Demonstrate an advanced hyperspectral imager and novel on-board processor.

Observe the Earth using a satellite equipped with a hyperspectral instrument and advanced data processing on board using deep convolutional neural networks. Camera with spectral resolution in the range of visible and near-infrared light. By dividing this band into 150 channels, it will be possible to obtain much more information as compared to the existing instruments on the market which offer only 40 channels. The first satellite with processing capability to segment hyperspectral images in orbit.

• Imagine an area of 40 km x 40 km depicted with a spatial resolution of 25 m/pixel across 192 spectral bands, generating approximately 7 GB of data. Now envision a 100-fold reduction of this data volume while still retaining critical information. This is the data efficiency we aspire to with Intuition-1.
• Our hyperspectral camera captures up to 192 spectral bands (470 nm - 900 nm), comprehensively analysing the research area. Paired with the onboard Leopard DPU unit, this allows for flexible repurposing of the satellite as needed.

Intuition-1’s hyperspectral camera captures and segments light across a broad spectrum, enabling the identification of a number of soil health indicators such as potassium oxide, phosphorus pentoxide, magnesium and pH level.

Computational muscle is provided by an orbit-resilient data processing unit which, by pre-processing and filtering the images, is expected to reduce the volume of data transferred daily to ground from around 100 GB to just 300 MB.

The majority of the AI models for Intuition-1 were developed within the ESA FutureEO-funded Genesis activity.

Intuition-1 is reporting nominal telemetry across the board. After successfully deploying UHF antennas and solar arrays, the operations team is currently engaged in the precise activation of subsystems as we progress toward the satellite's full operational state.

Successfully activated the Leopard Data Processing Unit (DPU), marking a significant development in our satellite's functionality. This unit, with its capability for high-speed processing up to 7.6 Gb/s and a substantial storage capacity of 960 GiB, plays a critical role in processing hyperspectral images on-board through Neural Networks.

Deployment date estimated by Jonathan McDowell.

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• Barry
• BRO-10
• BRO-11
• Connecta T3.1
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• GENMAT-1
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• Lemur-2 171 (SNC 1)
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