OSARIS, the “Open Source SAR Investigation System” for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications
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 tempor...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2019-07-01
|
| Series: | Frontiers in Earth Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/feart.2019.00172/full |
| _version_ | 1818082297443778560 |
|---|---|
| author | David Loibl Bodo Bookhagen Sébastien Valade Christoph Schneider |
| author_facet | David Loibl Bodo Bookhagen Sébastien Valade Christoph Schneider |
| author_sort | David Loibl |
| collection | DOAJ |
| description | 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. Methods are needed to efficiently detect short term changes in dynamic environments. Approaches considering pair-wise processing of a series of consecutive scenes to retain maximum temporal resolution in conjunction with time series analyses are required. Here we present OSARIS, the “Open Source SAR Investigation System,” as a framework to process large stacks of S1 data on high-performance computing clusters. Based on Generic Mapping Tools SAR, shell scripts, and the workload manager Slurm, OSARIS provides an open and modular framework combining parallelization of high-performance C programs, flexible 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. The capabilities of OSARIS are demonstrated 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 input scenes. The coherence time series exhibits pronounced seasonal variability, with relatively high coherence values prevailing during the summer months in the nival zone. As an example of a time series analysis module, we present OSARIS' “Unstable Coherence Metric” which identifies pixels affected by significant drops from high to low coherence values. Measurements of motion provided by LOSD measurements require careful evaluation because interferometric phase unwrapping is prone to errors. Here, OSARIS provides a series of modules to detect and mask unwrapping errors, correct for atmospheric disturbances, and remove large-scale trends. Wall clock processing time for the case study (area ~9,000 km2) was ~12 h 4 min on a machine with 400 cores and 2 TB RAM. In total, ~12 d 10 h 44 min (~96%) were saved through parallelization. A comparison of selected OSARIS datasets to results from two state-of-the-art SAR processing suites, ISCE and SNAP, shows that OSARIS provides products of competitive quality despite its high level of automatization. OSARIS thus facilitates efficient S1-based region-wide investigations of surface movement events over multiple years. |
| first_indexed | 2024-12-10T19:19:52Z |
| format | Article |
| id | doaj.art-8557d7d3f21c449a8bbfe2b2e702c08e |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-12-10T19:19:52Z |
| publishDate | 2019-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-8557d7d3f21c449a8bbfe2b2e702c08e2022-12-22T01:36:31ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632019-07-01710.3389/feart.2019.00172451152OSARIS, the “Open Source SAR Investigation System” for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere ApplicationsDavid Loibl0Bodo Bookhagen1Sébastien Valade2Christoph Schneider3Climate Geography, Geography Department, Humboldt-Universität zu Berlin, Berlin, GermanyGeological Remote Sensing, Institute of Geosciences, University of Potsdam, Potsdam, GermanyComputer Vision and Remote Sensing, Department of Computer Engineering and Microelectronics, Technische Universität Berlin, Berlin, GermanyClimate Geography, Geography Department, Humboldt-Universität zu Berlin, Berlin, GermanyWith 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. Methods are needed to efficiently detect short term changes in dynamic environments. Approaches considering pair-wise processing of a series of consecutive scenes to retain maximum temporal resolution in conjunction with time series analyses are required. Here we present OSARIS, the “Open Source SAR Investigation System,” as a framework to process large stacks of S1 data on high-performance computing clusters. Based on Generic Mapping Tools SAR, shell scripts, and the workload manager Slurm, OSARIS provides an open and modular framework combining parallelization of high-performance C programs, flexible 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. The capabilities of OSARIS are demonstrated 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 input scenes. The coherence time series exhibits pronounced seasonal variability, with relatively high coherence values prevailing during the summer months in the nival zone. As an example of a time series analysis module, we present OSARIS' “Unstable Coherence Metric” which identifies pixels affected by significant drops from high to low coherence values. Measurements of motion provided by LOSD measurements require careful evaluation because interferometric phase unwrapping is prone to errors. Here, OSARIS provides a series of modules to detect and mask unwrapping errors, correct for atmospheric disturbances, and remove large-scale trends. Wall clock processing time for the case study (area ~9,000 km2) was ~12 h 4 min on a machine with 400 cores and 2 TB RAM. In total, ~12 d 10 h 44 min (~96%) were saved through parallelization. A comparison of selected OSARIS datasets to results from two state-of-the-art SAR processing suites, ISCE and SNAP, shows that OSARIS provides products of competitive quality despite its high level of automatization. OSARIS thus facilitates efficient S1-based region-wide investigations of surface movement events over multiple years.https://www.frontiersin.org/article/10.3389/feart.2019.00172/fullremote sensingInSARhigh mountain environmentsrock glaciersentinel-1time series analysis |
| spellingShingle | David Loibl Bodo Bookhagen Sébastien Valade Christoph Schneider OSARIS, the “Open Source SAR Investigation System” for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications Frontiers in Earth Science remote sensing InSAR high mountain environments rock glacier sentinel-1 time series analysis |
| title | OSARIS, the “Open Source SAR Investigation System” for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications |
| title_full | OSARIS, the “Open Source SAR Investigation System” for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications |
| title_fullStr | OSARIS, the “Open Source SAR Investigation System” for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications |
| title_full_unstemmed | OSARIS, the “Open Source SAR Investigation System” for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications |
| title_short | OSARIS, the “Open Source SAR Investigation System” for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications |
| title_sort | osaris the open source sar investigation system for automatized parallel insar processing of sentinel 1 time series data with special emphasis on cryosphere applications |
| topic | remote sensing InSAR high mountain environments rock glacier sentinel-1 time series analysis |
| url | https://www.frontiersin.org/article/10.3389/feart.2019.00172/full |
| work_keys_str_mv | AT davidloibl osaristheopensourcesarinvestigationsystemforautomatizedparallelinsarprocessingofsentinel1timeseriesdatawithspecialemphasisoncryosphereapplications AT bodobookhagen osaristheopensourcesarinvestigationsystemforautomatizedparallelinsarprocessingofsentinel1timeseriesdatawithspecialemphasisoncryosphereapplications AT sebastienvalade osaristheopensourcesarinvestigationsystemforautomatizedparallelinsarprocessingofsentinel1timeseriesdatawithspecialemphasisoncryosphereapplications AT christophschneider osaristheopensourcesarinvestigationsystemforautomatizedparallelinsarprocessingofsentinel1timeseriesdatawithspecialemphasisoncryosphereapplications |