calculate the magnitude of subsidence. The results show the maximum displacement rate in this area is 18 mm between 2014 and 2019 in the radar line of sight direction, but no subsidence took place between 2003 and 2009 .The results of the study confirm typical patterns of subsidence induced by oil extraction. Also, since 2017, with the onset of Iran’s oil extraction and the intensification of Iraq's oil exploration, subsidence has taken place with a steeper slope. The displacement of the area before and after this date is modelled with two lines.

scholarly journals FUSION OF THE OPTICAL AND RADAR IMAGES OF THE LAND SURFACE IN MULTI-POSITION ON-BOARD SYSTEMS FOR OPERATIONAL MONITORING

2021 ◽  
Vol XLIV-2/W1-2021 ◽  
pp. 107-111
Author(s):  
I. G. Khanykov ◽  
V. A. Nenashev
Keyword(s):  
Land Surface ◽  
Human Life ◽  
Practical Significance ◽  
Operational Monitoring ◽  
Content Quality ◽  
Location System ◽  
Radar Images ◽  
Segmentation Methods ◽  
Spatially Distributed ◽  
Optical Location

Abstract. The issues of image fusion in a two-position small-size radar on-board operational monitoring system are considered. The aim of present research is to develop a method for fusion of images of the land surface based on data obtained from a multi-sensor spatially distributed on-board location system implemented on the basis of a UAV. The method of combining different-angle location images is implemented iteratively. At each iteration, there is a search for pairs of points of the contour of the isolated areas. Areas are highlighted using two image segmentation methods. The final result is a proposed method for information fusion from a two-position on-board small-sized radar system and an optical location system. The implemented method of fusion makes it possible to increase the information content, quality and reliability of information about the observed underlying surfaces and the physical objects detected on them. The practical significance of the results obtained lies in the formation of integral information in real time in the interests of environmental reconnaissance, monitoring in hard-to-reach and dangerous places for human life, as well as in order to promptly prevent natural and man-made emergencies.

Land Subsidence in Delhi, India investigated using Sentinel-1 InSAR measurements

2020 ◽  
Author(s):  
Shagun Garg ◽  
Mahdi Motagh ◽  
Indu Jayaluxmi
Keyword(s):  
Land Subsidence ◽  
Land Surface ◽  
Surface Deformation ◽  
Field Measurements ◽  
Groundwater Depletion ◽  
National Capital Region ◽  
Rapid Urbanization ◽  
In Situ Data ◽  
Persistent Scatterers ◽  
The Government

<p>Groundwater induced land subsidence is a growing problem worldwide and has been documented in places like Mexico, Jakarta, Tehran, and China. India is the largest user of groundwater and pumps more than the USA and China combined. The National capital region(NCR) of India, due to rapid urbanization and illegal extraction, is facing severe groundwater depletion of the order of 0.5m-2m per year and is declared as a critical zone by the government of India. The looming crisis of groundwater depletion and supporting hydrogeology makes this region prone to land surface deformation.</p><p>Monitoring subsidence by conventional methods such as extensometers, leveling, hydrogeology modeling, and GPS requires precise field measurements and are time-consuming. With the advent of Interferometry, monitoring deformation precisely from the microwave sensors onboard satellite is possible. In our study, we demonstrate the result of the Persistent Scatterer InSAR (PS-InSAR) technique to monitor the subsidence in the Delhi NCR region using Sentinel -1 Interferometric wide swath (IW) mode. Descending pass datasets are used to identify the PSs over the study area. Fifty-six differential interferograms from Aug 2016 to Sep 2018 are formed after removing flat earth and topographic phase using SRTM 30m DEM. The PS-InSAR processing is done using Stanford Method for Persistent Scatterers (StaMPS), where an amplitude threshold index of 0.4 is selected for Initial PS candidate. The PS points are the stable targets which do not decorrelate much over time.  The deformation is calculated for all these PS points and a time series, and hence a velocity map is formed.</p><p>The rate of deformation in Southwest Delhi is found to be approximately 15 cm/year (max) in the radar line of sight direction. The in-situ data provided by the Central groundwater board (CGWB) India is not consistent and has many gaps. However, after applying Spatio-temporal interpolation, it follows the decreasing trend of Land subsidence which suggests that the groundwater extraction is the major cause for the subsidence in the southwest region of NCR during the observed period i.e., from 2016 -2018.</p>

scholarly journals The extremely warm summer of 2018 in Sweden – set in a historical context

