Corner Reflector Network as a Geodetic Reference for Landslide Monitoring via InSAR Time Series: Case Study from Slovakia

2021 ◽  
Author(s):  
Richard Czikhardt ◽  
Juraj Papco ◽  
Peter Ondrejka ◽  
Peter Ondrus ◽  
Pavel Liscak
Keyword(s):  
Time Series ◽  
Horizontal Displacement ◽  
Terrestrial Reference Frame ◽  
Sar Interferometry ◽  
Global Navigation Satellite Systems ◽  
Reference Network ◽  
Landslide Monitoring ◽  
First Order ◽  
Order Estimation ◽  
Better Than

<p>SAR interferometry (InSAR) is inherently a relative geodetic technique requiring one temporal and one spatial reference to obtain the datum-free estimates on millimetre-level displacements within the network of radar scatterers. To correct the systematic errors, such as the varying atmospheric delay, and solve the phase ambiguities, it relies on the first-order estimation network of coherent point scatterers (PS).</p><p>For vegetated and sparsely urbanized areas, commonly affected by landslides in Slovakia, it is often difficult to construct a reliable first-order estimation network, as they lack the PS. Purposedly deploying corner reflectors (CR) at such areas strengthens the estimation network and, if these CR are collocated with a Global Navigation Satellite Systems (GNSS), they provide an absolute geodetic reference to a well-defined terrestrial reference frame (TRF), as well as independent quality control.</p><p>For landslides, line-of-sight (LOS) InSAR displacements can be difficult to interpret. Using double CR, i.e. two reflectors for ascending/descending geometries within a single instrument, enables the assumption-less decomposition of the observed cross-track LOS displacements into the vertical and the horizontal displacement components.</p><p>In this study, we perform InSAR analysis on the one-year of Sentinel-1 time series of five areas in Slovakia, affected by landslides. 24 double back-flipped trihedral CR were carefully deployed at these sites to form a reference network, guaranteeing reliable displacement information over the critical landslide zones. To confirm the measurement quality, we show that the temporal average Signal-to-Clutter Ratio (SCR) of the CR is better than 20 dB. The observed CR motions in vertical and east-west directions vary from several millimetres up to 3 centimetres, with average standard deviation better than 0.5 mm.<br>Repeated GNSS measurements of the CR confirm the displacement observed by the InSAR, improve the positioning precision of the nearby PS, and attain the transformation into the national TRF.</p>

scholarly journals MT-INSAR LANDSLIDE MONITORING WITH THE AID OF HOMOGENEOUS PIXELS FILTER

2018 ◽  
Vol XLII-3 ◽  
pp. 1135-1139
Author(s):  
X. J. Liu ◽  
C. Y. Zhao ◽  
B. H. Wang ◽  
W. F. Zhu
Keyword(s):  
Time Series ◽  
Rainy Season ◽  
Small Scale ◽  
Landslide Monitoring ◽  
Loess Landslide ◽  
Temporal Decorrelation ◽  
Gps Time Series ◽  
Better Than

SAR interferograms are often contaminated by random noises related to temporal decorrelation, geometrical decorrelation and thermal noises, which makes the fringes obscured and greatly decreases the density of the coherent target and the accuracy of InSAR deformation results, especially for the landslide monitoring in vegetated region and in rainy season. Two different SAR interferogram filtering methods, that is Goldstein filter and homogeneous pixels filter, for one specific landslide are compared. The results show that homogeneous pixels filter is better than Goldstein one for small-scale loess landslide monitoring, which can increase the density of monitoring points. Moreover, the precision of InSAR result can reach millimeter by comparing with GPS time series measurements.

scholarly journals Empirical Insights from a Study on Outlier Preserving Value Generalization in Animated Choropleth Maps

2021 ◽  
Vol 10 (4) ◽  
pp. 208
Author(s):  
Christoph Traun ◽  
Manuela Larissa Schreyer ◽  
Gudrun Wallentin
Keyword(s):  
Time Series ◽  
Empirical Research ◽  
Global Trends ◽  
First Order ◽  
Choropleth Maps ◽  
Temporal Generalization ◽  
Perceptual Limits ◽  
Local Outlier

Time series animation of choropleth maps easily exceeds our perceptual limits. In this empirical research, we investigate the effect of local outlier preserving value generalization of animated choropleth maps on the ability to detect general trends and local deviations thereof. Comparing generalization in space, in time, and in a combination of both dimensions, value smoothing based on a first order spatial neighborhood facilitated the detection of local outliers best, followed by the spatiotemporal and temporal generalization variants. We did not find any evidence that value generalization helps in detecting global trends.

