Astrophysics-Ecology Drone Project Could Help Save Endangered Species

The world's first astrophysics-ecology drone project at Liverpool John Moores University could be the answer to many global conservation efforts.

False-color, thermal-infrared image of a "crash" of rhinos taken from drone video footage at Knowsley Safari Park. (Credit: Belongs to Liverpool John Moores University)

Four hundred years ago Galileo created a revolution by pointing his telescope to the skies. Now an astrophysicist and an ecologist from Liverpool John Moores University (LJMU) are reversing this perspective to help endangered species including rhinos and orang-utans.

The authors of the study, published in the International Journal of Remote Sensing, have brought together their expertise using drones, thermal cameras and the techniques used to analyse objects in space to find a solution to this 21st Century challenge for Earth.

Professor Serge Wich, from LJMU's School of Natural Sciences and Psychology and the University of Amsterdam's Institute for Biodiversity and Ecosystem Dynamics, is a pioneer in using drones for conservation work and is the founder of conservationdrones.org, commented:

"As an 'eye in the sky', conservation drones are helping the fight against illegal deforesting, poaching and habitat destruction, all leading to many species being endangered, including rhinos, orang-utans, and elephants. Now, teamed with the same astrophysics analysis techniques used to find and identify objects in the far-distant Universe, we can try to do this more efficiently."

"The World Bank estimates that ecosystems provide $33 trillion every year to the global economy and biodiversity loss and consequent ecosystem collapse is one of the ten foremost dangers facing humanity. We hope this research will help tackle these problems by allowing anyone in the world to upload their aerial data and in real time get back geo-locations of anything, whether that be survivors of natural disasters, or poachers approaching endangered species, or even the size, weight and health of livestock."

Dr Steve Longmore, from the LJMU Astrophysics Research Institute, explains why this is possible:

"Astrophysicists have been using thermal cameras for many decades. Crucially, it turns out the techniques we've developed to find and characterise the faintest objects in the Universe are exactly those needed to find and identify objects in thermal images taken with drones. The key to success is building libraries of the thermal heat profiles that act like "thermal finger prints", allowing us to uniquely identify any animals detected. Our goal is to build the definitive finger print libraries and automated pipeline that all future efforts will rely upon."

The next stage of this research, which will be funded by the Science and Technology Facilities Council (STFC), is to start expanding these techniques to other equally significant applications, including disaster relief and search and rescue.

This new drone technology is part of the growing technological innovation within LJMU. The Astrophysics Research Institute is also developing the world's largest fully robotic telescope, a scaled up version of the Liverpool Telescope, located at the Roque de Los Muchachos Observatory, on the island of La Palma, and operated by LJMU as a national facility.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.