Mark De Jong

Member of the NCEO-King's research group and the Earth and Environmental Dynamics research group.

• wildfire
• fire danger
• land surface temperature
• remote sensing
• atmospheric pollution

Mark was awarded a BSc in Environmental Science at the University of Leeds in 2008 with first class honours, and the Sally McGill Memorial Prize for exceptional academic achievement. During his undergraduate studies, he also completed an industrial placement as an Environmental Engineer at VHE Construction. After graduating Mark took advantage of his background in atmospheric science and worked at the Bermuda Institute Of Ocean Sciences for a year, monitoring Bermuda's environmental quality for the government, with a focus on air pollution.

After returning to the UK, Mark completed an MSc in Environmental Monitoring, Modelling and Management in the Department of Geography, King's College London in 2010, where he was awarded a distinction and the 'best physical geography thesis' prize. He then worked for 3 years as an air quality modelling scientist with the King's Environmental Research Group. Mark re-joined the King's Department of Geography in 2013 to take up a NERC funded PhD studentship.

Thesis Title: Fire incidence, characteristics and the influence of weather at landscape to regional scales

Viva passed subject to minor amendments, November 2018

Mark's thesis investigates patterns of wildfire incidence and relationships between fire incidence/fire characteristics and weather. It does so over landscape (100s to 10,000s km²) to regional (millions of km²) scales and over time periods ranging from several days to several decades. Specifically, the role of weather is examined through the Canadian Forest Fire Weather Index (FWI) System and its underlying meteorological variables. Three broadly related research areas are investigated, to determine:
1. whether a percentile-based calibration of the FWI System can be used to better identify
periods of high potential fire incidence in the United Kingdom (UK) than an existing
implementation of the System;
2. whether the FWI System can be used to support forecasting of the evolution of fire
activity captured by the Global Fire Assimilation System (GFAS; Kaiser et al. 2012) at
regional to global scales at 1 to 5-day lead times. Such developments could improve the
representation of biomass burning emissions in air quality forecasting models;
3. whether a new global night-time active fire dataset can be created using the extensive (>
30 year) Advanced Very High-Resolution Radiometer (AVHRR) Global Area Coverage
(GAC) archive, for the purpose of investigating the potential impacts of climate change
on regional patterns of fire over recent decades.