Persistent Scatterer Interferometry: A review Crosetto, Michele; Monserrat, Oriol; Cuevas-González, María ...
ISPRS journal of photogrammetry and remote sensing,
20/May , Letnik:
115
Journal Article
Recenzirano
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Persistent Scatterer Interferometry (PSI) is a powerful remote sensing technique able to measure and monitor displacements of the Earth’s surface over time. Specifically, PSI is a radar-based ...technique that belongs to the group of differential interferometric Synthetic Aperture Radar (SAR). This paper provides a review of such PSI technique. It firstly recalls the basic principles of SAR interferometry, differential SAR interferometry and PSI. Then, a review of the main PSI algorithms proposed in the literature is provided, describing the main approaches and the most important works devoted to single aspects of PSI. A central part of this paper is devoted to the discussion of different characteristics and technical aspects of PSI, e.g. SAR data availability, maximum deformation rates, deformation time series, thermal expansion component of PSI observations, etc. The paper then goes through the most important PSI validation activities, which have provided valuable inputs for the PSI development and its acceptability at scientific, technical and commercial level. This is followed by a description of the main PSI applications developed in the last fifteen years. The paper concludes with a discussion of the main open PSI problems and the associated future research lines.
On March 11, 2020, the World Health Organization declared COVID-19-the infectious disease caused by SARS-CoV-2-a pandemic. Since then, the majority of countries-including Spain-have imposed strict ...restrictions in order to stop the spread of the virus and the collapse of the health systems. People's health care-seeking behavior has exhibited a change, not only in those months when the COVID-19 control measures were strictest, but also in the months that followed. We aimed to examine how the trends in ophthalmological emergencies changed during the COVID-19 pandemic in one of the largest tertiary referral hospitals in Spain. To this end, data from all the patients that attended the ophthalmological emergency department during the pandemic period-March 2020 to February 2021-were retrospectively collected and compared with data from the previous year. Moreover, a comparison between April 2020-when the restrictions were most severe-and April 2019 was made. A total of 90,694 patients were included. As expected, there was a decrease in the number of consultations. There was also a decrease in the frequency of conjunctival pathology consultations. These changes may bring to light not only the use that people make of the emergency department, but also the new trends in ophthalmological conditions derived from the hygienic habits that the COVID-19 pandemic has established.
This paper describes a new approach to Persistent Scatterer Interferometry (PSI) data processing and analysis, which is implemented in the PSI chain of the Geomatics (PSIG) Division of CTTC. This ...approach includes three main processing blocks. In the first one, a set of correctly unwrapped and temporally ordered phases are derived, which are computed on Persistent Scatterers (PSs) that cover homogeneously the area of interest. The key element of this block is given by the so-called Cousin PSs (CPSs), which are PSs characterized by a moderate spatial phase variation that ensures a correct phase unwrapping. This block makes use of flexible tools to check the consistency of phase unwrapping and guarantee a uniform CPS coverage. In the second block, the above phases are used to estimate the atmospheric phase screen. The third block is used to derive the PS deformation velocity and time series. Its key tool is a new 2+1D phase unwrapping algorithm. The procedure offers different tools to globally control the quality of the processing steps. The PSIG procedure has been successfully tested over urban, rural and vegetated areas using X-band PSI data. Its performance is illustrated using 28 TerraSAR-X StripMap images over the metropolitan area of Barcelona.
Wildfires have major effects on forest dynamics, succession and the carbon cycle in the boreal biome. They are a significant source of carbon emissions, and current observed changes in wildfire ...regimes due to changes in climate could affect the balance of the boreal carbon pool. A better understanding of postwildfire vegetation dynamics in boreal forests will help predict the future role of boreal forests as a carbon sink or source. Time series of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Shortwave Infrared Index (NDSWIR) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite were used to investigate whether characteristic temporal patterns exist for stands of different ages in the Siberian boreal forests and whether their postwildfire dynamics are influenced by variables such as prewildfire vegetation cover. Two types of forests, evergreen needle-leaf (ENF) and deciduous needle-leaf (DNF), were studied by analysing a sample of 78 burned forest areas. In order to study a longer time frame, a chronosequence of burned areas of different ages was built by coupling information on location and age provided by a forest burned area database (from 1992 to 2003) to MODIS NDVI and NDSWIR time series acquired from 2001 to 2005. For each of the burned areas, an adjacent unburned control plot representing the same forest type was selected, with the aim of separating the interannual variations caused by climate from changes in NDVI and NDSWIR behaviour due to a wildfire. The results suggest that it takes more than 13 years for the temporal NDVI and NDSWIR signal to recover fully after wildfire. NDSWIR, which is associated to canopy moisture, needs a longer recovery period than NDVI, which is associated to vegetation greenness. The results also suggest that variability observed in postwildfire NDVI and NDSWIR can be explained partially by the dominant forest type: while 13 years after a fire NDVI and NDSWIR are similar for ENF and DNF, the initial impact appears to be greater on the NDVI and NDSWIR of ENF, suggesting a faster recovery by ENF.
