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pyroSAR: a python package to provide Sentinel-1 time series in data cubes

Cremer, Felix and Truckenbrodt, John and Baris, Ismail and Eberle, Jonas (2019) pyroSAR: a python package to provide Sentinel-1 time series in data cubes. ESA Phi Week, 09-13 Sept 2019, Frascati, Italy.

Full text not available from this repository.

Abstract

To increase the uptake of synthetic aperture radar (SAR) data it is crucial to ease the preprocessing thereof. Optimally, a user is presented with a standardized data cube ready for analysis without further knowledge of SAR processing details. pyroSAR addresses this need by providing a complete workflow from retrieving the raw data from its provider to filled data cubes ready for analysis. pyroSAR is harmonizing the metadata of multiple SAR data formats for relevant parameters like acquisition time or relative orbit. It keeps record of registered scenes with their metadata and of the already preprocessed data. This eases the management of SAR data for multiple testsites in multiple projects. Currently pyroSAR is using the ESA Sentinel Application Platform (SNAP) or the Gamma SAR software for the preprocessing of the SAR data. The multiple parameters of SAR processing and the different approaches are hereby broken down in simple python functions which select the needed processing steps based on the user defined requirements like pixel size, study area and variable type . Currently the preprocessing functions are optimized for the conversion of Sentinel-1 IW GRD products to geocoded Gamma0. This includes the subsetting on a given test site geometry, border noise removal, Range-Doppler geocoding and topographic normalization. This data can then be scaled to dB. The preprocessed data sets will then be provided in a data cube from the open data cube (ODC) initiative or from the Earth System Data Laboratory (ESDL) . pyroSAR acts as a central SAR data broker to keep track of what data is available in raw or processed format and organizing this data in an easily accessible form while reducing the need to learn different processing software solutions thus leaving more time for actual data analysis. To achieve this, pyroSAR goes beyond processing SAR scenes and provides a comprehensive toolchain for general spatial data handling connecting several open source software tools along the way. It creates a framework around existing SAR processing tools to ensure consistent output from each of them reducing their individual handling to a minimum.

Item URL in elib:https://elib.dlr.de/133274/
Document Type:Conference or Workshop Item (Speech)
Title:pyroSAR: a python package to provide Sentinel-1 time series in data cubes
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Cremer, FelixFelix.Cremer (at) dlr.dehttps://orcid.org/0000-0001-8659-4361
Truckenbrodt, JohnJohn.Truckenbrodt (at) dlr.dehttps://orcid.org/0000-0002-7259-101X
Baris, IsmailIsmail.Baris (at) dlr.dehttps://orcid.org/0000-0003-2626-6811
Eberle, Jonasjonas.eberle (at) uni-jena.deUNSPECIFIED
Date:12 September 2019
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:SAR, pyroSAR, Sentinel-1, SNAP, GAMMA, processing, earth observation, data cube
Event Title:ESA Phi Week
Event Location:Frascati, Italy
Event Type:international Conference
Event Dates:09-13 Sept 2019
Organizer:ESA
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:other
DLR - Research area:Raumfahrt
DLR - Program:R - no assignment
DLR - Research theme (Project):R - no assignment
Location: Jena
Institutes and Institutions:Institute of Data Science > Citizen Science
Deposited By: Truckenbrodt, John
Deposited On:07 Jan 2020 12:57
Last Modified:07 Jan 2020 12:57

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