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

1
Department for Earth Observation, Friedrich-Schiller-University Jena, 07743 Jena, Germany
2
Institute for Data Science, German Aerospace Center DLR, 07745 Jena, Germany
3
Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK
4
Remote Sensing Laboratories, Dept. of Geography, University of Zurich, 8057 Zurich, Switzerland
5
Institute for Environmental Sciences, University of Geneva, 1205 Geneva, Switzerland
*
Author to whom correspondence should be addressed.
Received: 15 June 2019 / Revised: 2 July 2019 / Accepted: 2 July 2019 / Published: 5 July 2019
(This article belongs to the Special Issue Earth Observation Data Cubes)
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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. View Full-Text
Keywords: Sentinel-1; SAR; analysis ready data; ARD; interoperability; data cube; Earth observation; pyroSAR Sentinel-1; SAR; analysis ready data; ARD; interoperability; data cube; Earth observation; pyroSAR
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Truckenbrodt, J.; Freemantle, T.; Williams, C.; Jones, T.; Small, D.; Dubois, C.; Thiel, C.; Rossi, C.; Syriou, A.; Giuliani, G. Towards Sentinel-1 SAR Analysis-Ready Data: A Best Practices Assessment on Preparing Backscatter Data for the Cube. Data 2019, 4, 93.

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