Webinar - Mapping Canada's Peatlands Using Remote Sensing

Peatlands in the Canadian Boreal Forest are being negatively impacted by anthropogenic climate change, the effects of which are expected to worsen. Peatland types and sub-classes vary in their ecohydrological characteristics and are expected to have different responses to climate change. Large-scale modelling frameworks such as the Canadian Model for Peatlands, the Canadian Fire Behaviour Prediction System, and the Canadian Land Data Assimilation System require peatland maps, including information on sub-types and vegetation, as critical inputs. Additionally, peatland class and vegetation height are crucial variables for wildlife habitat management and are related to the carbon cycle and wildfire fuel loading. This study aimed to create a peatland sub-class map (bog, poor fen, rich fen, permafrost peat complexes) for the Canadian boreal forest, and inventory peatland vegetation height characteristics using ICESat-2 data. Employing a three-stage hierarchical classification framework, peatland sub-classes were mapped using diverse data sources, including optical data, Synthetic Aperture Radar, forest structure, and ancillary variables.