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.

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 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 Epidemiological profile, spatial distribution, and syphilis time series: a cross-sectional study in a Brazilian municipality

2021 ◽  
Vol 15 (10) ◽  
pp. 1462-1470
Author(s):  
Carolina Matteussi Lino ◽  
Maria da Luz Rosário de Sousa ◽  
Marília Jesus Batista
Keyword(s):  
Time Series ◽  
Spatial Distribution ◽  
Congenital Syphilis ◽  
Public Health Problem ◽  
Cross Sectional Study ◽  
Incidence Rates ◽  
P Value ◽  
Cross Sectional ◽  
Definition Of ◽  
Epidemiological Profile

Introduction: Syphilis is an infectious disease of bacterial nature, acting on organs and/or systems. The increase in the number of cases worldwide has been of concern and the infection has been considered a public health problem. Given this scenario, this study evaluates the epidemiological profile, spatial distribution, and time series of the cases of acquired syphilis, syphilis in pregnant women, and congenital syphilis in a Brazilian municipality. Methodology: This is a cross-sectional and descriptive study with second data of the notified cases. For the definition of the population universe, an initial survey of syphilis cases notified in the municipality was carried out, from January 1, 2013 to December 31, 2017. Results: There was an increase in the notified cases and the detection/incidence rates of syphilis. The epidemiological profile was composed of men (76.7%), adults (24.8%), white (60.4%), with eight or more years of study (53.7%) in addition to pregnant adolescents (36.7%) and young adults (26.0%), with inadequate treatment and untreated partners. A concentration of cases was identified in the regions with the lowest monthly income and the time series showed an increasing trend (p-value < 0.001). Conclusions: Health actions should continue to improve access to diagnosis and to notification, focusing on treatment, cure and health education actions to control and prevent new cases.

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

&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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 &quot;Kalkberg&quot;. And we can observe subsidence processes over the historic town of L&amp;#252;beck.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

scholarly journals Surface Deformation Monitoring in Zhengzhou City from 2014 to 2016 Using Time-Series InSAR

2018 ◽  
Vol 10 (11) ◽  
pp. 1731 ◽  
Author(s):  
Zhengjia Zhang ◽  
Chao Wang ◽  
Mengmeng Wang ◽  
Ziwei Wang ◽  
Hong Zhang
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Urban Expansion ◽  
Correction Method ◽  
Deformation Monitoring ◽  
Ground Subsidence ◽  
Significant Information ◽  
Persistent Scatterers ◽  
Deformation Parameters

In recent years, with the development of urban expansion in Zhengzhou city, the underground resources, such as underground water and coal mining, have been exploited greatly, which have resulted in ground subsidence and several environmental issues. In order to study the spatial distribution and temporal changes of ground subsidence of Zhengzhou city, the Interferometric Synthetic Aperture Radar (InSAR) time series analysis technique combining persistent scatterers (PSs) and distributed scatterers (DSs) was proposed and applied. In particular, the orbit and topographic related atmospheric phase errors have been corrected by a phase ramp correction method. Furthermore, the deformation parameters of PSs and DSs are retrieved based on a layered strategy. The deformation and DEM error of PSs are first estimated using conventional PSI method. Then the deformation parameters of DSs are retrieved using an adaptive searching window based on the initial results of PSs. Experimental results show that ground deformation of the study area could be retrieved by the proposed method and the ground deformation is widespread and unevenly distributed with large differences. The deformation rate ranges from −55 to 10 mm/year, and the standard deviation of the results is about 8 mm/year. The observed InSAR results reveal that most of the subsidence areas are in the north and northeast of Zhengzhou city. Furthermore, it is found that the possible factors resulting in the ground subsidence include sediment consolidation, water exploitation, and urban expansion. The result could provide significant information to serve the land subsidence mitigation in Zhengzhou city.

scholarly journals Temporal analysis of the clinical evolution of confirmed cases of COVID-19 in the state of Mato Grosso do Sul - Brazil

2020 ◽  
Author(s):  
Carolina Pompeo ◽  
Marcos Antonio Ferreira Junior ◽  
Andreia Insabralde de Queiroz Cardoso ◽  
Luciana Scarlazzari Costa ◽  
Mercy da Costa Souza ◽  
...  
Keyword(s):  
Time Series ◽  
Polynomial Regression ◽  
Temporal Analysis ◽  
The State ◽  
Cross Sectional ◽  
Mato Grosso ◽  
Significance Level ◽  
Health Authorities ◽  
Polynomial Regression Models ◽  
Mato Grosso Do Sul

The objective was to analyze the evolution of confirmed cases of COVID-19 in the first four months of the pandemic in Mato Grosso do Sul, a state in the Center-West region of Brazil, as well as the factors related to the prevalence of deaths. This was an observational study with a cross-sectional and time series design based on data from the information system of the State Department of Health of Mato Grosso do Sul, Brazil. The microdata from the epidemiological bulletin is open and in the public domain; consultation was carried out from March to July 2020. The incidences were stratified per 100,000 inhabitants. The cross-section study was conducted to describe COVID-19 cases, and the trend analysis was performed using polynomial regression models for time series, with R-Studio software and a significance level of 5%. There was a predominance of women among the cases, and of men in terms of deaths. The presence of comorbidities was statistically related to mortality, particularly lung disease and diabetes, and the mean age of the deaths was 67.7 years. Even though the macro-region of the state capital, Campo Grande, had a higher number of cases, the most fatalities were in the macro-region of Corumba. The trend curve demonstrated discreet growth in the incidence of cases between epidemiological weeks 11 and 19, with a significant increase in week 20 throughout the state. The trend for COVID-19 in the state of Mato Grosso do Sul was upward and regular, but there was an important and alarming exponential increase. The health authorities should adopt the necessary measures to enforce health precautions and encourage social distancing of the population so that health services will be able to care for those afflicted by the disease, especially older people, those with comorbidities, and vulnerable sectors of the population. Keywords: Pandemics; Coronavirus; Respiratory tract diseases.

