Towards Sentinel-1 SAR Analysis-Ready Data: A Best Practices Assessment on Preparing Backscatter Data for the Cube

John Truckenbrodt, Terri Freemantle, Chris Williams, Tom Jones, David Small, Clémence Dubois, Christian Thiel, Cristian Rossi, Asimina Syriou and Gregory Giuliani
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John Truckenbrodt: Department for Earth Observation, Friedrich-Schiller-University Jena, 07743 Jena, Germany
Terri Freemantle: Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK
Chris Williams: Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK
Tom Jones: Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK
David Small: Remote Sensing Laboratories, Dept. of Geography, University of Zurich, 8057 Zurich, Switzerland
Clémence Dubois: Department for Earth Observation, Friedrich-Schiller-University Jena, 07743 Jena, Germany
Christian Thiel: Institute for Data Science, German Aerospace Center DLR, 07745 Jena, Germany
Cristian Rossi: Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK
Asimina Syriou: Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK
Gregory Giuliani: Institute for Environmental Sciences, University of Geneva, 1205 Geneva, Switzerland

Data, 2019, vol. 4, issue 3, 1-37

Abstract: This study aims at assessing the feasibility of automatically producing analysis-ready radiometrically terrain-corrected (RTC) Synthetic Aperture Radar (SAR) gamma nought backscatter data for ingestion into a data cube for use in a large spatio-temporal data environment. As such, this study investigates the analysis readiness of different openly available digital elevation models (DEMs) and the capability of the software solutions SNAP and GAMMA in terms of overall usability as well as backscatter data quality. To achieve this, the study builds on the Python library pyroSAR for providing the workflow implementation test bed and provides a Jupyter notebook for transparency and future reproducibility of performed analyses. Two test sites were selected, over the Alps and Fiji, to be able to assess regional differences and support the establishment of the Swiss and Common Sensing Open Data cubes respectively.

Keywords: Sentinel-1; SAR; analysis ready data; ARD; interoperability; data cube; Earth observation; pyroSAR (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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