Scientific article
OA Policy
English

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

Published inData, vol. 4, no. 3, 93
Publication date2019
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
Citation (ISO format)
TRUCKENBRODT, John et al. Towards Sentinel-1 SAR Analysis-Ready Data: A Best Practices Assessment on Preparing Backscatter Data for the Cube. In: Data, 2019, vol. 4, n° 3, p. 93. doi: 10.3390/data4030093
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Article (Published version)
Identifiers
Additional URL for this publicationhttps://www.mdpi.com/2306-5729/4/3/93
Journal ISSN2306-5729
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Technical informations

Creation07/05/2019 8:26:00 PM
First validation07/05/2019 8:26:00 PM
Update time03/15/2023 5:44:50 PM
Status update03/15/2023 5:44:49 PM
Last indexation10/31/2024 1:45:31 PM
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