ICEYE OY (FI)
AI4SAR is an attempt to harness AI techniques for high-resolution, high-fidelity SAR data, both in time and spatially. It aims to process rapid-revisit SAR data and develop modular applications for high-frequency monitoring of Earth.
The inherent complexity of the backscattered SAR signal presents a daunting challenge to data scientists and machine learning (ML) engineers, thereby increasing the entry barrier and precluding the exploration of an incredibly rich data source.
AI4SAR is a great opportunity to lower this entry barrier to SAR-based ML applications and unlock the full potential of persistent monitoring of our dynamic planet.
AI4SAR addresses three critical needs of the data science and machine learning community:
AI4SAR aims at building tools that simplify SAR for data scientists and ML engineers so that they can accelerate AI development for EO applications. To this end, the AI4SAR project team built the icecube toolkit that helps organize ICEYE SAR images and annotations for supervised ML applications. The Python library generates multidimensional SAR image and labels datacubes.
The datacubes stack SAR time-series images in range and azimuth and can preserve the geospatial content, intensity, and complex SAR signal from the SAR images. You can use the datacubes with ICEYE Ground Range Detected (GRD) geotifs and Single Look Complex (SLC) .hdf5 product formats.
With the icecube toolkit, the community can:
Additional resources: The icecube toolkit is available on https://github.com/iceye-ltd/icecube/