2020 ◽  
Vol 11 (4) ◽  
pp. 1107-1121
Author(s):  
Renate Anna Irma Wilcke ◽  
Erik Kjellström ◽  
Changgui Lin ◽  
Daniela Matei ◽  
Anders Moberg ◽  
...  
Keyword(s):  
Time Series ◽  
Climate Model ◽  
Human Life ◽  
Historical Context ◽  
Lower Probability ◽  
Warm Summer ◽  
Long Time ◽  
Climate Model Ensembles ◽  
Model Ensembles ◽  
The One

Abstract. Two long-lasting high-pressure systems in summer 2018 led to persisting heatwaves over Scandinavia and other parts of Europe and an extended summer period with devastating impacts on agriculture, infrastructure, and human life. We use five climate model ensembles and the unique 263-year-long Stockholm temperature time series along with a composite 150-year-long time series for the whole of Sweden to set the latest heatwave in the summer of 2018 into historical perspective. With 263 years of data, we are able to grasp the pre-industrial period well and see a clear upward trend in temperature as well as upward trends in five heatwave indicators. With five climate model ensembles providing 20 580 simulated summers representing the latest 70 years, we analyse the likelihood of such a heat event and how unusual the 2018 Swedish summer actually was. We find that conditions such as those observed in summer 2018 are present in all climate model ensembles. An exception is the monthly mean temperature for May for which 2018 was warmer than any member in one of the five climate model ensembles. However, even if the ensembles generally contain individual years like 2018, the comparison shows that such conditions are rare. For the indices assessed here, anomalies such as those observed in 2018 occur in a maximum of 5 % of the ensemble members, sometimes even in less than 1 %. For all of the indices evaluated, we find that the probability of a summer such as that in 2018 has increased from relatively low values in the pre-industrial era (1861–1890, one ensemble) and the recent past (1951–1980, all five ensembles) to higher values in the most recent decades (1989–2018). An implication of this is that anthropogenic climate change has strongly increased the probability of a warm summer, such as the one observed 2018, occurring in Sweden. Despite this, we still find such summers in the pre-industrial climate in our simulations, albeit with a lower probability.

scholarly journals Comparative Study of Groundwater-Induced Subsidence for London and Delhi Using PSInSAR

2021 ◽  
Vol 13 (23) ◽  
pp. 4741
Author(s):  
Vivek Agarwal ◽  
Amit Kumar ◽  
David Gee ◽  
Stephen Grebby ◽  
Rachel L. Gomes ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Land Surface ◽  
Groundwater Resources ◽  
Ground Level ◽  
Groundwater Depletion ◽  
Water Storage Capacity ◽  
Capital Cities ◽  
Groundwater Levels ◽  
Radar Images ◽  
Spatio Temporal

Groundwater variation can cause land-surface movement, which in turn can cause significant and recurrent harm to infrastructure and the water storage capacity of aquifers. The capital cities in the England (London) and India (Delhi) are witnessing an ever-increasing population that has resulted in excess pressure on groundwater resources. Thus, monitoring groundwater-induced land movement in both these cities is very important in terms of understanding the risk posed to assets. Here, Sentinel-1 C-band radar images and the persistent scatterer interferometric synthetic aperture radar (PSInSAR) methodology are used to study land movement for London and National Capital Territory (NCT)-Delhi from October 2016 to December 2020. The land movement velocities were found to vary between −24 and +24 mm/year for London and between −18 and +30 mm/year for NCT-Delhi. This land movement was compared with observed groundwater levels, and spatio-temporal variation of groundwater and land movement was studied in conjunction. It was broadly observed that the extraction of a large quantity of groundwater leads to land subsidence, whereas groundwater recharge leads to uplift. A mathematical model was used to quantify land subsidence/uplift which occurred due to groundwater depletion/rebound. This is the first study that compares C-band PSInSAR-derived land subsidence response to observed groundwater change for London and NCT-Delhi during this time-period. The results of this study could be helpful to examine the potential implications of ground-level movement on the resource management, safety, and economics of both these cities.

Detecting ground motion in Schleswig-Holstein from radar satellite data

2021 ◽  
Author(s):  
Dieter Hoogestraat ◽  
Henriette Sudhaus ◽  
Andreas Omlin
Keyword(s):  
Time Series ◽  
Ground Motion ◽  
Time Series Data ◽  
Ground Motions ◽  
Anthropogenic Sources ◽  
Series Data ◽  
Small Scale ◽  
Near Surface ◽  
Radar Images ◽  
Persistent Scatterers

