Copernicus Sentinel-1 is the first operational mission that systematically acquires SAR data on a global scale. The open and free data policy led to a massive rise of interest beyond traditional SAR experts and there is now the need for easy-to-use tools that accelerate the uptake of this valuable data source. The Open SAR Toolkit responds to the requirement by bundling the full workflow for the generation of Sentinel-1 Analysis-Ready-Data (ARD) for land in a single high-level Python package. The concept of ARD is driven by the need for ready-made data that does not need further sensor-expert pre-processing, thus letting the user focus on the actual information extraction.
The toolkit can be considered an end-to-end data preparation package that includes functionalities for data inventory and advanced sorting, as well as bulk concurrent downloading from various data mirrors. The pre-processing routines are almost entirely based on ESA’s Sentinel-1 toolbox and wrapped into a single function for the fully automated batch processing. Given that at the moment there is no consensus on the specification of ARD products for SAR and the respective pre-processing steps involved, various types of ARD templates can be selected and customised.
The toolkit does include advanced types of ARD, such as the combined production of calibrated backscatter, interferometric coherence and the dual-polarimetric H-A-Alpha decomposition. Time-series and multi-temporal statistics (i.e. Timescans) can be produced for each of these layers. The generation of seamless large-scale mosaics over time is also possible. Jupyter notebooks are the main way to interact with the tools, and tutorial notebooks are available to get users started.
