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 CONCEPT TO ANALYZE THE DISPLACEMENT TIME SERIES OF INDIVIDUAL PERSISTENT SCATTERERS

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 147-154
Author(s):  
M. Evers ◽  
A. Thiele ◽  
H. Hammer ◽  
E. Cadario ◽  
K. Schulz ◽  
...  
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Piecewise Linear ◽  
Deformation Pattern ◽  
Mean Velocity ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
The Mean

Abstract. Persistent Scatterer Interferometry (PSInSAR) exploits a time series of Synthetic Aperture Radar (SAR) images to estimate the mean velocity with which the surface of the earth is deforming. However, most PSInSAR algorithms estimate the mean velocities using a linear regression model. Since some deformation phenomena can exhibit a more complex behavior over time, using a linear regression model leads to potentially wrong estimations for the mean velocity. For example, the velocity of a landslide moving down a steep slope can change depending on the water content of the material of the landslide, or an inactive landslide can reactivate due to an earthquake. Both scenarios would not result in a time series with a constant linear slope but in a piecewise linear time series.This paper presents a Matlab-based tool to analyze an individual Persistent Scatterer (PS) time series. The Persistent Scatterer Deformation Pattern Analysis Tool (PSDefoPAT) aims to build a mathematical model that sufficiently describes the time series trend and seasonal and noise components. The trend component is estimated using polynomial regression and piecewise linear models, while a sine function approximates the seasonal component. The goal is to identify the best fitting model for the displacement time series of a PS. PSDefoPAT is introduced by examine the time series of three different PS located in the region surrounding Patras, Greece. Based on the derived models, we discuss the nature of their deformation patterns.

scholarly journals InSAR Greece with Parallelized Persistent Scatterer Interferometry: A National Ground Motion Service for Big Copernicus Sentinel-1 Data

2020 ◽  
Vol 12 (19) ◽  
pp. 3207
Author(s):  
Ioannis Papoutsis ◽  
Charalampos Kontoes ◽  
Stavroula Alatza ◽  
Alexis Apostolakis ◽  
Constantinos Loupasakis
Keyword(s):  
Time Series ◽  
Ground Motion ◽  
Large Scale ◽  
Persistent Scatterer Interferometry ◽  
Persistent Scatterers ◽  
Processing Chain ◽  
Persistent Scatterer ◽  
Basin Scale ◽  
Wide Range ◽  
The Impact

Advances in synthetic aperture radar (SAR) interferometry have enabled the seamless monitoring of the Earth’s crust deformation. The dense archive of the Sentinel-1 Copernicus mission provides unprecedented spatial and temporal coverage; however, time-series analysis of such big data volumes requires high computational efficiency. We present a parallelized-PSI (P-PSI), a novel, parallelized, and end-to-end processing chain for the fully automated assessment of line-of-sight ground velocities through persistent scatterer interferometry (PSI), tailored to scale to the vast multitemporal archive of Sentinel-1 data. P-PSI is designed to transparently access different and complementary Sentinel-1 repositories, and download the appropriate datasets for PSI. To make it efficient for large-scale applications, we re-engineered and parallelized interferogram creation and multitemporal interferometric processing, and introduced distributed implementations to best use computing cores and provide resourceful storage management. We propose a new algorithm to further enhance the processing efficiency, which establishes a non-uniform patch grid considering land use, based on the expected number of persistent scatterers. P-PSI achieves an overall speed-up by a factor of five for a full Sentinel-1 frame for processing in a 20-core server. The processing chain is tested on a large-scale project to calculate and monitor deformation patterns over the entire extent of the Greek territory—our own Interferometric SAR (InSAR) Greece project. Time-series InSAR analysis was performed on volumes of about 12 TB input data corresponding to more than 760 Single Look Complex Sentinel-1A and B images mostly covering mainland Greece in the period of 2015–2019. InSAR Greece provides detailed ground motion information on more than 12 million distinct locations, providing completely new insights into the impact of geophysical and anthropogenic activities at this geographic scale. This new information is critical to enhancing our understanding of the underlying mechanisms, providing valuable input into risk assessment models. We showcase this through the identification of various characteristic geohazard locations in Greece and discuss their criticality. The selected geohazard locations, among a thousand, cover a wide range of catastrophic events including landslides, land subsidence, and structural failures of various scales, ranging from a few hundredths of square meters up to the basin scale. The study enriches the large catalog of geophysical related phenomena maintained by the GeObservatory portal of the Center of Earth Observation Research and Satellite Remote Sensing BEYOND of the National Observatory of Athens for the opening of new knowledge to the wider scientific community.

