scholarly journals GECORIS: An Open-Source Toolbox for Analyzing Time Series of Corner Reflectors in InSAR Geodesy

2021 ◽  
Vol 13 (5) ◽  
pp. 926
Author(s):  
Richard Czikhardt ◽  
Hans van der Marel ◽  
Juraj Papco
Keyword(s):  
Time Series ◽  
Open Source ◽  
Open Source Software ◽  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Sensor Calibration ◽  
Corner Reflector ◽  
Debris Accumulation ◽  
Automatic Estimation ◽  
Phase Variance

Artificial radar reflectors, such as corner reflectors or transponders, are commonly used for radiometric and geometric Synthetic Aperture Radar (SAR) sensor calibration, SAR interferometry (InSAR) applications over areas with few natural coherent scatterers, and InSAR datum connection and geodetic integration. Despite the current abundance of regular SAR time series, no free and open-source software (FOSS) dedicated to analyzing SAR time series of artificial radar reflectors exists. In this paper, we present a FOSS Python toolbox for efficient and automatic estimation of: (i) the clutter level of a particular site before a corner reflector installation, (ii) the Radar Cross Section (RCS) to track a corner reflector’s performance and detect outliers, for example, due to damage or debris accumulation, (iii) the Signal-to-Clutter Ratio (SCR) to predict the positioning precision and the InSAR phase variance, (iv) the InSAR displacement time series of a corner reflector network. We use the toolbox to analyze Sentinel-1 SAR time series of the network of 23 corner reflectors for InSAR monitoring of landslides in Slovakia.

scholarly journals LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

2020 ◽  
Vol 12 (3) ◽  
pp. 424 ◽  
Author(s):  
Yu Morishita ◽  
Milan Lazecky ◽  
Tim Wright ◽  
Jonathan Weiss ◽  
John Elliott ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Open Source ◽  
Large Scale ◽  
Surface Deformation ◽  
Atmospheric Correction ◽  
Sar Interferometry ◽  
Processing Scheme ◽  
Series Analysis ◽  
Analysis Package

For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (~km) relative displacements with an accuracy of <1 cm/epoch and ~2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.

scholarly journals Radar Interferometry: 20 Years of Development in Time Series Techniques and Future Perspectives

2020 ◽  
Vol 12 (9) ◽  
pp. 1364 ◽  
Author(s):  
Dinh HO TONG MINH ◽  
Ramon Hanssen ◽  
Fabio Rocca
Keyword(s):  
Time Series ◽  
Big Data ◽  
Synthetic Aperture Radar ◽  
Radar Interferometry ◽  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Future Perspectives ◽  
Interferometric Sar ◽  
Deformation Measurements ◽  
Over Time

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.

scholarly journals Pastas: Open Source Software for the Analysis of Groundwater Time Series

Ground Water ◽  
2019 ◽  
Vol 57 (6) ◽  
pp. 877-885 ◽  
Author(s):  
Raoul A. Collenteur ◽  
Mark Bakker ◽  
Ruben Caljé ◽  
Stijn A. Klop ◽  
Frans Schaars
Keyword(s):  
Time Series ◽  
Open Source ◽  
Open Source Software

scholarly journals Understanding Open Source Software Evolution Using Fuzzy Data Mining Algorithm for Time Series Data

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Munish Saini ◽  
Sandeep Mehmi ◽  
Kuljit Kaur Chahal
Keyword(s):  
Data Mining ◽  
Time Series ◽  
Open Source ◽  
Open Source Software ◽  
Time Series Data ◽  
Series Data ◽  
Software Project ◽  
Data Mining Algorithm ◽  
Fuzzy Data ◽  
Mining Algorithm

Source code management systems (such as Concurrent Versions System (CVS), Subversion, and git) record changes to code repositories of open source software projects. This study explores a fuzzy data mining algorithm for time series data to generate the association rules for evaluating the existing trend and regularity in the evolution of open source software project. The idea to choose fuzzy data mining algorithm for time series data is due to the stochastic nature of the open source software development process. Commit activity of an open source project indicates the activeness of its development community. An active development community is a strong contributor to the success of an open source project. Therefore commit activity analysis along with the trend and regularity analysis for commit activity of open source software project acts as an important indicator to the project managers and analyst regarding the evolutionary prospects of the project in the future.

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