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.

scholarly journals Adversarial Unsupervised Representation Learning for Activity Time-Series

2019 ◽  
Vol 33 ◽  
pp. 834-841 ◽  
Author(s):  
Karan Aggarwal ◽  
Shafiq Joty ◽  
Luis Fernandez-Luque ◽  
Jaideep Srivastava
Keyword(s):  
Time Series ◽  
Chronic Conditions ◽  
Empirical Evaluation ◽  
Representation Learning ◽  
Time Segment ◽  
Linear Classifiers ◽  
Daily Routines ◽  
Learning Technique ◽  
Prevention And Cure ◽  
Better Than

Sufficient physical activity and restful sleep play a major role in the prevention and cure of many chronic conditions. Being able to proactively screen and monitor such chronic conditions would be a big step forward for overall health. The rapid increase in the popularity of wearable devices pro-vides a significant new source, making it possible to track the user’s lifestyle real-time. In this paper, we propose a novel unsupervised representation learning technique called activ-ity2vecthat learns and “summarizes” the discrete-valued ac-tivity time-series. It learns the representations with three com-ponents: (i) the co-occurrence and magnitude of the activ-ity levels in a time-segment, (ii) neighboring context of the time-segment, and (iii) promoting subject-invariance with ad-versarial training. We evaluate our method on four disorder prediction tasks using linear classifiers. Empirical evaluation demonstrates that our proposed method scales and performs better than many strong baselines. The adversarial regime helps improve the generalizability of our representations by promoting subject invariant features. We also show that using the representations at the level of a day works the best since human activity is structured in terms of daily routines.

scholarly journals Municipal Leachate Treatment by Fenton Process: Effect of Some Variable and Kinetics

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Mohammad Ahmadian ◽  
Sohyla Reshadat ◽  
Nader Yousefi ◽  
Seyed Hamed Mirhossieni ◽  
Mohammad Reza Zare ◽  
...  
Keyword(s):  
Reaction Time ◽  
Color Removal ◽  
Molar Ratio ◽  
Order Kinetic ◽  
Fenton Process ◽  
Solution Ph ◽  
Leachate Treatment ◽  
First Order ◽  
Order Kinetic Model ◽  
Better Than

Due to complex composition of leachate, the comprehensive leachate treatment methods have been not demonstrated. Moreover, the improper management of leachate can lead to many environmental problems. The aim of this study was application of Fenton process for decreasing the major pollutants of landfill leachate on Kermanshah city. The leachate was collected from Kermanshah landfill site and treated by Fenton process. The effect of various parameters including solution pH, Fe2+and H2O2dosage, Fe2+/H2O2molar ratio, and reaction time was investigated. The result showed that with increasing Fe2+and H2O2dosage, Fe2+/H2O2molar ratio, and reaction time, the COD, TOC, TSS, and color removal increased. The maximum COD, TOC, TSS, and color removal were obtained at low pH (pH: 3). The kinetic data were analyzed in term of zero-order, first-order, and second-order expressions. First-order kinetic model described the removal of COD, TOC, TSS, and color from leachate better than two other kinetic models. In spite of extremely difficulty of leachate treatment, the previous results seem rather encouraging on the application of Fenton’s oxidation.

The Contribution of LARES to Global Climate Change Studies With Geodetic Satellites

2015 ◽  
Author(s):  
Giampiero Sindoni ◽  
Claudio Paris ◽  
Cristian Vendittozzi ◽  
Erricos C. Pavlis ◽  
Ignazio Ciufolini ◽  
...  
Keyword(s):  
Reference Frame ◽  
Earth Science ◽  
Global Climate ◽  
Temporal Variations ◽  
Terrestrial Reference Frame ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Long Baseline ◽  
Geophysical Processes ◽  
Global Navigation Satellite

