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LiCSBAS

  • 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 withFor 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.zeige mehrzeige weniger

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Verfasserangaben:Yu MorishitaORCiD, Milan LazeckyORCiD, Tim J. WrightORCiDGND, Jonathan R. WeissORCiD, John R. ElliottORCiD, Andy Hooper
URN:urn:nbn:de:kobv:517-opus4-472431
DOI:https://doi.org/10.25932/publishup-47243
ISSN:1866-8372
Titel des übergeordneten Werks (Deutsch):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
Untertitel (Englisch):An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor
Schriftenreihe (Bandnummer):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (1078)
Publikationstyp:Postprint
Sprache:Englisch
Datum der Erstveröffentlichung:07.01.2021
Erscheinungsjahr:2020
Veröffentlichende Institution:Universität Potsdam
Datum der Freischaltung:07.01.2021
Freies Schlagwort / Tag:InSAR; Sentinel-1; automatic processing; deformation monitoring; global; subsidence; tectonics; time series analysis
Ausgabe:1078
Seitenanzahl:31
Quelle:Remote sensing 12 (2020) 3, Art. 424 DOI: 10.3390/rs12030424
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC-Klassifikation:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
Peer Review:Referiert
Fördermittelquelle:Multidisciplinary Digital Publishing Institute (MDPI)
Publikationsweg:Open Access / Green Open-Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
Externe Anmerkung:Bibliographieeintrag der Originalveröffentlichung/Quelle
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