Leverhulme Wildfires Centre Leverhulme Wildfires Centre

Machine Learning and Data Assimilation for Accurate Wildfire Predictions and Estimations.

Twitter is increasingly being used as a real-time human-sensor network during natural disasters, detecting, tracking and documenting these events. Social media data represents a large amount of publicly available, unprocessed social data which is both opinionated, informative, and emotional. During disaster scenarios, users post a geographically and emotionally subjective account of events unfolding locally. There is scope for this information to be collated and analysed in real-time, and incorporated into wildfire models to improve their accuracy. 

This PhD project aims to help make disaster management teams make more informed, data driven decisions by including social media analysis as a data source in real-time wildfire models. In doing this, we aim to create more socially conscious wildfire models, which consider the impacts of wildfire spread.

Project duration: 2020-2024

Leadership Team

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In recent years wildfires have made headlines in Australia, California, continental Europe and even the UK, and satellite data are the only way to robustly track and quantify the phenomena across such large scales, something that can now be done close to real-time. Two traits of particular interest are fire intensity and combustion phase (i.e. smouldering vs. flaming), which strongly influence the amount and chemical composition of smoke and in turn controls its impact on the atmosphere and on air quality. Whilst satellite data are commonly used to identify where fires are burning, there are no proven means currently of extracting these fire characteristics, and even detecting the fires requires use of manually tuned algorithms that are time-consuming to optimise.

This project will explore the use of multi and hyper-spectral laboratory and airborne remote sensing in characterising landscape fires, and ultimately the use of such metrics to help improve and validate new information extractable from satellite observations of active fires.

This project is also co-supervised by Rob Francis, KCL.

 

KCL combustion chamber at Rothamsted Research. Photo: Martin Wooster.

 

British Antarctic Survey aeroplane, fitted with KCL remote sensing equipment. Photo: Adriana Ford, Leverhulme Wildfires 2021

 

Leadership Team

Meet the team

The northern extratropics has experienced increases in fire activity in recent decades, which have had important consequences for ecosystems, carbon cycling and human societies. There is currently wide uncertainty in predictions of how fire will respond to climate changes in this region in the coming decades. Studying fire responses over palaeo timescales provides a window into how fire may respond to large environmental changes, which are anticipated to play out over the course of this century. This project will leverage a newly-created global palaeo charcoal database, the Reading Palaeofire Database, to reconstruct changes in biomass burning across the circum-northern extratropics over the Holocene. It will attempt to explain patterns in fire activity over millennia in this region by quantitatively linking sub-continental scale fire responses to climate, vegetation and human-induced landscape shifts. This will provide novel insights into the importance of various environmental reorganisations in shaping fire regimes, which can directly contribute to attempts at better constraining predictions of future changes in wildfire patterns.

Project Duration: 2019-2023

Leadership Team

Meet the team

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