Mekong SAR Interferometry Big Data: Preliminary Results

Author(s):  
D. Ho Tong Minh ◽  
T.-C. Le ◽  
Y.-N. Ngo ◽  
C.-C. Nguyen ◽  
T.-A. Pham ◽  
...  
2020 ◽  
Vol 12 (9) ◽  
pp. 1364 ◽  
Author(s):  
Dinh HO TONG MINH ◽  
Ramon Hanssen ◽  
Fabio Rocca

The research and improvement of methods to be used for deformation measurements from space is a challenge. From the previous 20 years, time series Synthetic Aperture Radar (SAR) interferometry techniques have proved for their ability to provide millimeter-scale deformation measurements over time. This paper aims to provide a review of such techniques developed in the last twenty years. We first recall the background of interferometric SAR (InSAR). We then provide an overview of the InSAR time series methods developed in the literature, describing their principles and advancements. Finally, we highlight challenges and future perspectives of the InSAR in the Big Data era.


Author(s):  
Karin Hagoort ◽  
Peter Deschamps ◽  
Floortje E. Scheepers
Keyword(s):  
Big Data ◽  

10.29007/tvck ◽  
2019 ◽  
Author(s):  
Anna Novoselova ◽  
Alexander Kostyrkin

The Japanese language has a great variety of verb inflectional suffixes (auxiliaries), each having conjugation of their own. In this paper we propose a corpus-based approach to studying Japanese verb paradigms. Such an approach benefits from identifying possible verb forms on big data of written language. Description of methods and tools used for building databases of verbs and auxiliaries and for parsing verb 7-grams from a Japanese N-gram Corpus is presented.


2017 ◽  
Vol 43 (3) ◽  
pp. 1301
Author(s):  
I. Parcharidis ◽  
M. Foumelis ◽  
P. Kourkouli

Space borne differential synthetic aperture radar interferometry (DInSAR) has already proven its potential for mapping ground deformation phenomena, e.g. earthquakes, volcano dynamics, etc covering in continuity large areas. The innovative Persistent Scatterers Interferometry (PSI) technique, which overcomes several limitations of conventional SAR differential interferometry especially for applications in landslide studies, is suitable for monitoring slope deformations with millimetric precision. With PSI technique we detect the deformation, for long periods, that occur in an area as average annual deformation (mm/y) and is not spatially continuous but in terms of points (point targets). The aim of this study is to present preliminary results on the monitoring of slope instability in Panachaiko Mountain and particularly of the slopes facing the city of Patras. For this purpose we processed and analysed 42 ERS 1 and ERS 2 SAR scenes acquired in the time span 1992 and 2001, by applying the Interferometric Point Target Analysis algorithm. Point target reflectors with stable radar response over time were selected. In this case most of the point targets correspond to buildings of the local settlements or to rock outcrops. Additionally, millimetric target displacements along the line of sight direction were detected allowing measurements of slow terrain motion.


2016 ◽  
Vol 39 (1) ◽  
pp. 78-94 ◽  
Author(s):  
Lorraine J. Phillips ◽  
Chelsea B. DeRoche ◽  
Marilyn Rantz ◽  
Gregory L. Alexander ◽  
Marjorie Skubic ◽  
...  

This study explored using Big Data, totaling 66 terabytes over 10 years, captured from sensor systems installed in independent living apartments to predict falls from pre-fall changes in residents’ Kinect-recorded gait parameters. Over a period of 3 to 48 months, we analyzed gait parameters continuously collected for residents who actually fell ( n = 13) and those who did not fall ( n = 10). We analyzed associations between participants’ fall events ( n = 69) and pre-fall changes in in-home gait speed and stride length ( n = 2,070). Preliminary results indicate that a cumulative change in speed over time is associated with the probability of a fall ( p < .0001). The odds of a resident falling within 3 weeks after a cumulative change of 2.54 cm/s is 4.22 times the odds of a resident falling within 3 weeks after no change in in-home gait speed. Results demonstrate using sensors to measure in-home gait parameters associated with the occurrence of future falls.


2018 ◽  
Author(s):  
Dominik Moritz ◽  
Danyel Fisher ◽  
Bolin Ding ◽  
Chi Wang

Analysts need interactive speed for exploratory analysis, but big data systems are often slow. With sampling, data systems can produce approximate answers fast enough for exploratory visualization, at the cost of accuracy and trust. We propose optimistic visualization, which approaches these issues from a user experience perspective. This method lets analysts explore approximate results interactively, and provides a way to detect and recover from errors later. Pangloss implements these ideas. We discuss design issues raised by optimistic visualization systems. We test this concept with five expert visualizers in a laboratory study and three case studies at Microsoft. Analysts reported that they felt more confident in their results, and used optimistic visualization to check that their preliminary results were correct.


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