The conversation started over a fence dividing two backyards. On one side, an ecologist remarked that surveying animals is a pain. His neighbor, an astronomer, said he could see objects in space billions of light years away.
And so began an unusual partnership to adapt tools originally developed to detect stars in the sky to monitor animals on the ground.
The neighbors, Steven Longmore, the astronomer, and Serge Wich, the ecologist, both of Liverpool John Moores University in England, made their backyard banter a reality that may contribute to conservation and the fight against poaching.
The scientists developed a system of drones and special cameras that can record rare and endangered species on the ground, day or night. Computer-vision and machine-learning techniques that help researchers study the universe’s oldest and most distant galaxies can now be used to find animals in video footage.
Claire Burke, an astrophysicist at the university now leading the project, presented the team’s latest findings at the European Week of Astronomy and Space Science on Tuesday.
Keeping track of elusive animals, especially those that are endangered, isn’t trivial. First, it takes time and money to conduct manual counts on the ground or to shoot photos from planes in the sky. With video, cheaper drones and software, identifying animals has become more efficient.
But cameras made for daylight can miss animals or poachers moving through vegetation, and the devices don’t work at night. Infrared cameras can help: Dr. Wich had been using them for decades to study orangutans.
These cameras yield large amounts of footage that can’t be analyzed fast enough. So what do animals and stars have in common? They both emit heat. And much like stars, every species has a recognizable thermal footprint.
“They look like really bright, shining objects in the infrared footage,” said Dr. Burke. So the software used to find stars and galaxies in space can be used to seek out thermal footprints and the animals that produce them.
To build up a reference library of different animals in various environments, the team is working with a safari park and zoo to film and photograph animals. With these thermal images — and they’ll need thousands — they’ll be able to better calibrate algorithms to identify target species in ecosystems around the world.
The experts started with cows and humans in England. On a sunny, summer day in 2015, the team flew their drones over a farm to see if their machine-learning algorithms could locate the animals in infrared footage.
For the most part, they could.
But accuracy was compromised when drones flew too high, cows huddled together, or roads and rocks heated up in the sun. In a later test, the machines occasionally mistook hot rocks for students pretending to be poachers hiding in the bush.
Last September, the scientists honed their tools in the first field test in South Africa. There, they found five Riverine rabbits in a relatively small area. These shy rodents are among the world’s most endangered mammals. Only a thousand have ever been spotted by people.
The tests helped the scientists calculate an optimal height to fly the drones. The team also learned that animals change shape in real time (rocks don’t) as drones fly over. And the researchers found that rain, humidity and other environmental, atmospheric and weather conditions can interfere with proper imaging.
The scientists are refining their system to account for these issues. And in two years, Dr. Burke said, they plan to have a fully automatic prototype ready for testing. Within five years, she hopes to sell systems at cost — today, just around $15,000.
In the meantime, these astro-ecologists are also working with search and rescue groups to help find people lost at sea or in fog. And starting in May, they will collaborate with conservation groups and other universities to look for orangutans and spider monkeys in the dense forests of Malaysia and Mexico, as well as for river dolphins in Brazil’s murky Amazon River.