Max Fancourt

Max Fancourt

Profile

I joined the University of Leeds in January 2019 to start a PhD. The primary focus of this PhD is to investigate the potential of remotely sensed data from platforms such as satellites, unmanned aerial systems (UAVs/drones) and flux towers to help understand, quantify and monitor changes in ecosystem stability, resistance, and resilience in the context of forest ecosystems. The primary focus of this PhD is to investigate the potential of remotely sensed data from platforms such as satellites, unmanned aerial systems (UAVs/drones) and flux towers to help understand, quantify and monitor changes in ecosystem stability, resistance, and resilience in the context of forest ecosystems. This research will employ a multidimensional paradigm fusing a wide range of stability measures, metrics and methods in order to provide a quantitative description of stability that explicitly takes into account the multifaceted nature of these ecological concepts, and permits changes over time and space to be explicitly monitored and explored. Through combining this stability data with in-situ data, we hope to be able to investigate the role of functional diversity, species richness and a number of other variables play in moderating the impact of drivers of change on an ecosystem.

I come from a biodiversity conservation background having worked at a number of international conservation organisations including the International Union for Conservation of Nature as part of the Red List Unit where it was my role to review assessments submitted for publication of the global IUCN Red List, and the UN World Conservation Monitoring Centre where I worked as part of the Ecosystem Assessment Unit.

I studied Natural Sciences at the University of Cambridge for my undergraduate degree focusing on conservation, population and behavioural ecology in my final year, and Applied Ecology and Conservation for my Masters at the University of East Anglia. My master's thesis focused on using developing a low-cost UAV based system to evaluate carbon stocks using farmland forest segments as a study site.

Research interests

Combining my conservation background, ecological training and technological leanings my research interests are wide and include:

  • Use and development of remotely sensed data to monitoring ecosystem status, stability and health. 
  • Use and development of remotely sensed data to monitor ecosystem services. 
  • Ecosystem stability, resistance, resilience.
  • Machine learning algorithms to enable the processing and manipulation of "big" dataset. 
  • Multi and Hyperspectral imagery.
  • LIDAR. 
  • Applications of computer science more generally to conservation, and ecological research.

Qualifications

  • BA. Natural Sciences - Zoology (Hons.)
  • MSc Applied Ecology and Conservation (Hons.)