For conservationists to work effectively, they need to know how many elephants they are dealing with and where they are. New technology is helping.
The picture comes from an Earth-observation satellite orbiting 600km (372 miles) above the planet's surface. At first, the satellite image appears to be of grey blobs in a forest of green splotches - but, on closer inspection, those blobs are revealed as elephants wandering through the trees. And scientists are now using these images to count African elephants from space with a machine learning algorithm.
For decades, the best way for conservationists to monitor threatened elephant populations has been via an aircraft survey. The trouble is that it's expensive, time consuming and the naked eye is not entirely reliable. So, to help conservationists count African elephant populations accurately and swiftly, scientists in the UK have developed an algorithm that can identify elephants in satellite images.
We just present examples to the algorithm and tell it, ‘This is an elephant, this is not an elephant,’” said Dr. Olga Isupova of the University of Bath. “By doing this, we can train the machine to recognize small details that we wouldn’t be able to pick up with the naked eye.”
The scientists have tested the algorithm on South Africa’s Addo Elephant National Park. Through machine learning, the algorithm was able to identify elephants in a variety of backdrops, whether it be in the open savannah, dense thickets or clusters of trees.
According to University of Oxford scientist Dr. Isla Duporge, conservation organizations are already showing interest in using the algorithm to replace aircraft surveys, although they will have to pay for access to commercial satellites and the images they capture. That said, it should be worth it as the algorithm can survey up to 5,000 sq km of elephant habitat on a single cloud-free day.
Motion sensor uses AI to recognise when wildlife is running from poachers and can alert rangers. Any innovation that can help stop the slaughter of wildlife at the hands of poachers seeking, for example, ivory, has got to be good news. So, it's good to learn that scientists in the Netherlands are mixing motion sensors with machine learning to create a powerful tool that could achieve exactly that, simply by allowing them to recognize when wildlife is responding to a nearby threat. More...