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Dataset

OSARIS Sentinel-1 InSAR processing results for the Ala-Archa Region, Kyrgyzstan, December 2015 to April 2019

Cite as:

Loibl, David (2019): OSARIS Sentinel-1 InSAR processing results for the Ala-Archa Region, Kyrgyzstan, December 2015 to April 2019. GFZ Data Services. https://doi.org/10.5880/fidgeo.2019.016

Status

I   N       R   E   V   I   E   W : Loibl, David (2019): OSARIS Sentinel-1 InSAR processing results for the Ala-Archa Region, Kyrgyzstan, December 2015 to April 2019. GFZ Data Services. https://doi.org/10.5880/fidgeo.2019.016

Abstract

With the advent of the two Sentinel-1 (S1) satellites, Synthetic Aperture Radar (SAR) data with high temporal and spatial resolution are freely available. This provides a promising framework to facilitate detailed investigations of surface instabilities and movements on large scales with high temporal resolution, but also poses substantial processing challenges because of storage and computation requirements. Here we present OSARIS, the ‘Open Source SAR Investigation System’, as a framework to process large stacks of S1 data on High-Performance Computing (HPC) clusters. Based on GMTSAR, shell scripts, and the workload manager Slurm, OSARIS provides an open and modular framework combining parallelization of high-performance C programs, flexibility of processing schemes, convenient configuration, and generation of geocoded stacks of analysis-ready base data, including amplitude, phase, coherence, and unwrapped interferograms. Time series analyses can be conducted by applying automated modules to the data stacks.


Here, a demonstration dataset is presented that was generated using OSARIS in a case study from the northwestern Tien Shan, Central Asia. After merging of slices, a total of 80 scene pairs were processed from 174 total S1 input scenes. This archive contains full time series in original resolution of ~31 m for selected OSARIS interferometric processing results, i.e. amplitude, coherence, connected components, interferometric phase, line-of-sight displacement, sums of forward plus reverse pair unwrapped interferograms, and 'Unstable Coherence Metric'. In addition, results from the coherence-based 'Stable Ground Point Identification' module and coherence statistics for time series of selected subregions and landforms discussed in the associated publication are included.


Wall clock processing time for the case study (area ~9,000 km²) was ~12h:04m on a machine with 400 cores and two TB RAM. In total, ~12d:10h:44m were saved through parallelization. OSARIS thus facilitates efficient S1-based region-wide investigations of surface movement events over multiple years.

Methods

All data in this archive were processed using the Open Source SAR Investigation System (OSARIS; https://github.com/cryotools/osaris) v. 0.7.2. Processing was conducted on the Cirrus Cluster at the Climate Geography department, Humboldt-Universität zu Berlin. Input data were ESA Sentinel-1 IW SLC files.

Authors

  • Loibl, David;Humboldt-Universität zu Berlin, Berlin, Germany

Contact

Keywords

HPC computing, SAR interferometry, Surface movement, Time series

GCMD Science Keywords

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    Files

    License: CC BY 4.0

    Dataset Description

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