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

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.

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Improving runoff estimates from regional climate models: a performance analysis in Spain

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-9-175-2012 ◽

2012 ◽

Vol 9 (1) ◽

pp. 175-214

Author(s):

D. González-Zeas ◽

L. Garrote ◽

A. Iglesias ◽

A. Sordo-Ward

Keyword(s):

Time Series ◽

Large Scale ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Hydrologic Model ◽

Direct Runoff ◽

Interpolation Methods ◽

Basin Scale ◽

The Impact

Abstract. An important aspect to assess the impact of climate change on water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimize the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of naturalised runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behavior of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evaporation and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the "best estimator" of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber also gives good results.

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Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry

Remote Sensing ◽

10.3390/rs11020129 ◽

2019 ◽

Vol 11 (2) ◽

pp. 129 ◽

Cited By ~ 22

Author(s):

José Delgado Blasco ◽

Michael Foumelis ◽

Chris Stewart ◽

Andrew Hooper

Keyword(s):

Ground Deformation ◽

European Space Agency ◽

Vertical Motion ◽

Automatic Processing ◽

Deformation Monitoring ◽

Geographical Information ◽

Persistent Scatterer Interferometry ◽

Persistent Scatterers ◽

Processing Chain ◽

Persistent Scatterer

Land subsidence in urban environments is an increasingly prominent aspect in the monitoring and maintenance of urban infrastructures. In this study we update the subsidence information over Rome and its surroundings (already the subject of past research with other sensors) for the first time using Copernicus Sentinel-1 data and open source tools. With this aim, we have developed a fully automatic processing chain for land deformation monitoring using the European Space Agency (ESA) SentiNel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS). We have applied this automatic processing chain to more than 160 Sentinel-1A images over ascending and descending orbits to depict primarily the Line-Of-Sight ground deformation rates. Results of both geometries were then combined to compute the actual vertical motion component, which resulted in more than 2 million point targets, over their common area. Deformation measurements are in agreement with past studies over the city of Rome, identifying main subsidence areas in: (i) Fiumicino; (ii) along the Tiber River; (iii) Ostia and coastal area; (iv) Ostiense quarter; and (v) Tivoli area. Finally, post-processing of Persistent Scatterer Inteferometry (PSI) results, in a Geographical Information System (GIS) environment, for the extraction of ground displacements on urban infrastructures (including road networks, buildings and bridges) is considered.

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Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets

Remote Sensing ◽

10.3390/rs11141675 ◽

2019 ◽

Vol 11 (14) ◽

pp. 1675 ◽

Cited By ~ 10

Author(s):

Tomás ◽

Pagán ◽

Navarro ◽

Cano ◽

Pastor ◽

...

Keyword(s):

Regional Scale ◽

Central Italy ◽

Geographical Information ◽

External Information ◽

Automatic Identification ◽

Persistent Scatterer Interferometry ◽

Active Deformation ◽

Persistent Scatterers ◽

Persistent Scatterer ◽

Map Scale

This work describes a new procedure aimed to semi-automatically identify clusters of active persistent scatterers and preliminarily associate them with different potential types of deformational processes over wide areas. This procedure consists of three main modules: (i) ADAfinder, aimed at the detection of Active Deformation Areas (ADA) using Persistent Scatterer Interferometry (PSI) data; (ii) LOS2HV, focused on the decomposition of Line Of Sight (LOS) displacements from ascending and descending PSI datasets into vertical and east-west components; iii) ADAclassifier, that semi-automatically categorizes each ADA into potential deformational processes using the outputs derived from (i) and (ii), as well as ancillary external information. The proposed procedure enables infrastructures management authorities to identify, classify, monitor and categorize the most critical deformations measured by PSI techniques in order to provide the capacity for implementing prevention and mitigation actions over wide areas against geological threats. Zeri, Campiglia Marittima–Suvereto and Abbadia San Salvatore (Tuscany, central Italy) are used as case studies for illustrating the developed methodology. Three PSI datasets derived from the Sentinel-1 constellation have been used, jointly with the geological map of Italy (scale 1:50,000), the updated Italian landslide and land subsidence maps (scale 1:25,000), a 25 m grid Digital Elevation Model, and a cadastral vector map (scale 1:5,000). The application to these cases of the proposed workflow demonstrates its capability to quickly process wide areas in very short times and a high compatibility with Geographical Information System (GIS) environments for data visualization and representation. The derived products are of key interest for infrastructures and land management as well as decision-making at a regional scale.