<p>The near-surface geology of northern Germany is characterized by glacial deposits, deformed by rising Permian and Upper Triassic salt structures. Ground motions potentially associated with salt tectonic processes are very slow and are superimposed by signals of e.g. hydrological and anthropogenic sources. To measure them requires the detection of motion rates in the range of a few millimeters per year with sufficient spatial coverage. For large areas little is known about the rates and the characteristics of ground motions, even though they directly affect anthropogenic infrastructure and could have an impact on the future use of the underground for storage purposes or the exploitation of geothermal energy.</p><p>To measure ground motion, we use radar interferometric time series data provided by the German Aerospace Center and the Federal Institute for Geosciences and Natural Resources' Ground motion service. These data are based on Synthetic Aperture Radar images acquired by ESA's ERS and Sentinel satellites. Time-series analyses are possible for temporally stable backscattering objects (persistent scatterers) on the ground. Generally, this results in spatially dense observations over built-up areas and sparse observations over rural areas.</p><p>We use a set of geostatistical methods to analyze these time series data. We see signals of large-scale surface-deforming processes such as the subsidence of the marshes and small-scale signals like the swelling of Permian anhydrite at the Segeberger "Kalkberg". And we can observe subsidence processes over the historic town of Lübeck.</p><p>Our work extends the area of application of the PS-InSAR technique from areas with high motion rates to regions with particulary low motion rates. We discuss methods that can be used to link ERS data to the Sentinel-1 data, in particular, to separate long-term motion processes from short-term effects. We are working on techniques that shall help to decompose different signal sources. Finally, we aim to prepare a set of tools, that can be used by the community.</p>

scholarly journals Investigating Subsidence in the Bursa Plain, Turkey, Using Ascending and Descending Sentinel-1 Satellite Data

2019 ◽  
Vol 11 (1) ◽  
pp. 85 ◽  
Author(s):  
Gokhan Aslan ◽  
Ziyadin Cakir ◽  
Cécile Lasserre ◽  
François Renard
Keyword(s):  
Time Series ◽  
Water Pressure ◽  
Alluvial Fan ◽  
Ground Subsidence ◽  
Clear Correlation ◽  
Agricultural Activity ◽  
Marmara Region ◽  
Groundwater Exploitation ◽  
Radar Images ◽  
Persistent Scatterers

We characterize and monitor subsidence of the Bursa Plain (southern Marmara region of Turkey), which has been interpreted as resulting from tectonic motions in the region. We quantify the subsidence using Interferometric Synthetic Aperture Radar (InSAR) time-series analysis. The Stanford Method for Persistent Scatterers InSAR package (StaMPS) is employed to process series of Sentinel 1 A-B radar images acquired between 2014 and 2017 along both ascending and descending orbits. The vertical velocity field obtained after decomposition of line-of-sight velocity fields on the two tracks reveals that the Bursa plain is subsiding at rates up to 25 mm/yr. The most prominent subsidence signal in the basin forms an east-west elongated ellipse of deformation in the east, and is bounded by a Quaternary alluvial plain undergoing average vertical subsidence at ~10 mm/yr. Another localized subsidence signal is located 5 km north of the city, following the Bursa alluvial fan, and is subsiding at velocities up to 25 mm/yr. The comparison between temporal variations of the subsiding surface displacements and variations of the water pressure head in the aquifer allows estimation of the compressibility of the aquifer, α . It falls in the range of 0.5 × 10 − 6 − 2 × 10 − 6 Pa−1, which corresponds to typical values for clay and sand sediments. We find a clear correlation between subsidence patterns and the lithology, suggesting a strong lithological control over subsidence. In addition, the maximum rate of ground subsidence occurs where agricultural activity relies on groundwater exploitation. The InSAR time series within the observation period is well correlated with changes in the depth of the ground water. These observations indicate that the recent acceleration of subsidence is mainly due to anthropogenic activities rather than tectonic motion.

scholarly journals The extremely warm summer 2018 in Sweden – set in a historical context

2020 ◽  
Author(s):  
Renate A. I. Wilcke ◽  
Erik Kjellström ◽  
Changgui Lin ◽  
Daniela Matei ◽  
Anders Moberg
Keyword(s):  
Time Series ◽  
Heat Wave ◽  
Climate Model ◽  
Heat Waves ◽  
Human Life ◽  
Lower Probability ◽  
Warm Summer ◽  
Climate Model Ensembles ◽  
Model Ensembles ◽  
The One

