Why this matters in the Arctic

The Arctic is warming faster than any other region, and the same waters are seeing more shipping, fishing, aquaculture and tourism. Sea ice extent and drift, oil spills, harmful algal blooms, coastal erosion, thawing ground and vessel traffic all need to be observed at a cadence and coverage that field campaigns cannot deliver.

Cloud cover, polar night and low sun angles rule out optical-only methods for much of the year, which puts radar, thermal and fused approaches at the centre. Latency matters too: for ice advisories, spill response or fisheries management, a product delivered tomorrow is a different product.

We are looking for downstream services and analytics with paying users — operators, authorities, insurers, industry — not demonstrations without a customer.

Relevant technologies and data sources

Satellite data

Sentinel-1 SAR, Sentinel-2 and Sentinel-3, thermal and hyperspectral imagery, altimetry, commercial optical and SAR constellations, Copernicus core services.

Maritime domain awareness

SAR ship detection fused with AIS, dark vessel detection, oil spill detection and drift, iceberg and sea ice charting, route and ice-class decision support.

Environment and ecosystems

Ocean colour and algal bloom monitoring, sea surface temperature, aquaculture siting and site conditions, coastal erosion, snow and permafrost change detection.

Methods and delivery

Machine learning for detection and change, data fusion with in-situ buoys, gliders and models, cloud processing, near-real-time delivery from polar ground stations, APIs and dashboards.

Partner expertise available to you

Selected teams get access to partner expertise, data and facilities alongside seed funding and business coaching.

KSAT

Near-real-time SAR services, polar ground station network, operational maritime and spill monitoring at scale.

Akvaplan-niva

Arctic marine environment, aquaculture and ecosystem expertise, field campaigns and in-situ validation.

NORCE

Remote sensing analytics, machine learning on EO data, modelling and cross-domain applied research.

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