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Improving runoff estimates from regional climate models: a performance analysis in Spain

Hydrology and Earth System Sciences ◽

10.5194/hess-16-1709-2012 ◽

2012 ◽

Vol 16 (6) ◽

pp. 1709-1723 ◽

Cited By ~ 18

Author(s):

D. González-Zeas ◽

L. Garrote ◽

A. Iglesias ◽

A. Sordo-Ward

Keyword(s):

Time Series ◽

Large Scale ◽

Climate Models ◽

Regional Climate ◽

Aridity Index ◽

Regional Climate Models ◽

Hydrologic Model ◽

Direct Runoff ◽

Interpolation Methods ◽

Basin Scale

Abstract. An important step to assess water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimise the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of natural runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behaviour of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evapotranspiration and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the "best estimator" of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber (1904) also gives good results.

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Self-Supervised Pre-Training of Transformers for Satellite Image Time Series Classification

10.36227/techrxiv.13025039.v1 ◽

2020 ◽

Author(s):

Yuan Yuan ◽

Lei Lin

Keyword(s):

Time Series ◽

Deep Learning ◽

Large Scale ◽

Temporal Structure ◽

Satellite Image ◽

Fine Tuning ◽

Small Scale ◽

Model Parameters ◽

Learning Approaches ◽

Wide Range

Satellite image time series (SITS) classification is a major research topic in remote sensing and is relevant for a wide range of applications. Deep learning approaches have been commonly employed for SITS classification and have provided state-of-the-art performance. However, deep learning methods suffer from overfitting when labeled data is scarce. To address this problem, we propose a novel self-supervised pre-training scheme to initialize a Transformer-based network by utilizing large-scale unlabeled data. In detail, the model is asked to predict randomly contaminated observations given an entire time series of a pixel. The main idea of our proposal is to leverage the inherent temporal structure of satellite time series to learn general-purpose spectral-temporal representations related to land cover semantics. Once pre-training is completed, the pre-trained network can be further adapted to various SITS classification tasks by fine-tuning all the model parameters on small-scale task-related labeled data. In this way, the general knowledge and representations about SITS can be transferred to a label-scarce task, thereby improving the generalization performance of the model as well as reducing the risk of overfitting. Comprehensive experiments have been carried out on three benchmark datasets over large study areas. Experimental results demonstrate the effectiveness of the proposed method, leading to a classification accuracy increment up to 1.91% to 6.69%. <div><b>This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.</b></div>

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Persistent Scatterer Interferometry of Sentinel-1 time series to detect ground subsidence in the city of Recife, Brazil

Journal of Hyperspectral Remote Sensing ◽

10.29150/jhrs.v10.1.p1-9 ◽

2020 ◽

Vol 10 (1) ◽

pp. 1

Author(s):

Enton Bedini

Keyword(s):

Time Series ◽

Ground Subsidence ◽

Persistent Scatterer Interferometry ◽

Persistent Scatterer ◽

Radar Imagery ◽

Long Time ◽

Satellite Radar ◽

Surrounding Areas ◽

Satellite Radar Imagery ◽

The City

Persistent Scatterer Interferometry (PSI) analysis of Sentinel-1 time series was carried out to detect ground subsidence in the city of Recife, Brazil. The dataset consisted of sixty-eight Sentinel-1A Interferometric Wide (IW) Single Look Complex (SLC) images of the time period April 2017 – September 2019. The images were acquired in descending orbit in VV (vertical transmitting, vertical receiving) polarization. The results of the PSI analysis show that in the city of Recife occur several ground subsidence areas. The largest ground subsidence area occurs between the neighborhoods of Afogados, Torrŏes and Cordeiro. The subsidence rates in this area range from few mm/year up to -15 mm/year. This ground subsidence could be a result of groundwater extraction or of subsidence processes in urbanized reclaimed lands. Similar but smaller ground subsidence areas occur in several localities in Recife. In some cases, subsidence with rates of up to -25 mm/year is noted in small zones where new buildings have been constructed in the last decade. This should be due to ground settlement processes, taking a long time due to the particular soils and geology of the locality. This study can serve as a first contribution for further research on the ground subsidence hazard in the city of Recife and the surrounding areas by means of satellite radar imagery.

