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SIMPLIFYING SAR FOR AI DEVELOPMENT

AI4SAR

Simplifying SAR for AI development.
ICECUBE: An open source python library for SAR-based machine learning.
build your icecube (GitHub)
AI4SAR
AI4SAR
AI4SAR

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 engineering. However, the complexity of the backscattered SAR signal is quick to overwhelm both novice and expert data scientists.

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

Data

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.

Timely

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.

Activity

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

MUHAMMAD-IRFAN-ALI
MUHAMMAD IRFAN ALI

Machine Learning Engineer

ANDREA-RADIUS
ANDREA RADIUS

SAR Expert

TAPIO-FRIBERG
TAPIO FRIBERG

Sr. Machine Learning Engineer

SHAY-STRONG
SHAY STRONG

VP, Analytics

bartosz-postulka
BARTOSZ POSTULKA

Sr. Technology Manager

Arnaud-dupeyrat
ARNAUD DUPEYRAT

Data Scientist

IBRAHIM-EL-MEREHBI
IBRAHIM EL MEREHBI

Remote Sensing Engineer

LETICIA-MENDONCA
LETICIA MENDONCA

Product Owner

Abdullah-AI4SAR
ABDULLAH ALMAKSOUR

Machine Learning Engineer, Lead

Additional information