Spotting elephants from space: a satellite revolution
Using the highest resolution satellite imagery currently available - Worldview 3 – from Maxar Technologies and deep learning, (TensorFlow API, Google Brain) researchers at the University of Oxford Wildlife Conservation Research Unit and Machine Learning Research Group have detected elephants from space with comparable accuracy to human detection capabilities. Finding a needle in a haystack is a challenge, but counting elephants from space sounds like science fiction, but that is exactly what a team led by WildCRU’s Isla Duporge has achieved.
Currently the most common survey technique for elephant populations in savannah environments is aerial counts from manned aircraft. Observers on aerial surveys can get exhausted, be hindered by poor visibility and otherwise succumb to bias, and aerial surveys can be costly and logistically challenging. A team from the University of Oxford (WildCRU: Department of Zoology and the Machine Learning Research Group: Department of Engineering) in collaboration with Dr Olga Isupova, University of Bath and Dr. Tiejun Wang, University of Twente, set out to solve these problems.
One of the challenges of using satellite monitoring is processing the enormous quantity of imagery generated. However, automating detection means a process that would formally have taken months can be completed in a matter of hours. Furthermore, machines are less prone to error, false negatives and false positives in deep learning algorithms are consistent and can be rectified by systematically improving models- the same cannot be said for humans. To develop this new method, the team created a customised training dataset of more than 1000 elephants in South Africa, which was fed into a Convolutional Neural Network (CNN) and the results were compared to human performance. Elephants, it turns out, can be detected in satellite imagery with accuracy as high as human detection capabilities.
The researchers believe that this demonstrates the power of technology to serve conservation: satellite remote sensing and deep learning technologies offer promise to the conservation of these majestic mammals. Conservation technologies open a new world of possibilities, to be embraced with the urgency necessitated by the sixth mass extinction and the global plight of biodiversity.