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OncoThreads: Visualization of Large Scale Longitudinal Cancer Molecular Data

10.31219/osf.io/b3n4u ◽

2021 ◽

Author(s):

Theresa A Harbig ◽

Sabrina Nusrat ◽

Tali Mazor ◽

Qianwen Wang ◽

Alexander Thomson ◽

...

Keyword(s):

Longitudinal Data ◽

Large Scale ◽

Cancer Genomics ◽

Temporal Patterns ◽

Molecular Data ◽

Liquid Biopsies ◽

Sequencing Technologies ◽

Molecular Features ◽

Wide Range ◽

The Impact

Molecular profiling of patient tumors and liquid biopsies over time with next-generation sequencing technologies and new immuno-profile assays are becoming part of standard research and clinical practice. With the wealth of new longitudinal data, there is a critical need for visualizations for cancer researchers to explore and interpret temporal patterns not just in a single patient but across cohorts. To address this need we developed OncoThreads, a tool for the visualization of longitudinal clinical and cancer genomics and other molecular data in patient cohorts. The tool visualizes patient cohorts as temporal heatmaps and Sankey diagrams that support the interactive exploration and ranking of a wide range of clinical and molecular features. This allows analysts to discover temporal patterns in longitudinal data, such as the impact of mutations on response to a treatment, e.g. emergence of resistant clones. We demonstrate the functionality of OncoThreads using a cohort of 23 glioma patients sampled at 2-4 timepoints. OncoThreads is freely available at http://oncothreads.gehlenborglab.org and implemented in Javascript using the cBioPortal web API as a backend.

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Ivan Kavaleridze`s dramaturgy on the Sumy stage

SUMY HISTORICAL AND ARCHIVAL JOURNAL ◽

10.21272/shaj.2021.i36.p.37 ◽

2021 ◽

Author(s):

D.V. Budianskyi

Keyword(s):

Large Scale ◽

Musical Comedy ◽

Historical Figures ◽

Wide Range ◽

Socialist Realist ◽

History Of ◽

Characteristic Features ◽

Old Men ◽

The Impact ◽

First Time

The characteristic features of I. Kavaleridze’s drama is considered in the article. It is noted that there are signs of the artist’s individuality, attraction to expressionist forms, artistic techniques characteristic for the art of sculpture: symbolism, monumentality, hyperbole. I. Kavaleridze was well versed in the drama laws, understood the specifics of the stage events construction, had a large arsenal of literary means, thanks to which the characters’ monologues and dialogues were extremely expressive and colorful. In his work, he implemented original solutions that were ahead of time. Therefore, many of the artist’s ideas and achievements received due recognition only after his death. I. Kavaleridze’s creative heritage covers a wide range of both purely artistic and general philosophical problems. Among them the formation of the era of modernism and its features in the Ukrainian art of the early XX century, the impact of revolutionary ideas on the work of the 1920s, the role of spiritual leaders of the Ukrainian people T. Shevchenko and G. Skovoroda in the formation of national consciousness, political and ideological pressure on figurative art language and the formation of a socialist-realist canon, etc. The analysis of the productions of I. Kavalerizde’s plays “The First Furrow” and “Gregory and Paraskeva” on the stage of the Mykhailo Shchepkin Sumy Theater of Drama and Musical Comedy in 1970-1972. The article notes that these plays were staged in Sumy for the first time in the history of Ukrainian theater. The premiere of “The First Furrow” (the play was called “Old Men”) took place on March 19, 1970. The figure of the national genius Hryhoriy Skov oroda was als o embodied for the first time on t he stage in Sumy in th e play “Hryhoriy and Paraskeva”. It premiered on October 21, 1972. I. Rybchynsky, Honored Artist of the USSR, performed the production. Creating generalized historical outlines of people’s life, features of life at that time, depicting psychological portraits of people in various, sometimes-dramatic collisions, in the productions of I. Kavaleridze’s plays on the Sumy stage the emphasis was on universal values such as virtue, love. The main character was the Ukrainian people, who nurtured such large-scale historical figures, gave them strength and wisdom for great achievements. Based on publications in periodicals of that time, memoirs of Ukrainian directors, the peculiarities of the director’s interpretation, stenographic and musical design of these plays on the Sumy stage are considered. Considerable attention is paid to the analysis of acting works in I. Kavaleridze’s plays. In particular, the peculiarities of the actor’s embodiment of the image of the national genius Hryhoriy Skovoroda on the stage are presented. It is noted that I. Kavaleridze’s plays, created in a difficult political, social and ideological context, are rightly considered to be highly artistic works of Ukrainian drama. Their staging was carried out on various theatrical stages, including Mykhailo Shchepkin Sumy Theater of Drama and Musical Comedy is an important page of national theatrical art.

