Leverhulme Wildfires Centre

Key past publications from our Team

• Integrating wildfire spread and evacuation times to design safe triggers: Application to two rural communities using PERIL model

  Safety Science

  Mitchell, H., Gwynne, S., Ronchi, E., Kalogeropoulos, N., and Rein, G. (2022)

   

• GAMBUT field experiment of peatland wildfires in Sumatra: from ignition to spread and suppression

  International Journal of Wildland Fire

  Santoso, M.A., Christensen, E.G., Amin, H.M.F., Palamba, P., Hu, Y., Purnomo, D.M.J., Cui, W., Pamitran, A., Richter, F., Smith, T.E.L., Nugroho, Y.S. and Rein, G. (2022)

• Systematic Mapping and Review of Landscape Fire Smoke (LFS) Exposure Impacts on Insects

  Environmental Entomology

  Liu, Y., Francis, R.A., Wooster, M. J., Grosvenor, M.J., Yan, S., and Roberts, G. (2022)

• Sentimental wildfire: a social-physics machine learning model for wildfire nowcasting

  Journal of Computational Social Science

  Lever, J. and Arcucci, R. (2022)

  Blog post

• Social Data Assimilation of Human Sensor Networks for Wildfires

  PETRA '22: Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments

  Lever, J., Arcucci, R., and Cai, J. (2022)

• Parameter Flexible Wildfire Prediction Using Machine Learning Techniques: Forward and Inverse Modelling

  Remote Sensing

  Cheng, S., Jin, Y., Harrison, S.P., Quilodrán-Casas, C., Prentice, I.C., Guo, Y-K., Arcucci, R., 2022.

• Human Fire Use and Management: A Global Database of Anthropogenic Fire Impacts for Modelling

  Fire

  Millington, J.D.A., Perkins, O. and Smith, C. (2022)

  Blog post

• Parameter Flexible Wildfire Prediction Using Machine Learning Techniques: Forward and Inverse Modelling

  Remote Sensing

  Cheng, S., Jin, Y., Harrison, S.P., Quilodrán-Casas, C., Prentice, I.C., Guo, Y, and Arcucci, R., (2022)

• Assessing anthropogenic influence on fire history during the Holocene in the Iberian Peninsula

  Quaternary Science Reviews

  Sweeney, L., Harrison, S.P. and Vander Linden, M. (2022)

• Towards Social Machine Learning for Natural Disasters

  International Conference on Computational Science

  Lever, J. and Arcucci, R. (2022)

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