scholarly journals Generation of Earth’s Surface Three-Dimensional (3-D) Displacement Time-Series by Multiple-Platform SAR Data

2018 ◽  
Author(s):  
Antonio Pepe
Keyword(s):  
Time Series ◽  
Three Dimensional ◽  
Multiple Platform ◽  
Sar Data

scholarly journals Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kazutoshi Yoshitake ◽  
Gaku Kimura ◽  
Tomoko Sakami ◽  
Tsuyoshi Watanabe ◽  
Yukiko Taniuchi ◽  
...  
Keyword(s):  
Time Series ◽  
Microbial Communities ◽  
Pacific Coast ◽  
Three Dimensional ◽  
Amplicon Sequencing ◽  
Metagenomic Data ◽  
Shotgun Metagenomics ◽  
Functional Features ◽  
Pacific Coast Of Japan ◽  
Marine Microbial Communities

AbstractAlthough numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

scholarly journals Meso- and microscale sea-ice motion in the East Siberian Sea as determined from ERS-1 SAR Data

1999 ◽  
Vol 45 (150) ◽  
pp. 370-383 ◽  
Author(s):  
Kim Morris ◽  
Shusun Li ◽  
Martin Jeffries
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Large Scale ◽  
Vector Fields ◽  
Lateral Displacement ◽  
Motion Vector ◽  
Sar Interferometry ◽  
East Siberian Sea ◽  
Pack Ice ◽  
Sar Data

Abstract Synthetic aperture radar- (SAR-)derived ice-motion vectors and SAR interferometry were used to study the sea-ice conditions in the region between the coast and 75° N (~ 560 km) in the East Siberian Sea in the vicinity of the Kolyma River. ERS-1 SAR data were acquired between 24 December 1993 and 30 March 1994 during the 3 day repeat Ice Phase of the satellite. The time series of the ice-motion vector fields revealed rapid (3 day) changes in the direction and displacement of the pack ice. Longer-term (≥ 1 month) trends also emerged which were related to changes in large-scale atmospheric circulation. On the basis of this time series, three sea-ice zones were identified: the near-shore, stationary-ice zone; a transitional-ice zone;and the pack-ice zone. Three 3 day interval and one 9 day interval interferometric sets (amplitude, correlation and phase diagrams) were generated for the end of December, the begining of February and mid-March. They revealed that the stationary-ice zone adjacent to the coast is in constant motion, primarily by lateral displacement, bending, tilting and rotation induced by atmospheric/oceanic forcing. The interferogram patterns change through time as the sea ice becomes thicker and a network of cracks becomes established in the ice cover. It was found that the major features in the interferograms were spatially correlated with sea-ice deformation features (cracks and ridges) and major discontinuities in ice thickness.

Study of Rehabilitation of Injured Knee Joint Applying Chaotic Theory in Human Body Motion

2007 ◽  
Vol 342-343 ◽  
pp. 581-584
Author(s):  
Byung Young Moon ◽  
Kwon Son ◽  
Jung Hong Park
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Angular Displacement ◽  
Three Dimensional ◽  
Gait Pattern ◽  
Body Motion ◽  
Largest Lyapunov Exponent ◽  
Chaos Analysis ◽  
Nonlinear Technique ◽  
Injured Knee

Gait analysis is essential to identify accurate cause and knee condition from patients who display abnormal walking. Traditional linear tools can, however, mask the true structure of motor variability, since biomechanical data from a few strides during the gait have limitation to understanding the system. Therefore, it is necessary to propose a more precise dynamic method. The chaos analysis, a nonlinear technique, focuses on understanding how variations in the gait pattern change over time. Healthy eight subjects walked on a treadmill for 100 seconds at 60 Hz. Three dimensional walking kinematic data were obtained using two cameras and KWON3D motion analyzer. The largest Lyapunov exponent from the measured knee angular displacement time series was calculated to quantify local stability. This study quantified the variability present in time series generated from gait parameter via chaos analysis. Gait pattern is found to be chaotic. The proposed Lyapunov exponent can be used in rehabilitation and diagnosis of recoverable patients.