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Effects of Seismic Incident Directionality on Ground Motion Characteristics and Responses of a Single-Mass Bi-Degree-of-Freedom System

International Journal of Structural Stability and Dynamics ◽

10.1142/s0219455421501194 ◽

2021 ◽

pp. 2150119

Author(s):

Jun Gong ◽

Xudong Zhi ◽

Feng Fan ◽

Shizhao Shen ◽

Da Qaio ◽

...

Keyword(s):

Ground Motion ◽

Large Scale ◽

Seismic Analysis ◽

Ground Motions ◽

Propagation Distance ◽

Degree Of Freedom ◽

Different Types ◽

Single Mass ◽

Motion Characteristics ◽

The Impact

To investigate the variability of ground motion characteristics (GMC) with the angle of seismic incidence (ASI) and the impact of seismic incident directionality on structural responses, first, a large-scale database of recorded ground motions was used to analyze the causes of GMC variability due to the seismic incident directionality effect (SIDE). Then a single-mass bi-degree-of-freedom system (SM-BDOF-S) with different types of symmetrical sections was selected to explore the influence mechanism of SIDE on the seismic responses. The results illustrated that the GMC has substantial variability with the ASI, which is independent of the earthquake source, propagation distance, and site condition, and exhibits complex random characteristics. Additionally, a classification method for ground motions is proposed based on this GMC variability to establish a criterion for selecting ground motions in seismic analysis considering the SIDE. Moreover, for an SM-BDOF-S, the response spectral plane is proposed to explain the transition behavior of spectral responses that are very similar among different stiffness ratios, but divergent for different types of ground motions. The influence of SIDE on structures is determined by their stiffness and stiffness ratio in the [Formula: see text]- and [Formula: see text]-directions, as well as the type of ground motion.

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Economics of the disintegration of the Greenland ice sheet

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1814990116 ◽

2019 ◽

Vol 116 (25) ◽

pp. 12261-12269 ◽

Cited By ~ 5

Author(s):

William Nordhaus

Keyword(s):

Climate Change ◽

Large Scale ◽

Social Cost ◽

Climate Models ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Reduced Form ◽

Small Contribution ◽

Wide Range ◽

The Impact

Concerns about the impact on large-scale earth systems have taken center stage in the scientific and economic analysis of climate change. The present study analyzes the economic impact of a potential disintegration of the Greenland ice sheet (GIS). The study introduces an approach that combines long-run economic growth models, climate models, and reduced-form GIS models. The study demonstrates that social cost–benefit analysis and damage-limiting strategies can be usefully extended to illuminate issues with major long-term consequences, as well as concerns such as potential tipping points, irreversibility, and hysteresis. A key finding is that, under a wide range of assumptions, the risk of GIS disintegration makes a small contribution to the optimal stringency of current policy or to the overall social cost of climate change. It finds that the cost of GIS disintegration adds less than 5% to the social cost of carbon (SCC) under alternative discount rates and estimates of the GIS dynamics.

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