Abstract. Two long-lasting high pressure systems in summer 2018 lead to long lasting heat waves over Scandinavia and other parts of Europe and an extended summer period with devastating impacts on agriculture, infrastructure and human life. We use five climate model ensembles and the unique 263 year long Stockholm temperature time series along with a composite 150 year long time series for whole Sweden to set the latest heat-wave in summer 2018 in historical perspective. With 263 years we are able to grasp the pre-industrial time well and see a clear upward trend in temperature itself as well as heat wave indicators. With five climate model ensembles providing 20 580 simulated summers representing the latest 70 years, we analyse the likelihood of such a heat event and how unusual the 2018 Swedish summer actually was. We find that conditions as those observed in summer 2018 show up in all climate model ensembles. An exception is the monthly mean temperature for May for which 2018 was warmer than any member in one of the five climate model ensembles. However, even if the ensembles generally hold individual years like 2018, the comparison shows that such conditions are rare. For the indices assessed here, anomalies such as observed in 2018 occur maximally in 5 % of the ensemble members, sometimes even in less than 1 %. For all indices evaluated we find that probabilities of a summer like in 2018 have increased from relatively low values for the one ensemble extending back to 1861–90 and for all five ensembles including 1951–80 to the most recent decades (1989–2018). An implication is that anthropogenic climate change has strongly increased the probability of a warm summer such as the one observed 2018 to occur in Sweden. Despite this, we still find such summers also in the pre-industrial climate, however, with a lower probability.

Persistent Scatterer Interferometry for Pettimudi (India) Landslide Monitoring using Sentinel-1A Images

2021 ◽  
Vol 87 (11) ◽  
pp. 853-862
Author(s):  
Hari Shankar ◽  
Arijit Roy ◽  
Prakash Chauhan
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Early Warning Systems ◽  
Landslide Monitoring ◽  
Surface Movement ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
Landslide Event ◽  
The Mean ◽  
Over Time

The continuous monitoring of land surface movement over time is of paramount importance for assessing landslide triggering factors and mitigating landslide hazards. This research focuses on measuring horizontal and vertical surface displacement due to a devastating landslide event in the west-facing slope of the Rajamala Hills, induced by intense rainfall. The landslide occurred in Pettimudi, a tea-plantation village of the Idukki district in Kerala, India, on August 6–7, 2020. The persistent-scatterer synthetic aperture radar interferometry (PSInSAR ) technique, along with the Stanford Method for Persistent Scatterers (StaMPS), was applied to investigate the land surface movement over time. A stack of 20 Sentinel-1A single-look complex images (19 interferograms) acquired in descending passes was used for PSInSAR processing. The line-of-sight (LOS ) displacement in long time series, and hence the average LOS velocity, was measured at each measurement-point location. The mean LOS velocity was decomposed into horizontal east–west (EW ) and vertical up–down velocity components. The results show that the mean LOS, EW, and up–down velocities in the study area, respectively, range from –18.76 to +11.88, –10.95 to +6.93, and –15.05 to +9.53 mm/y, and the LOS displacement ranges from –19.60 to +19.59 mm. The displacement values clearly indicate the instability of the terrain. The time-series LOS displacement trends derived from the applied PSInSAR technique are very useful for providing valuable inputs for disaster management and the development of disaster early-warning systems for the benefit of local residents.

scholarly journals Monitoring ground subsidence in urban environments: M-30 tunnels under Madrid City (Spain)

2015 ◽  
Vol 35 (2) ◽  
pp. 30-35 ◽  
Author(s):  
Rubén Martínez Marín ◽  
Eleanor Sillerico ◽  
Pablo Ezquerro ◽  
Miguel Marchamalo ◽  
Gerardo Herrera ◽  
...  
Keyword(s):  
Time Series ◽  
Spatial Distribution ◽  
Temporal Dynamics ◽  
Temporal Analysis ◽  
Urban Environments ◽  
Added Value ◽  
Ground Subsidence ◽  
Cross Sectional ◽  
Radar Images ◽  
Persistent Scatterers

Big cities improvement usually requires the construction of large underground infrastructures, in order to ensure proper communication and optimize urban use. Monitoring ground subsidences is therefore one of the main challenges in changing urban environments. The "Madrid Río" project (2003-2008) is an effort to reclaim the riverfront land and improve the busy M-30 beltway that involved the construction of 7.93 km of tunnels underneath the southern center of Madrid City. This paper presents a remote-sensing approach to monitor ground subsidences induced by tunneling excavation.  The Persistent Scatterers Interferometry technique (PSI) was used to estimate subsidence and displacement time series from Synthetic Aperture Radar images, acquired between August 2003 and April 2008 from ENVISAT.  Remote sensed results were compared to traditional extensometric measures, fitting adequately for selected sectors. Spatial analysis of displacements allowed evaluating impacts of tunneling on surrounding buildings and facilities, highlighting critical areas. The availability of a spatial distribution of displacements in a time series allowed analyzing longitudinal, cross-sectional and temporal dynamics. The main limitations during this work were the heterogeneous spatial distribution of Persistent Scatterers, the absence of measurement points in work areas, the threshold for velocity detection and low temporal resolution of ENVISAT images. Nevertheless, these limitations of DInSAR for monitoring infrastructures are overcome by actual satellites, being a complementary technique with an exceptional added value and temporal analysis capability.

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