ICEYE Data

Simplifying SAR for AI Development

ICEcube: an open source python library for SAR-based machine learning

Build your ICECUBE external_link

About The AI4SAR Project

Rapid-revisit Synthetic Aperture Radar (SAR) satellites in Low Earth Orbit (LEO) are promising with their observational persistence, low cost, and breakthrough engineeringHowever, the complexity of the backscattered SAR signal is quick to overwhelm both novice and expert data scientists.

ai4sar_inside_1

At ICEYE Analytics, we are keen on building AI/ML applications for heavy-duty image processing and scalable analytics. The European Space Agency (ESA) Φ-lab presented us with an opportunity to lower the entry barrier to SAR-based ML applications. Due to the combination of our internal objectives and this fantastic ESA opportunity, we’ve begun to develop an open source Python library to easily enable ML exploration of ICEYE SAR images.

The ICEcube array handling library is our first step to lower the SAR barrier to entry. This library abstracts, yet persists, some of the metadata handling and optimizes array manipulation and memory usage through xarray data structures.

 

Applications

  • SAR Processing
  • SAR Processing

    SAR-ML pipelines support quick iterations that enable us to identify and correct SAR processing artifacts. ML applications can be deployed easily to a cloud processing environment and can scale asynchronously to handle large quantities of data.
  • Time Series Analysis
  • Time Series Analysis

    Time-series stacks of coregistered SAR images help us appreciate the true weight of the challenge at hand. SAR is the only EO technology that can consistently and with high precision enable the quantification of change over time. High-temporal resolution and persistence under cloud cover create opportunities to study the dynamics (manmade or natural) of the Earth regardless of season. Unsanctioned deforestation can no longer be hidden in the rainy season.
  • Data Handeling
  • Data Handling

    SAR preprocessing quickly overwhelms with its inherent complexity, unique processing chain, and stringent requirements, such as coregistration, to make sense of the data. ICEcube abstracts away this burden.

 

PROJECT TEAM

ai4sar_Irfan

Muhammad Irfan Ali

Machine Learning Engineer
Irfan on LinkedIn

ai4sar_Andrea

Andrea Radius

SAR Expert
Andrea on LinkedIn

ai4sar_Tapio_2

Tapio Friberg

Machine Learning Engineer 

 

ai4sar_Shay

Shay Strong

VP, Analytics
Shay on LinkedIn

ai4sar_Bartosz

Bartosz Postulka

Sr. Technology Manager

ai4sar_Arnaud

Arnaud Dupeyrat

Data Scientist
Arnaud on LinkedIn

ai4sar_Ibrahim

Ibrahim El Merehbi

Remote Sensing Engineer
Ibrahim on LinkedIn

ai4sar_Leticia

Leticia Mendonca

Technical Writer
Leticia on LinkedIn

 

 



ADDITIONAL INFORMATION

Blog: Applying Machine Learning To Rapid Revisit SAR

The complexity of SAR data is often daunting and discourages even experts from integrating it into their Machine Learning workflows. We at ICEYE Analytics want to change that.

Read more
Build Your OWN ICEcube

Extract the essence of SAR without the burden of heavy-duty preprocessing

Build It Now