Peatland burning identification among other wildfires across different ecozones in Canada
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chen-chenm736-meng-cee-2025-thesis.pdf
Description
Thesis PDF
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4.32 MB
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Adobe PDF
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500a520c3e79f1636f4c2e9d1ea00ad5
Author(s)
Chen, Ming
Advisor(s)
Terrer, César
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
The unprecedented severity of the 2023 Canadian wildfires highlights growing concerns about the vulnerability of global peatlands—key ecosystems storing substantial amounts of terrestrial carbon. Peatlands, traditionally resistant to burning, are increasingly at risk due to climate-induced warmer and drier conditions. This study specifically investigates the extent and characteristics of peat burning in the 2023 Canadian wildfires based on available remote sensing data. The primary objective is to determine whether fires on peatlands demonstrate distinct fire behavior compared to fires on non-peatland. To achieve this goal, this study utilized statistical tools and machine learning algorithms, including power-law relationship estimates, Mann-Whitney U test, K-means clustering, and generalized additive model (GAM) to identify the contribution of peat presence to fire behaviors. Key findings demonstrate that fires on peatland are significantly more intense, longer-lasting, and associated with higher carbon emissions. Even though peat combustion can not be confirmed without field validations, these results underscore the critical importance of the potential impact of peat on wildfire growth and management. By highlighting the disproportionate impact of peat burning, this study provides a foundation for future research aimed at developing targeted remote sensing techniques and policy responses to mitigate peatland vulnerability and preserve vital carbon stores in the context of global climate change.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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