Introduction. Periodontal disease (PD) is a chronic inflammation of the soft tissues that support the structure of the tooth, and miRNAs are highly dynamic molecules that participate in the ...regulation of gene expression interfering with multiple genetic targets. The dysregulation of the expression of miRNAs has been associated with different types of pathologies; therefore, they are excellent molecules to be studied as biomarkers. Material and Methods. A search was made in the electronic databases of PubMed, Scopus, and Science Direct. The following key words were used: “microRNAs,” “miRNAs,” “periodontal disease,” “periodontitis,” and “biomarker”; employee independent search strategies with the Boolean operators “OR” and “AND”; a further search of the references of the selected studies was performed to detect potential studies that met the selection criteria. The data recollected from each article were author, country, year of publication, sample size, type of sample used to identify miRNAs, methodology used to identify miRNAs, type of periodontal disease, and miRNAs identified. Results. Of the 13 selected studies, 6 used gingival tissue as a sample for the identification of miRNAs, 3 used gingival fluid, 2 used saliva, 1 used serum, and another used periodontal tissue. Chronic periodontitis was the most studied periodontal disease in 9 of the 13 selected articles; 7 used microarrays as the main technique for the identification of miRNAs. qRT-PCR was the assay choice to validate the identified miRNAs. Conclusion. The main type of periodontal disease on which most studies are focused is chronic periodontitis, with the main miRNAs being hsa-miR-146a, hsa-miR-146b, hsa-miR-155, and hsa-miR-200. This systematic review is one of the first to carry out an analysis of the current role of miRNAs in PD as biomarkers.
(1) Background: Both sarcopenia and disease-related malnutrition (DRM) are unfortunately underdiagnosed and undertreated in our Western hospitals, which could lead to worse clinical outcomes. Our ...objectives included to determine the impact of low muscle mass (MM) and strength, and also DRM and sarcopenia, on clinical outcomes (length of stay, death, readmissions at three months, and quality of life). (2) Methodology: Prospective cohort study in medical inpatients. On admission, MM and hand grip strength (HGS) were assessed. The Global Leadership Initiative on Malnutrition (GLIM) criteria were used to diagnose DRM and EWGSOP2 for sarcopenia. Assessment was repeated after one week and at discharge. Quality of life (EuroQoL-5D), length of stay (LoS), readmissions and mortality are reported. (3) Results: Two hundred medical inpatients, median 76.0 years-old and 68% with high comorbidity. 27.5% met GLIM criteria and 33% sarcopenia on admission, increasing to 38.1% and 52.3% on discharge. Both DRM and sarcopenia were associated with worse QoL. 6.5% died and 32% readmission in 3 months. The odds ratio (OR) of mortality for DRM was 4.36 and for sarcopenia 8.16. Readmissions were significantly associated with sarcopenia (OR = 2.25) but not with DRM. A higher HGS, but not MM, was related to better QoL, less readmissions (OR = 0.947) and lower mortality (OR = 0.848) after adjusting for age, sex, and comorbidity. (4) Conclusions: In medical inpatients, mostly polymorbid, both DRM but specially sarcopenia are associated with poorer quality of life, more readmissions, and higher mortality. Low HGS proved to be a stronger predictor of worse outcomes than MM.
In the present work, we analyzed the linear and nonlinear model suitabilities for adsorption data from aqueous As(III) removal by manganese ferrite nanoparticles (NPs). Hence, As(III) adsorption onto ...ferrite NPs was formerly analyzed by the intraparticle diffusion model (IPD). Then, adsorption kinetics was described by the pseudo-first-order (PFO), pseudo-second-order (PSO), and Elovich models, while equilibrium adsorption was fitted to the Freundlich and Langmuir isotherms. Linear and nonlinear kinetic and isotherm models were solved and compared. The nonlinear data fitting was applied through the
lsqcurvefit
user-defined function (Matlab ver. 7.10.0). The initial adsorption rate was influenced by intraparticle diffusion and surface or film diffusion from the arsenic bulk solution to ferrite NPs, according to the IPD model. Adsorption kinetics of As(III) on manganese ferrite NPs was better described by the PSO model, followed by the Elovich model and then the PFO model. Equilibrium adsorption data were only worthily described by the Freundlich isotherm model. While the PSO, Elovich and Freundlich linear models showed even better fit than the nonlinear models, determinant bias was depicted for the PFO and Langmuir linear models. Thus, to use nonlinear adsorption models is highly advisable, having the Matlab
lsqcurvefit
function been proven very useful to face such task.
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.
This paper is focused on the estimation of the thermal expansion of buildings and infrastructures using X-band Persistent Scatterer Interferometry (PSI) observations. For this purpose an extended PSI ...model is used, which allows separating the thermal expansion from the total observed deformation thus generating a new PSI product: the map of the thermal expansion parameter, named thermal map. The core of the paper is devoted to the exploitation of the information contained in the thermal maps: three examples are discussed in detail, which concern a viaduct, a set of industrial buildings and two skyscrapers. The thermal maps can be used to derive the thermal expansion coefficient of the observed objects and information on their static structure. In addition, the paper illustrates the distortions in the PSI deformation products that occur if the thermal expansion is not explicitly modelled. Finally, an inter-comparison exercise is described, where the thermal expansion coefficients estimated by PSI are compared with those derived by a Ku-band ground-based SAR campaign.
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