scholarly journals Three-dimensional deformation time series of glacier motion from multiple-aperture DInSAR observation

2019 ◽  
Vol 93 (12) ◽  
pp. 2651-2660 ◽  
Author(s):  
Sergey Samsonov
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Three Dimensional ◽  
Data Sets ◽  
Ice Flow ◽  
The North ◽  
Glacier Ice ◽  
Deformation Component ◽  
3D Deformation

AbstractThe previously presented Multidimensional Small Baseline Subset (MSBAS-2D) technique computes two-dimensional (2D), east and vertical, ground deformation time series from two or more ascending and descending Differential Interferometric Synthetic Aperture Radar (DInSAR) data sets by assuming that the contribution of the north deformation component is negligible. DInSAR data sets can be acquired with different temporal and spatial resolutions, viewing geometries and wavelengths. The MSBAS-2D technique has previously been used for mapping deformation due to mining, urban development, carbon sequestration, permafrost aggradation and pingo growth, and volcanic activities. In the case of glacier ice flow, the north deformation component is often too large to be negligible. Historically, the surface-parallel flow (SPF) constraint was used to compute the static three-dimensional (3D) velocity field at various glaciers. A novel MSBAS-3D technique has been developed for computing 3D deformation time series where the SPF constraint is utilized. This technique is used for mapping 3D deformation at the Barnes Ice Cap, Baffin Island, Nunavut, Canada, during January–March 2015, and the MSBAS-2D and MSBAS-3D solutions are compared. The MSBAS-3D technique can be used for studying glacier ice flow at other glaciers and other surface deformation processes with large north deformation component, such as landslides. The software implementation of MSBAS-3D technique can be downloaded from http://insar.ca/.

Diesel Droplet Diffusion in Isotropic Turbulence With Digital Holographic Cinematography

2005 ◽  
Author(s):  
Balaji Gopalan ◽  
Edwin Malkiel ◽  
Jian Sheng ◽  
Joseph Katz
Keyword(s):  
Time Series ◽  
High Speed ◽  
Isotropic Turbulence ◽  
Fluid Motion ◽  
Three Dimensional ◽  
Time History ◽  
Sample Volume ◽  
Velocity Autocorrelation Function ◽  
Digital Cameras ◽  
Velocity Autocorrelation

High-speed in-line digital holographic cinematography was used to investigate the diffusion of droplets in locally isotropic turbulence. Droplets of diesel fuel (0.3–0.9mm diameter, specific gravity of 0.85) were injected into a 37×37×37mm3 sample volume located in the center of a 160-liter tank. The turbulence was generated by 4 spinning grids, located symmetrically in the corners of the tank, and was characterized prior to the experiments. The sample volume was back illuminated with two perpendicular collimated beams of coherent laser light and time series of in-line holograms were recorded with two high-speed digital cameras at 500 frames/sec. Numerical reconstruction generated a time series of high-resolution images of the droplets throughout the sample volume. We developed an algorithm for automatically detecting the droplet trajectories from each view, for matching the two views to obtain the three-dimensional tracks, and for calculating the time history of velocity. We also measured the mean fluid motion using 2-D PIV. The data enabled us to calculate the Lagrangian velocity autocorrelation function.

Coseismic Three-Dimensional Displacements Determined Using SAR Data: Theory and an Application Test

2009 ◽  
Vol 166 (8-9) ◽  
pp. 1403-1424 ◽  
Author(s):  
Pablo J. González ◽  
José Fernández ◽  
Antonio G. Camacho
Keyword(s):  
Three Dimensional ◽  
Sar Data

scholarly journals VirtEl - Software for Magnetic Encephalography Data Analysis by the Method of Virtual Electrodes

2019 ◽  
Vol 14 (1) ◽  
pp. 340-354 ◽  
Author(s):  
S.D. Rykunov ◽  
E.D. Rykunova ◽  
A.I. Boyko ◽  
M.N. Ustinin
Keyword(s):  
Time Series ◽  
Brain Area ◽  
Three Dimensional ◽  
Large Radius ◽  
Magnetic Encephalography ◽  
Electrode Method ◽  
The Fourier Transform ◽  
Virtual Electrodes ◽  
The Brain ◽  
Virtual Electrode