Twitter Usage Using Common Reference to Tinnitus

2020 ◽  
Vol 29 (2) ◽  
pp. 206-217
Author(s):  
Jianyuan Ni ◽  
Monica L. Bellon-Harn ◽  
Jiang Zhang ◽  
Yueqing Li ◽  
Vinaya Manchaiah
Keyword(s):  
Nonprofit Organizations ◽  
Temporal Trends ◽  
Temporal Analysis ◽  
Cross Sectional ◽  
For Profit ◽  
Common Reference ◽  
Personal Experiences ◽  
Twitter Users ◽  
Sectional Analysis ◽  
Share Information

Objective The objective of the study was to examine specific patterns of Twitter usage using common reference to tinnitus. Method The study used cross-sectional analysis of data generated from Twitter data. Twitter content, language, reach, users, accounts, temporal trends, and social networks were examined. Results Around 70,000 tweets were identified and analyzed from May to October 2018. Of the 100 most active Twitter accounts, organizations owned 52%, individuals owned 44%, and 4% of the accounts were unknown. Commercial/for-profit and nonprofit organizations were the most common organization account owners (i.e., 26% and 16%, respectively). Seven unique tweets were identified with a reach of over 400 Twitter users. The greatest reach exceeded 2,000 users. Temporal analysis identified retweet outliers (> 200 retweets per hour) that corresponded to a widely publicized event involving the response of a Twitter user to another user's joke. Content analysis indicated that Twitter is a platform that primarily functions to advocate, share personal experiences, or share information about management of tinnitus rather than to provide social support and build relationships. Conclusions Twitter accounts owned by organizations outnumbered individual accounts, and commercial/for-profit user accounts were the most frequently active organization account type. Analyses of social media use can be helpful in discovering issues of interest to the tinnitus community as well as determining which users and organizations are dominating social network conversations.

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

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

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

An easy way to create duration variables in binary cross-sectional time-series data

2020 ◽  
Vol 20 (4) ◽  
pp. 916-930
Author(s):  
Andrew Q. Philips
Keyword(s):  
Time Series ◽  
Missing Data ◽  
Time Series Data ◽  
Series Data ◽  
Duration Dependence ◽  
Cross Sectional ◽  
Common Solution ◽  
The Common

In cross-sectional time-series data with a dichotomous dependent variable, failing to account for duration dependence when it exists can lead to faulty inferences. A common solution is to include duration dummies, polynomials, or splines to proxy for duration dependence. Because creating these is not easy for the common practitioner, I introduce a new command, mkduration, that is a straightforward way to generate a duration variable for binary cross-sectional time-series data in Stata. mkduration can handle various forms of missing data and allows the duration variable to easily be turned into common parametric and nonparametric approximations.

scholarly journals Spectral Pitch Similarity is a Predictor of Perceived Change in Sound- as Well as Note-Based Music

2019 ◽  
Vol 2 ◽  
pp. 205920431984735
Author(s):  
Roger T. Dean ◽  
Andrew J. Milne ◽  
Freya Bailes
Keyword(s):  
Time Series ◽  
Piano Music ◽  
Individual Response ◽  
Discrete Events ◽  
Acoustic Intensity ◽  
Spectral Parameters ◽  
Cross Sectional ◽  
Perceived Change ◽  
Predictive Role ◽  
The Individual

Spectral pitch similarity (SPS) is a measure of the similarity between spectra of any pair of sounds. It has proved powerful in predicting perceived stability and fit of notes and chords in various tonal and microtonal instrumental contexts, that is, with discrete tones whose spectra are harmonic or close to harmonic. Here we assess the possible contribution of SPS to listeners’ continuous perceptions of change in music with fewer discrete events and with noisy or profoundly inharmonic sounds, such as electroacoustic music. Previous studies have shown that time series of perception of change in a range of music can be reasonably represented by time series models, whose predictors comprise autoregression together with series representing acoustic intensity and, usually, the timbral parameter spectral flatness. Here, we study possible roles for SPS in such models of continuous perceptions of change in a range of both instrumental (note-based) and sound-based music (generally containing more noise and fewer discrete events). In the first analysis, perceived change in three pieces of electroacoustic and one of piano music is modeled, to assess the possible contribution of (de-noised) SPS in cooperation with acoustic intensity and spectral flatness series. In the second analysis, a broad range of nine pieces is studied in relation to the wider range of distinctive spectral predictors useful in previous perceptual work, together with intensity and SPS. The second analysis uses cross-sectional (mixed-effects) time series analysis to take advantage of all the individual response series in the dataset, and to assess the possible generality of a predictive role for SPS. SPS proves to be a useful feature, making a predictive contribution distinct from other spectral parameters. Because SPS is a psychoacoustic “bottom up” feature, it may have wide applicability across both the familiar and the unfamiliar in the music to which we are exposed.

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