Astro-ecology

For astro-ecology PhD projects click here!

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Astro-Ecology group goal: Using techniques from astronomy and machine learning, we are developing a fully-automated drone system that can detect, identify and determine the health of animals. The system will be very low cost, robust, simple to operate and so user friendly that local communities in developing countries with no technical background can operate it independently. We are currently developing the system and starting to take this to different locations around the globe and, working with local rangers/researchers, helping monitor and project some of the most critically endangered animal species on the planet.


An urgent global challenge: The World Wildlife Fund for Nature (WWF) estimates that up to five species of life on our planet become extinct every day. This high rate “biological annihilation” means a sixth mass extinction in Earth’s history is under way (the 5th being the one that wiped out the dinosaurs).

 
Chimpanzees imaged with our thermal camera.


Current difficulties overcoming this challenge: Effective conservation strategy relies on knowing the current state of the ecosystem being conserved, how many animals there are and what threatens them. But monitoring all animals everywhere on the planet is no small task - especially when most conversation surveys have to happen on foot. By using drones we can get a bird's-eye view of the situation, and cover a large area on the ground very quickly. The addition of thermal cameras allows us to see animals as a result of their body-heat. This negates their natural camouflage and allows us to detect them in the dark. In thermal infrared footage animals appear as bright sources in a similar way to how stars and galaxies appear in astronomical imaging. We can apply techniques from astronomy to detect and classify different animals automatically. This means we have the potential to monitor endangered animals more effectively than ever before.

 

 

Press releases

 

 

Team Members

Name
 
Email
 
Research interests
 

Research staff
Claire Burke C.Burke@ljmu.ac.uk Mission planning, physics of the environment, optimizing thermal data capture
Steve Longmore S.N.Longmore@ljmu.ac.uk  
Ross (Paul) McWhirter P.R.McWhirter@ljmu.ac.uk Machine learning, automated identification of animal species
Josh Veitch-Michaelis J.L.VeitchMichaelis@ljmu.ac.uk Computing and drone hardware integration
Marco Lam C.Y.Lam@ljmu.ac.uk Databasing, data flow and storage.
   

Graduate students
Maisie Rashman M.F.Rashman@2016.ljmu.ac.uk Quantifying and optimizing thermal camera performance
   

Non-ARI team members
Serge Wich S.A.Wich@ljmu.ac.uk Conservation biologist specializing in primates
Mara Mulero-Pazmany M.C.MuleroPazmany@ljmu.ac.uk Drone-conservation pioneer
Owen McAree O.D.McAree@ljmu.ac.uk Aeronautical engineer specializing in drones
Paul Fergus P.Fergus@ljmu.ac.uk Computer scientist and machine learning expert
Carl Chalmers C.Chalmers@ljmu.ac.uk Computer scientist and machine learning expert

Links
PhD Positions

PhD projects we're currently looking to fill

Students interested in Ph.D. projects in astro-ecology are encouraged to contact Dr. Claire Burke or Prof. Steven Longmore. We are open to students with a background in physics, astrophysics, computer science, engineering and other related disciplines. Students with a background in natural sciences are encouraged to contact Prof. Serge Wich.

 

 

 

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