A new method of analyzing magnetic encephalography data, the virtual electrode method, was developed. According to magnetic encephalography data, a functional tomogram is constructed — the spatial distribution of field sources on a discrete grid. A functional tomogram displays on the head space the information contained in the multichannel time series of an encephalogram. This is achieved by solving the inverse problem for all elementary oscillations extracted using the Fourier transform. Each oscillation frequency corresponds to a three-dimensional grid node in which the source is located. The user sets the location, size and shape of the brain area for a detailed study of the frequency structure of a functional tomogram - a virtual electrode. The set of oscillations that fall into a given region represents the partial spectrum of this region. The time series of the encephalogram measured by the virtual electrode is restored using this spectrum. The method was applied to the analysis of magnetic encephalography data in two variations - a virtual electrode of a large radius and a point virtual electrode.

scholarly journals Landslide Deformation Analysis by Coupling Deformation Time Series from SAR Data with Hydrological Factors through Data Assimilation

2016 ◽  
Vol 8 (3) ◽  
pp. 179 ◽  
Author(s):  
Yanan Jiang ◽  
Mingsheng Liao ◽  
Zhiwei Zhou ◽  
Xuguo Shi ◽  
Lu Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Data Assimilation ◽  
Deformation Analysis ◽  
Landslide Deformation ◽  
Sar Data ◽  
Coupling Deformation

scholarly journals A global historical Radiosondes and Tracked Balloons Archive on standard pressure levels back to the 1920s

2013 ◽  
Vol 6 (2) ◽  
pp. 837-874 ◽  
Author(s):  
L. Ramella Pralungo ◽  
L. Haimberger ◽  
A. Stickler ◽  
S. Brönnimann
Keyword(s):  
Time Series ◽  
Three Dimensional ◽  
Forthcoming Paper ◽  
Radiosonde Data ◽  
Free Atmosphere ◽  
Climate Anomalies ◽  
Merging Procedure ◽  
Standard Pressure ◽  
Climate Studies ◽  
The Eu

Abstract. Long observed time series of climate state quantities are needed to extend our understanding of global weather, climate variability and monitoring not only at the Earths surface but also the free atmosphere, since climate anomalies and climate change have a three-dimensional spatial structure. Radiosonde data before 1958 and tracked balloon (PILOT) data are rarely available at standard times on standard pressure levels, which complicates their use for climate studies. This paper describes an upper air dataset on standard pressure levels at 00:00 GMT and 12:00 GMT for parameters temperature and wind. The input data sources of this dataset are the Comprehensive Historical Upper Air Network (CHUAN version 1.7), the Integrated Global Radiosonde Archive (IGRA) and upper air observations from the reanalysis datasets ERA-40 and ERA-Interim. As such it contains many data that have been digitized and collected in the EU FP7 project ERA-CLIM. Those data, which partly exist at asynoptic times and on altitude levels instead of pressure levels, have been brought to synoptic times and standard pressure levels using state of the art interpolation techniques, employing geopotential information National Oceanic and Atmosphere Administration (NOAA) 20th Century Reanalysis (NOAA 20CR) to aid the interpolation. The standardized time series have been merged if necessary, taking care that the data are traceable back to their original sources. Only time series longer than 300 days have been saved in the merged archive, since the main purpose of this dataset is to aid climatological studies. If possible WMO numbers have been given to the station records. For some records which have never been identified by a WMO number, a local ID above 100 000 has been attached. This paper describes the merging procedure, data count and data quality and how traceability of the data is ensured. It does not describe a homogenization procedure for both temperature and wind data. Homogeneity adjustments for both temperature and wind will be provided in a forthcoming paper. All the archives and metadata files are available in the PANGAEA archive with associated DOI http://doi.pangaea.de/10.1594/PANGAEA.823617. If users prefer netCDF files, they can be downloaded via http://www.univie.ac.at/theoret-met/research/raobcore/.

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