Project highlights

  • Join this exciting opportunity in collaboration with Forest Research, UK’s largest forestry and tree-related research agency to assess the extent to which compound climate and weather events generate forest disturbances.  
  • An exciting opportunity to integrate remote sensing and airborne data, climate model outputs, field surveys, and data science and machine learning approaches.  
  • The project outputs will contribute to the development of new management strategies to mitigate forest damage and promote resilience in a changing climate. 


Forests are critical to the realisation of UK net-zero ambitions through carbon sequestration. However, these valuable ecosystems can suffer from catastrophic forest damage and disturbances, exacerbated by the increasing impacts from compound climate events in a changing climate. This can have a significant impact on ecosystem services, such as water filtration, carbon sequestration, and wildlife habitat. As our climate changes, the increase in frequency and intensity of extreme weather events, such as droughts, storms, heat waves and their joint occurrences (IPCC 2021), threatens forests profoundly. This, in turn, leads to various forms of forest damage, from disturbance to windthrow and tree mortality, triggering both ecological and economic implications. These multiple climatic phenomena can have a compounding effect when they coincide or follow in succession. The compounded effects can amplify vulnerabilities, making trees more susceptible to hazards like windthrow. A drought may set the stage for subsequent threats, or a sequence of droughts and storms may compromise forest resilience and amplify the spread of disease. The cumulative impact of compound events often surpasses the isolated influence of individual climate events, as underscored by recent research, such as Gazol et al. (2022), which highlighted the role of combined climate events, particularly hot and dry conditions, in accentuating tree drought mortality within European forests. 

This PhD project aims to advance our understanding of forest disturbances and their association with compound extreme weather events, focusing on forest margins as biodiversity hotspots. The successful candidate will use open and proprietary Earth observation (EO) data, including airborne remote sensing and machine learning techniques, to detect and monitor forest damage. The project will explore the potential climate drivers, including both singular and interlinked extremes, that contribute to these disturbances. It will also use models such as ForestGALES and 3PG-SoNWaL to predict the risk impacts on forest function, including wind risk and climate impacts on productivity. 

This research has the potential to provide valuable insights for informed stand-level management decisions in the productive forestry sector, in light of future climate shifts. 

Image of a diagram with trees in the background and arrows and captions illustrating a cyclical mechanism.

Figure 1: An example of a compounding physical mechanisms of hot-dry extremes and the impact on land-atmosphere interactions (Zhang et al., 2021). The evaporation is associated with land conditions and plant physiology during droughts and heat waves, potentially modulating the atmospheric boundary layer state 

Case funding

This project is suitable for CASE funding


Cranfield University


  • Climate and Environmental Sustainability
  • Organisms and Ecosystems


Project investigator

Dr Abdou Khouakhi, [email protected]


Prof Paul Burges, Cranfield University, [email protected]

Dr Mike Perks, Forest Research, [email protected]

Dr Tom Locatelli, Forest research, [email protected]

How to apply


The project will use an integrated approach, including diverse satellite imagery, airborne measurements and machine learning techniques to assess forest damage in a case study area of England and to develop and refine automated detection and classification methodologies for disturbances. The key drivers of forest disturbances, with a particular focus on forest margins, will be then investigated, investigating factors such as soil conditions, species, stand age, stand composition, and past land management practices. The connection between climate extremes—such as droughts, storms, and temperature fluctuations—and forest margin disturbances will be analysed. By looking at historical climate data and disturbance patterns, correlations and potential causal mechanisms will be identified. Future risk forecasting of forest disturbances under evolving climate scenarios, using climate scenarios such as UKCIP18, will be an integral component. The investigation will be extended to compound extreme weather events, with the impact of forest edges on stand-level disturbance being quantified, and instances of multiple extreme events coinciding will be analysed. The combination of field assessments in diverse ecoclines and modelling will be used to help inform forest management in the face of changing risk under future climates. 

Training and skills

Students will be awarded CENTA2 Training Credits (CTCs) for participation in CENTA2-provided and ‘free choice’ external training. One CTC equates to 1⁄2 day session and students must accrue 100 CTCs across the three years of their PhD.  

The student will have access to relevant MSc modules taught at Cranfield University such as Applied Remote Sensing, Advanced GIS, and Modelling Environmental Processes). Training in Python and R for data science, statistical analysis and woodland modelling will be provided by the supervisory team. There will be opportunities to attend various other trainings, short courses and seminars through Cranfield’s Doctoral Training Centre, encouraging effective and vibrant research.  The successful candidate will spend a part of the PhD working in the field with Forest Research scientists. 

Partners and collaboration

Forest Research is the research agency of the Forestry Commission and the UK’s principal organisation for forestry and tree-related research. Renowned internationally, it delivers evidence and scientific services to support sustainable forestry. With a history of innovative interdisciplinary research, it advises and supports the forestry sector, covering topics from forest management to urban forests. Informing government policy, Forest Research is instrumental in decision-making on forestry and related issues, ensuring a resilient approach to the impact of factors like climate change, pests, diseases, and population growth. 

Further details

Further details on how to contact the supervisor for this project and how to apply for this project can be found here: 

For any enquiries related to this project please contact Dr Abdou Khouakhi (Cranfield University) by email: [email protected]. 

To apply to this project: 

Applications must be submitted by 23:59 GMT on Wednesday 10th January 2024. 

Possible timeline

Year 1

This PhD project is expected to take 3.5 years to complete. The first year will be spent on literature review, data collection, and developing the research methods. The second year will be spent on EO data analysis, ML model development and testing, and investigating underlying factors including field assessments. The third year will be spent on testing the models, analyse interlinked extremes, that collectively contribute to forest disturbances, identify forest disturbance future risks and writing the thesis. 

Year 2

See Year 1 above.

Year 3

See Year 1 above.

Further reading


Zhang, W., Luo, M., Gao, S., Chen, W., Hari, V., Khouakhi, A., Steeneveld, G.-J., Chen, W.-B., & Varlas, G. (2021). Compound Extremes: Drivers. Mechanisms and Methods. Front. Earth Sci, 9(13), 673495. 

Gazol, A., & Camarero, J. J. (2022). Compound climate events increase tree drought mortality across European forests. Science of The Total Environment, 816, 151604.