Elmontaserbellah (Monty) Ammar

PhD Title: Using remote sensing and machine learning to prioritise the recovery of degraded tropical forests

Elmontaserbellah (Monty) Ammar is a PhD researcher at the Durrell Institute of Conservation and Ecology (DICE), University of Kent. His doctoral research focuses on using artificial intelligence and remote sensing to map and monitor artisanal small-scale mining and forest recovery across the tropics. His work combines deep learning, satellite imagery, and ecological modelling to identify mining frontiers, quantify carbon loss, and predict post-mining vegetation recovery.

Before beginning his PhD, Monty completed a BSc in Animal Biology and Wildlife Conservation and an MSc in Conservation Biology at the University of Kent, where his research made use of remote sensing and machine learning to assess ecological regrowth in mined landscapes in Guyana.

He previously worked with Butterfly Conservation Northern Ireland as a Species on the Map Officer, conducting spatial analyses to support conservation of threatened butterfly and moth species. Alongside his PhD, Elmontaserbellah contributed to collaborative projects on ecological niche modelling, spatial data analysis, and the integration of AI tools into applied ecology and conservation policy.  

Elmontaserbellah’s research explores how artificial intelligence and remote sensing can be used to understand and manage tropical forest change. His current projects span four main areas:

– AI in ecology and policy – identifying opportunities, risks, and governance gaps in the growing use of AI tools such as computer vision, bioacoustics, and decision-support systems.

– Mining frontiers – mapping decades of artisanal and small-scale gold mining across the Guiana Shield using deep learning on Landsat imagery.

– Post-mining recovery – modelling how vegetation regenerates after mining, and which environmental factors drive or limit natural recovery.

– Global tropical applications – scaling these methods across tropical forests worldwide to pinpoint where restoration and protection efforts are most urgently needed.  

Supervised by Dr Jake Bicknell, Dr Matthew Struebig and Dr Eleni Matechou.