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 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 Detecting and Analyzing the Evolution of Subsidence Due to Coal Fires in Jharia Coalfield, India Using Sentinel-1 SAR Data

2021 ◽  
Vol 13 (8) ◽  
pp. 1521
Author(s):  
Moidu Jameela Riyas ◽  
Tajdarul Hassan Syed ◽  
Hrishikesh Kumar ◽  
Claudia Kuenzer
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Surface Deformation ◽  
Early Warning Systems ◽  
Temporal Variations ◽  
Landsat 8 ◽  
Jharia Coalfield ◽  
Field Evidence ◽  
Coal Fires ◽  
Sar Data

Public safety and socio-economic development of the Jharia coalfield (JCF) in India is critically dependent on precise monitoring and comprehensive understanding of coal fires, which have been burning underneath for more than a century. This study utilizes New-Small BAseline Subset (N-SBAS) technique to compute surface deformation time series for 2017–2020 to characterize the spatiotemporal dynamics of coal fires in JCF. The line-of-sight (LOS) surface deformation estimated from ascending and descending Sentinel-1 SAR data are subsequently decomposed to derive precise vertical subsidence estimates. The most prominent subsidence (~22 cm) is observed in Kusunda colliery. The subsidence regions also correspond well with the Landsat-8 based thermal anomaly map and field evidence. Subsequently, the vertical surface deformation time-series is analyzed to characterize temporal variations within the 9.5 km2 area of coal fires. Results reveal that nearly 10% of the coal fire area is newly formed, while 73% persisted throughout the study period. Vulnerability analyses performed in terms of the susceptibility of the population to land surface collapse demonstrate that Tisra, Chhatatanr, and Sijua are the most vulnerable towns. Our results provide critical information for developing early warning systems and remediation strategies.

scholarly journals Persistent Scatterer SAR Interferometry (PSI) for Airport Runways monitoring

2020 ◽  
Author(s):  
Luca Bianchini Ciampoli ◽  
Valerio Gagliardi ◽  
Fabio Tosti ◽  
Alessandro Calvi ◽  
Andrea Benedetto
Keyword(s):  
Time Series ◽  
Sar Interferometry ◽  
Transport Infrastructure ◽  
Image Stack ◽  
Subsidence Rate ◽  
Natural Neighbor ◽  
Persistent Scatterer ◽  
Deformation Velocity ◽  
Permanent Scatterers ◽  
The Mean

<p>In the last decades, monitoring the regional-scale deformation of international airports has become a priority, in order to ensure the highest operational security and safety standards. Within this context, among the most innovative and suitable techniques for transport infrastructures monitoring purpose, Persistent Scatterer SAR Interferometry (PSI) technology has proven to be an effective technique to investigate ground deformations [1-3].</p><p>However, the application of PSI to effectively and continuously monitor settlement in airports is an open challenge. In this study, a long time-series analysis of a high-resolution COSMO-Skymed satellite image-stack, acquired from September 2011 to October 2019, was collected and processed by PSI technique to retrieve the mean deformation velocity and time series of surface deformation of the runways of Leonardo Da Vinci-International Airport.</p><p>The mean PS velocity information is compared to the ground-based levelling-data, collected on the runway using a total station, in order to validate and increase the feasibility of the monitoring processing.</p><p>Finally, various Deformation maps using the Natural Neighbor Geostatistical interpolation algorithm [4], were created and demonstrated a maximum subsidence rate is up to 15.3 mm/yr during the investigated period. The results confirmed the well-known major down-lifting phenomenon over an area, which has undergone routine maintenance.</p><p>Results have demonstrated the viability of integrating InSAR and topographical in-situ survey methods, paving the way to future implementations in prioritizing maintenance activities and helping for decision-making to have a comprehensive and inclusive information data system for the investigation of survey sites.</p><p>The research is supported by the Italian Ministry of Education, University and Research under the National Project “Extended resilience analysis of transport networks (EXTRA TN): Towards a simultaneously space, aerial and ground sensed infrastructure for risks prevention”, PRIN 2017, Prot. 20179BP4SM</p><p> </p><p>[1] Bianchini Ciampoli, L., Gagliardi, V., Clementini, C. et al. Transport Infrastructure Monitoring by InSAR and GPR Data Fusion. Surv Geophys (2019). https://doi.org/10.1007/s10712-019-09563-7</p><p>[2] Ferretti, A., Prati, C., Rocca, F., 2000. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Trans. Geosci. 38 (5), 2202–2212. https://doi.org/10.1109/36.868878.</p><p>[3] Ferretti, A., Prati, C., Rocca, F.,2001. Permanent scatterers in SAR interferometry. IEEE Trans. Geosci. Remote Sens. 2001, 39, 8–20.</p><p>[4] Sibson, R. (1981). "A brief description of natural neighbor interpolation (Chapter 2)". In V. Barnett (ed.). Interpolating Multivariate Data. Chichester: John Wiley. pp. 21–36.</p>

scholarly journals Landslide Mapping and Monitoring Using Persistent Scatterer Interferometry (PSI) Technique in the French Alps