Satellite Laser Ranging (SLR) makes an important contribution to Earth science providing the most accurate measurement of the long-wavelength components of Earth’s gravity field, including their temporal variations. Furthermore, SLR data along with those from the other three geometric space techniques, Very Long Baseline Interferometry (VLBI), Global Navigation Satellite Systems (GNSS) and DORIS, generate and maintain the International Terrestrial Reference Frame (ITRF) that is used as a reference by all Earth Observing systems and beyond. As a result we obtain accurate station positions and linear velocities, a manifestation of tectonic plate movements important in earthquake studies and in geophysics in general. The “geodetic” satellites used in SLR are passive spheres characterized by very high density, with little else than gravity perturbing their orbits. As a result they define a very stable reference frame, defining primarily and uniquely the origin of the ITRF, and in equal shares, its scale. The ITRF is indeed used as “the” standard to which we can compare regional, GNSS-derived and alternate frames. The melting of global icecaps, ocean and atmospheric circulation, sea-level change, hydrological and internal Earth-mass redistribution are nowadays monitored using satellites. The observations and products of these missions are geolocated and referenced using the ITRF. This allows scientists to splice together records from various missions sometimes several years apart, to generate useful records for monitoring geophysical processes over several decades. The exchange of angular momentum between the atmosphere and solid Earth for example is measured and can be exploited for monitoring global change. LARES, an Italian Space Agency (ASI) satellite, is the latest geodetic satellite placed in orbit. Its main contribution is in the area of geodesy and the definition of the ITRF in particular and this presentation will discuss the improvements it will make in the aforementioned areas.

scholarly journals Demand forecasting in Small and Medium Enterprises (SMEs) ED Aluminium Yogyakarta using causal, time series, and combined causal-time series approaches

2018 ◽  
Vol 204 ◽  
pp. 01004 ◽  
Author(s):  
Wildanul Isnaini ◽  
Andi Sudiarso
Keyword(s):  
Time Series ◽  
Small And Medium Enterprises ◽  
Demand Forecasting ◽  
Actual Condition ◽  
Inventory Data ◽  
Inventory Cost ◽  
Forecasting Method ◽  
Medium Enterprises ◽  
Better Than

ED Aluminium is the biggest Small and Medium Enterprises (SMEs) in Daerah Istimewa Yogyakarta (DIY) with 90 number of workers and 1,5 ton ingot capacity for production (Isnaini, 2014). Inventory data in December 2015 indicates that some products are overstocked (9%) and stockout (83%). This condition can happend because that SMEs still using intuition to predict the number of demand. Inventory fluctuation causes the inventory cost increases while overstock happend and lost the opportunity cost during stockout. To avoid overstock and stockout, the determination of demand with exact method is needed and one of them can be solved by forecasting method. This study aims to find the best forecasting methods of demand in 2015 using causal, time series, and combined causal-time series approces that better than the actual condition. The results of this research is the best forecasting method used to predict the number of sales in January-November 2015, that are SARIMA (3,1,1)(0,1,1)12 for WB, SARIMA (1,1,1)(1,0,1)6 for WSD, SARIMA (1,1,1)(1,1,0)6 for DE, SARIMA (2,1,1)(1,1,0)6 for PE, and SARIMA (2,1,3)(0,1,0)12 for PT.

scholarly journals Sentinel-1 SAR Interferometry for Surface Deformation Monitoring in Low-Land Permafrost Areas

2018 ◽  
Vol 10 (9) ◽  
pp. 1360 ◽  
Author(s):  
Tazio Strozzi ◽  
Sofia Antonova ◽  
Frank Günther ◽  
Eva Mätzler ◽  
Gonçalo Vieira ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Displacement ◽  
Deformation Monitoring ◽  
In Situ Measurements ◽  
River Delta ◽  
Sar Interferometry ◽  
The Arctic ◽  
Lena River ◽  
Lena River Delta

Low-land permafrost areas are subject to intense freeze-thaw cycles and characterized by remarkable surface displacement. We used Sentinel-1 SAR interferometry (InSAR) in order to analyse the summer surface displacement over four spots in the Arctic and Antarctica since 2015. Choosing floodplain or outcrop areas as the reference for the InSAR relative deformation measurements, we found maximum subsidence of about 3 to 10 cm during the thawing season with generally high spatial variability. Sentinel-1 time-series of interferograms with 6–12 day time intervals highlight that subsidence is often occurring rather quickly within roughly one month in early summer. Intercomparison of summer subsidence from Sentinel-1 in 2017 with TerraSAR-X in 2013 over part of the Lena River Delta (Russia) shows a high spatial agreement between both SAR systems. A comparison with in-situ measurements for the summer of 2014 over the Lena River Delta indicates a pronounced downward movement of several centimetres in both cases but does not reveal a spatial correspondence between InSAR and local in-situ measurements. For the reconstruction of longer time-series of deformation, yearly Sentinel-1 interferograms from the end of the summer were considered. However, in order to infer an effective subsidence of the surface through melting of excess ice layers over multi-annual scales with Sentinel-1, a longer observation time period is necessary.

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