‘Cracking the code’ of woody weed spread with machine-learnt algorithms

The CABI Blog

rotor-cipher-machine-1147801_1920 Machine learning algorithms have their origins in early ‘computers’ such as the German WW2 ciphering Enigma machine

A scientific tool which has its principles in early ‘computers’ such as the German WW2 Enigma machine – used to convey secret commercial, diplomatic and military communication – is helping to map the fractional cover of the woody weed Prosopis julifloraacross the Afar Region of Ethiopia.

PhD Candidate Hailu Shiferaw from Addis Ababa University, who is being supervised by CABI’s Dr Urs Schaffner, Professor Woldeamlak Bewket (AAU) and Dr Sandra Eckert (Centre for Development and Environment, University of Bern), has compared the performances of five Machine Learning Algorithms (MLAs) to test their ability at mapping the fractional cover/abundance and distribution of Invasive Alien Plant Species (IAPS) – particularly Prosopis which has already devastated an area equivalent to half of neighbouring Djibouti.

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