2020 ◽  
Vol 12 (8) ◽  
pp. 1305 ◽  
Author(s):  
Gokhan Aslan ◽  
Michael Foumelis ◽  
Daniel Raucoules ◽  
Marcello De Michele ◽  
Severine Bernardie ◽  
...  
Keyword(s):  
Regional Scale ◽  
In Situ Monitoring ◽  
Landslide Monitoring ◽  
Persistent Scatterer Interferometry ◽  
French Alps ◽  
Kinematic Evolution ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
Slow Moving ◽  
State Of Activity

Continuous geodetic measurements in landslide prone regions are necessary to avoid disasters and better understand the spatiotemporal and kinematic evolution of landslides. The detection and characterization of landslides in high alpine environments remains a challenge associated with difficult accessibility, extensive coverage, limitations of available techniques, and the complex nature of landslide process. Recent studies using space-based observations and especially Persistent Scatterer Interferometry (PSI) techniques with the integration of in-situ monitoring instrumentation are providing vital information for an actual landslide monitoring. In the present study, the Stanford Method for Persistent Scatterers InSAR package (StaMPS) is employed to process the series of Sentinel 1-A and 1-B Synthetic Aperture Radar (SAR) images acquired between 2015 and 2019 along ascending and descending orbits for the selected area in the French Alps. We applied the proposed approach, based on extraction of Active Deformation Areas (ADA), to automatically detect and assess the state of activity and the intensity of the suspected slow-moving landslides in the study area. We illustrated the potential of Sentinel-1 data with the aim of detecting regions of relatively low motion rates that be can attributed to activate landslide and updated pre-existing national landslide inventory maps on a regional scale in terms of slow moving landslides. Our results are compared to pre-existing landslide inventories. More than 100 unknown slow-moving landslides, their spatial pattern, deformation rate, state of activity, as well as orientation are successfully identified over an area of 4000 km2 located in the French Alps. We also address the current limitations due the nature of PSI and geometric characteristic of InSAR data for measuring slope movements in mountainous environments like Alps.

scholarly journals Vegetation Phenology Influenced by Rapid Urbanization of The Yangtze Delta Region

2020 ◽  
Vol 12 (11) ◽  
pp. 1783 ◽  
Author(s):  
Haiyong Ding ◽  
Luming Xu ◽  
Andrew J. Elmore ◽  
Yuli Shi
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Phenology ◽  
Rapid Urbanization ◽  
Spring Phenology ◽  
Surface Temperatures ◽  
Land Surface Temperatures ◽  
Over Time

Impacts of urbanization and climate change on ecosystems are widely studied, but these drivers of change are often difficult to isolate from each other and interactions are complicated. Ecosystem responses to each of these drivers are perhaps most clearly seen in phenology changes due to global climate change (warming climate) and urbanization (heat island effect). The phenology of vegetation can influence many important ecological processes, including primary production, evapotranspiration, and plant fitness. Therefore, evaluating the interacting effects of urbanization and climate change on vegetation phenology has the potential to provide information about the long-term impact of global change. Using remotely sensed time series of vegetation on the Yangtze River Delta in China, this study evaluated the impacts of rapid urbanization and climate change on vegetation phenology along an urban to rural gradient over time. Phenology markers were extracted annually from an 18-year time series by fitting the asymmetric Gaussian function model. Thermal remote sensing acquired at daytime and nighttime was used to explore the relationship between land surface temperature and vegetation phenology. On average, the spring phenology marker was 9.6 days earlier and the autumn marker was 6.63 days later in urban areas compared with rural areas. The spring phenology of urban areas advanced and the autumn phenology delayed over time. Across space and time, warmer spring daytime and nighttime land surface temperatures were related to earlier spring, while autumn daytime and nighttime land surface temperatures were related to later autumn phenology. These results suggest that urbanization, through surface warming, compounds the effect of climate change on vegetation phenology.

