FOOTPRINTs: artificial intelligence & citizen science.

Identifying animal tracks in the snow is very helpful to monitor wildlife. But it’s not always easy to know what you’re looking at. That’s where the FOOTPRINTs project comes in! Led by Dr Caitlin Mandeville at the Norwegian University of Science and Technology (NTNU), this initiative uses image recognition to make track identification easy and accessible for everyone. Rissa Citizen Science is a partner in this exciting project, and now it's time to share what we’ve learned from the past winter season!

Happy-to-be-outside students during one of the FOOTPRINTs fieldtrips in March 2025.

From the classroom to the forest

Over 240 participants took part in the FOOTPRINTs events organized by Rissa Citizen Science around Tromsø and on Senja between February and April 2025. Our main focus was engaging youth, from local schools as well as international student groups visiting Norway on study trips or longer stays.

A typical day began with a one-hour classroom session introducing the project and helping participants recognize the most common animal tracks found in Northern Norway. Then, equipped with snowshoes, everyone headed outdoors, eyes to the ground and senses sharp, on the lookout for animal footprints in the snow.

Moose track in the deep snow near Tromsø in April 2025.

Machine learning

Before the model can identify which species an animal track belongs to, it first needs to be trained by humans. This is a classic machine learning process, and in the FOOTPRINTs project, the task of training the algorithm falls to experts from Artsdatabanken, Norway’s biodiversity database and a key project partner. These computer scientists are developing the image recognition tool, but to do so, they need a large and diverse dataset of animal track photos to account for the many variations that could otherwise confuse the model.

That’s where the participants played a vital role, by documenting animal tracks and submitting their photos, they contributed directly to teaching the algorithm how to "see" and correctly identify species in the snow.

Species we identified from their footprints during the project: European otter, lynx, mountain hare, moose and reindeer, pine marten, American mink, stoat, red fox, capercaillie, rock ptarmigan, willow ptarmigan, black grouse and red squirrel. Passerines, small rodents and shrews' tracks were commonly observed but so far not taken into account.

A FOOTPRINTs' participant looking at a rock ptarmigan track near Tromsø.

Ghosts in the wild

In most places, wildlife encounters are rare, animals have evolved to avoid humans, passing down elusive behaviors over generations to stay safe. In the Arctic, such encounters are even scarcer due to the low abundance of wildlife, shaped by harsh environmental conditions and topography. In the Tromsø area, the dense human presence further complicates the ability of wildlife to thrive. Yet, animal tracks often tell a different story. Snow reveals what the eye doesn’t see, silent evidence that animals are nearby, even when we rarely spot them.

A volunteer is taking a photo of an animal track near Tromsø in April 2025.

For Rissa Citizen Science, this contrast between what we observe and what the snow reveals became an key message during our outings. While many view nature primarily as a playground, animal tracks remind us that we share these spaces with other species; species that are acutely aware of and affected by our presence. In the forests, mountains, and valleys beyond our backyards, wildlife is simply trying to survive. We hope this perspective stayed with the participants: that nature is not ours alone, but a shared space where coexistence matters.

Katja and her students just before heading out in the field in March 2025.

What's next in the FOOTPRINTs project

The FOOTPRINTs project is nearing its conclusion. The machine learning model developed by scientists at Artsdatabanken has shown promising results, but it’s not yet fully reliable for identifying all the species found in Norway. More work is needed before anyone can confidently use a simple, user-friendly mobile app to identify animal tracks in the snow.

The long-term goal is for anyone with an interest in wildlife to use the app, not only to satisfy their curiosity, but also to contribute valuable data that can support conservation efforts and expand our understanding of animal populations.

Animal-tracking expert looking at a moose track near Tromsø.

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Five Instagram reels to watch:

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The FOOTPRINTs projects is a consortium of five partners:

• The Norwegian University of Science and Technology (NTNU) (project leader)

• Artsdatabanken

• iTrollheimen

• Trondheim kommune

• and Rissa Citizen Science

It is founded by TETTRIs, a consortium of 17 Partners joining efforts with the European Commission to tackle the shortage of taxonomic experts and resources.

More about the project on Rissa Citizen Science's website and on the FOOTPRINTs' website.

Moose in deep snow near Tromsø by Jean-Batiste Strobel.