Hyperspectral Imaging—Are We Ready for the Data Revolution?

Not all cameras are created equal. The human eye sees red, green, and blue. Traditional
cameras mimic that. But hyperspectral cameras? They capture hundreds of spectral bands,
revealing chemical compositions, material structures, and environmental changes invisible to
standard imaging. Mounted on drones, they are up to change everything from precision
agriculture to mineral exploration.

But there is a problem.

The Data Deluge – Key Challenges

More spectral bands mean more data. A single hyperspectral image can contain gigabytes of
information. Multiply that by thousands of picture permissions, and suddenly, you are dealing
with terabytes. That’s a challenge for processing, storage, and even transmission.

It is all about size and precision. Hyperspectral imaging relies on “push-broom scanning,” where
the sensor collects data line by line as the drone moves. Even slight variations in flight speed or
altitude can distort results, leading to gaps or misalignments in the dataset. These errors can
turn valuable insights into useless noise in scientific research, environmental monitoring, and
resource management.

Agriculture, Mining, and the Search for Hidden Patterns

Hyperspectral surveys are not just about drones with fancy cameras. They are data-driven tools
that have the potential to transform industries.

In agriculture, farmers can detect early signs of crop stress before the human eye can spot them. Soil composition, water distribution, and disease outbreaks become visible at a molecular level.

In mining, instead of expensive exploratory drilling, companies can map mineral deposits from
the sky. Hyperspectral sensors can distinguish between different rock types based on their unique spectral signatures.

Similarly, for forestry and the environment. Tracking deforestation, pollution, or invasive species becomes easier when every material has a distinct spectral fingerprint.

The Software Gap

In this case, the hardware is often ahead of the software. Hyperspectral cameras are improving
and becoming more compact and affordable, but the challenge lies in data interpretation and mission execution – once again, precision is very important here.

Flight planning software plays a critical role here. Since hyperspectral imaging requires precise,
repeatable flight paths, mission control platforms must ensure stable speed, altitude, and scanning angles. This is not just about flying in straight lines but also about eliminating human error and optimizing drone paths to avoid often costly re-flights.

We have dedicated a lot of time to it at UgCS. We have tackled this by automating mission planning for hyperspectral workflows. By integrating field-of-view angles, the ability to use high-resolution terrain models and overshoots, our software helps ensure that every pixel of spectral data is captured correctly.

Cost vs. Capability

Despite the potential, hyperspectral cameras remain expensive. Entry-level models start at
$10,000, while high-end systems exceed $100,000. That’s before factoring in the cost of drones, flight software, and data processing tools.

So, is the investment worth it? For industries where minor chemical differences translate to major financial impacts—yes. Farmers optimize fertilizer use, mining firms reduce drilling costs, and environmental researchers track climate change, all of which stand to gain. But for widespread adoption, costs must drop, and AI-driven data processing must improve.

The Future of Hyperspectral Imaging

Miniaturization is making these cameras more accessible, AI is accelerating data interpretation, and drones offer affordable satellite imagery alternatives. The biggest challenge? Turning hyperspectral data into actionable insights—fast.

For now, hyperspectral imaging remains a specialized tool. However, as automation refines the
workflow, its impact will expand. Whether it’s feeding the planet, finding rare minerals, or monitoring ecosystems, one thing is clear: the future of imaging is not just about seeing but also about understanding.

Author: Kristaps Brass

Kristaps Brass is an Engineer and Product Owner of UgCS at SPH Engineering. Having been with SPH Engineering since 2014, Kristaps has worked on countless field flight tests, lead customers training in Riga and around the world (from Brazil to Australia), and even participated in an expedition to Greenland in 2019 together with Alexey Dobrovolskiy, CTO. Kristaps graduated from Stockholm School of Economics in Riga and Tallinn University of Technology where he studied Integrated Engineering. He is currently heading the UgCS development and product team toward making UgCS flight planning software the leading choice for professional
drone pilots.