Der Sommer und Herbst 2003 aus phänologischer Sicht | Summer and autumn 2003 from a phenological point of view

2004 ◽  
Vol 155 (5) ◽  
pp. 142-145 ◽  
Author(s):  
Claudio Defila
Keyword(s):  
Time Series ◽  
New Record ◽  
Point Of View ◽  
Late Spring ◽  
Mean Deviation ◽  
Leaf Shedding ◽  
The Mean ◽  
Very High ◽  
Selection Of

The record-breaking heatwave of 2003 also had an impact on the vegetation in Switzerland. To examine its influences seven phenological late spring and summer phases were evaluated together with six phases in the autumn from a selection of stations. 30% of the 122 chosen phenological time series in late spring and summer phases set a new record (earliest arrival). The proportion of very early arrivals is very high and the mean deviation from the norm is between 10 and 20 days. The situation was less extreme in autumn, where 20% of the 103 time series chosen set a new record. The majority of the phenological arrivals were found in the class «normal» but the class«very early» is still well represented. The mean precocity lies between five and twenty days. As far as the leaf shedding of the beech is concerned, there was even a slight delay of around six days. The evaluation serves to show that the heatwave of 2003 strongly influenced the phenological events of summer and spring.

scholarly journals The influence of solar wind on extratropical cyclones – Part 1: Wilcox effect revisited

2009 ◽  
Vol 27 (1) ◽  
pp. 1-30 ◽  
Author(s):  
P. Prikryl ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Time Series ◽  
Solar Wind ◽  
Northern Hemisphere ◽  
High Speed ◽  
Coronal Holes ◽  
Extratropical Cyclones ◽  
Sector Boundary ◽  
Speed Solar Wind ◽  
The Mean ◽  
High Speed Solar Wind

Abstract. A sun-weather correlation, namely the link between solar magnetic sector boundary passage (SBP) by the Earth and upper-level tropospheric vorticity area index (VAI), that was found by Wilcox et al. (1974) and shown to be statistically significant by Hines and Halevy (1977) is revisited. A minimum in the VAI one day after SBP followed by an increase a few days later was observed. Using the ECMWF ERA-40 re-analysis dataset for the original period from 1963 to 1973 and extending it to 2002, we have verified what has become known as the "Wilcox effect" for the Northern as well as the Southern Hemisphere winters. The effect persists through years of high and low volcanic aerosol loading except for the Northern Hemisphere at 500 mb, when the VAI minimum is weak during the low aerosol years after 1973, particularly for sector boundaries associated with south-to-north reversals of the interplanetary magnetic field (IMF) BZ component. The "disappearance" of the Wilcox effect was found previously by Tinsley et al. (1994) who suggested that enhanced stratospheric volcanic aerosols and changes in air-earth current density are necessary conditions for the effect. The present results indicate that the Wilcox effect does not require high aerosol loading to be detected. The results are corroborated by a correlation with coronal holes where the fast solar wind originates. Ground-based measurements of the green coronal emission line (Fe XIV, 530.3 nm) are used in the superposed epoch analysis keyed by the times of sector boundary passage to show a one-to-one correspondence between the mean VAI variations and coronal holes. The VAI is modulated by high-speed solar wind streams with a delay of 1–2 days. The Fourier spectra of VAI time series show peaks at periods similar to those found in the solar corona and solar wind time series. In the modulation of VAI by solar wind the IMF BZ seems to control the phase of the Wilcox effect and the depth of the VAI minimum. The mean VAI response to SBP associated with the north-to-south reversal of BZ is leading by up to 2 days the mean VAI response to SBP associated with the south-to-north reversal of BZ. For the latter, less geoeffective events, the VAI minimum deepens (with the above exception of the Northern Hemisphere low-aerosol 500-mb VAI) and the VAI maximum is delayed. The phase shift between the mean VAI responses obtained for these two subsets of SBP events may explain the reduced amplitude of the overall Wilcox effect. In a companion paper, Prikryl et al. (2009) propose a new mechanism to explain the Wilcox effect, namely that solar-wind-generated auroral atmospheric gravity waves (AGWs) influence the growth of extratropical cyclones. It is also observed that severe extratropical storms, explosive cyclogenesis and significant sea level pressure deepenings of extratropical storms tend to occur within a few days of the arrival of high-speed solar wind. These observations are discussed in the context of the proposed AGW mechanism as well as the previously suggested atmospheric electrical current (AEC) model (Tinsley et al., 1994), which requires the presence of stratospheric aerosols for a significant (Wilcox) effect.

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