About ClearSKY Vision

Making Earth observation dependable for real decisions.

Earth observation is powerful, but the ecosystem is fragmented. Different satellites behave differently, formats vary, clouds break coverage, and missions evolve. Downstream teams often spend more time harmonizing data than using it.

It is not only harmonization. It is cleaning, quality control, and removing inconsistencies so EO becomes dependable in automated pipelines. When the data is consistent, teams can scale monitoring across regions, seasons, and sensors without rebuilding the workflow every time.

We are building the compatibility layer for Earth observation: cloud-free, analysis-ready imagery that stays consistent across sensors and time, so GIS and analytics teams can build once and rely on it.

Built for downstream teams

Designed to drop into GIS, dashboards, and models with less custom glue.

Operational reliability

Consistency that holds up when input availability shifts and missions change.

Continuity over perfection

Better monitoring comes from reliable cadence, not waiting for cloudless luck.

ClearSKY Vision team
UN Global Goal 2
UN Global Goal 6
UN Global Goal 9
UN Global Goal 12
UN Global Goal 13
UN Global Goal 15

What we optimize for

Reliable monitoring beats perfect snapshots

We focus on continuity, consistency, and downstream usability, the things that make EO practical in production.

Analysis-ready by default

Less preprocessing and fewer surprises when data lands in GIS, dashboards, or models.

Time series you can trust

Consistency across time so monitoring does not break when sensors, missions, or availability changes.

Cloud-free continuity

Reliable coverage by combining complementary sensors instead of waiting for a perfect acquisition.

How we do it

Fusion and harmonization, delivered as a stable output

No single sensor is enough. We combine complementary sources to improve coverage, and standardize outputs so time series stay comparable.

Sensor-agnostic outputs

Build downstream workflows once and reuse them across satellites and geographies.

Cross-sensor harmonization

Standardization that keeps geometry and radiometry comparable across sources.

Frequent updates

Higher temporal reliability through fusion when any one sensor falls short.

Reliability for production teams

Stable pipelines for organizations that depend on EO as an operational input.

Recognition

Prizes and acknowledgements

We have been recognized by leading European innovation and space ecosystem programs.

CopMa2 award
INNOspace award
CopMa award
CASSINI award

The people

Meet the team

Morten Fjord, ClearSKY

Morten Fjord

[email protected]

Niels Buus, ClearSKY

Niels Buus

 

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