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/Applications/Hyperspectral remote sensing

Hyperspectral remote sensing

A fleet of miniaturized satellites will soon circle our planet. By taking hyperspectral sensing technology on board, they can reveal what happens in and on its surface.

Which parts of a mountain range are teeming with valuable metals? Where are the islands of waste plastic in our oceans? What’s the moisture level of a piece of land after a heat wave? ...

All that information – and more – can be obtained through hyperspectral remote sensing.

By equipping a satellite with hyperspectral imaging capabilities, you’re able to see the big picture, in sharp detail. Each pixel contains a complete breakdown of visible and invisible frequencies of the reflected light. Revealing the spectral signatures of minerals, soil, vegetation, ...

Hyperspectral aerial image of large test fields of soybean cultures in Brazil. The color image is augmented with spectral features to show specific variations within crop cultures (e.g. disease patterns) – Courtesy of GAMAYA.

Applications of hyperspectral remote sensing range from precision agriculture to geology, environmental monitoring and archaeology.

Hyperspectral imaging for miniaturized satellites

Until recently, hyperspectral remote sensing suffered from low temporal resolution: images were taken one or two weeks apart – the time that a big satellite needs to complete its trajectory. For many applications, like agriculture, that frequency was too low to fully realize the benefits of the technology.

That’s why the advent of low-cost miniaturized satellites – so-called CubeSats – promises to be a game-changer for hyperspectral remote sensing. They allow for the development of a constellation of satellites that scan the same location almost daily.

Specific challenges in space

In space, and especially for small satellites, constraints are different than on-ground:

  • The payload must be extremely compact and light to save costs.
  • Because the lighting varies, the sensor must also operate in low-light conditions.
  • The satellite scans the earth while orbiting, and the smaller the satellite, the higher its instability.

Those conditions are difficult to meet with grating-based cameras. They are bulky. They suffer from low signal-to-noise ratio when the lighting is low. And because they require images to be reconstructed line by line, instability greatly reduces their ability to reconstruct images.

On-chip SWIR snapshot and push-frame sensors for hyperspectral remote sensing

As a leading R&D center for semiconductor technology, imec can deposit and pattern spectral filters on the surface of area-scan image sensors. That makes it possible to create push-frame hyperspectral sensors that relax the constraints on the line-of-sight pointing accuracy in small satellites.

By depositing exactly the same spectral filter on adjacent rows of pixels, that patterning capability is also used to increase the signal-to-noise ratio of the image with TDI functionality.

In an alternative configuration, it is possible to combine push-frame hyperspectral imaging with snapshot multispectral imaging. This results in the potential to make video imaging from space –even in low-earth orbit.

Last but not least: with spectral filters operating in the SWIR, combined with an off-the-shelf InGaAS detector, imec broadens spectral imaging further than the visible and NIR spectrum.

This makes these sensors ideal for use in satellites and high-altitude drones, for the classification of agricultural soils, minerals, plastic pollution, surveillance ...

Want to use our hyperspectral remote sensing technology?

Imec has a long history of applying its innovative technologies to research in and from space. Our hyperspectral imaging sensors were already used in the CHIEM project that developed a novel compact hyperspectral imager – compatible with a 12U CubeSat satellite.

Contact us if you want to use our sensors for your satellite projects. Or if you’re looking for a partner that can help you with the custom development of your sensor or system.

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