Docv1.0 / 2026
Rangeλ 400 - 2500 nm
StatusCalRef · testing
HORUS-1Q1 2028
●   Calibration infrastructure / Earth observation

Making Earth observation data comparable.

SpectraWorks builds the calibration layer that makes spectral data from different sensors comparable, traceable, and defensible.

Read about CalRef -> Talk to SpectraWorks
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Visible spectrum, nm - extended into SWIR for hyperspectral instruments
§ 01
The problem

The problem is not a lack of Earth observation data.
It is confidence in the measurement.

Spectral data is increasingly used to support decisions in climate, compliance, agriculture, mining, and environmental monitoring. When measurements come from different sensors, platforms, and processing chains, comparability becomes the hard part.

Without a stable calibration reference, different datasets can appear precise while remaining difficult to compare. That uncertainty does not stay in the dataset - it lands on the person who has to defend the result.

§ 02
The technology
CalRef

A calibration reference for cross-sensor spectral data.

CalRef is SpectraWorks' calibration transfer technology. It is the reference point that makes cross-sensor spectral measurements comparable.

With CalRef, spectral data from different sources can be compared, traced, and defended.

§ 03
Technical context

Even identical satellites need calibration.

Even flagship EO programmes like Sentinel require months of cross-calibration in-orbit to align their measurements, despite sensors built to the same specification. CalRef applies the same principle to every measurement - without the dedicated tandem campaign.

Fig. 1 / Sentinel-2 tandem operations ESA, 2022 · 7 weeks · 180 deg orbit phase
S-2A
in-service since 2015
S-2C
delta approx 30 sec
§ 04
Where it matters

Reliable spectral data changes the quality of decisions.

SpectraWorks works on the calibration layer for decisions where measurement confidence matters more than visual impression.

A · 01

Carbon & climate

When emissions, land-use change, or vegetation baselines are inferred from remote sensing, the credibility of the result depends on the reliability of the measurement underneath it.
"Has the signal changed, or has the sensor changed?"
A · 02

Compliance & supply chains

Deforestation, agriculture, and sourcing claims depend on data that can be compared across time, regions, and providers - and stand up under audit.
"Can this be defended to a regulator or auditor?"
A · 03

Mining exploration

Spectral signals can guide prioritisation across vast tenements - but only when the data is calibrated well enough to support confident interpretation.
"Is this anomaly real, or instrument drift?"
§ 05
Notes & commentary
From the blog

Calibration, uncertainty, and Earth observation.

Original commentary when a calibration story breaks, curated reading from the literature, and technical notes on the measurement layer underneath Earth observation.

All posts ->
● Commentary 15 May 2026 · 9 min

When a regulator asks "how do you know," the answer cannot be a colour ramp

A Mexican coffee farmer flagged non-compliant by an EUDR map that confused agroforestry with forest. A Dutch farmer permitted under a model the Council of State struck down. Both cases met the same question - how do you know - and could not answer it. The colour ramp is not the answer.
Read the post ->
§ 06
Roadmap

Today: calibration infrastructure. Next: reference-grade spectral data from orbit.

01   Today

CalRef

Calibration transfer for cross-sensor spectral data. In active development - demo available for early partners.

02   Next

Applied services

Calibration-led work with early partners: carbon verification, archive reprocessing, EO forensic analysis.

03   2028

HORUS-1

A calibration-grade hyperspectral satellite designed as a dedicated reference point for Earth observation.

§ Contact

Can your EO data stand up to scrutiny?

If your work depends on comparable spectral measurements, cross-sensor reliability, or defensible outputs, we should talk.