A hierarchical, multi‐sensor framework for peatland sub‐class and vegetation mapping throughout the Canadian boreal forest

Abstract

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 critical variables for wildlife habitat management and are related to the carbon cycle and wildfire fuel loading. This research aimed to create a map of peatland sub‐classes (bog, poor fen, rich fen permafrost peat complex) for the Canadian boreal forest and create an inventory of peatland vegetation height characteristics using ICESat‐2. A three‐stage hierarchical classification framework was developed to map peatland sub‐classes within the Canadian boreal forest circa 2020. Training and validation data consisted of peatland locations derived from various sources (field data, aerial photo interpretation, measurements documented in literature). A combination of multispectral data, L‐band SAR backscatter and C‐Band interferometric SAR coherence, forest structure and ancillary variables was used as model predictors. Ancillary data were used to mask agricultural areas and urban regions and account for regions that may exhibit permafrost. In the first stage of the classification, wetlands, uplands and water were classified with 86.5% accuracy. In the second stage, within the wetland areas only, peatland and mineral wetlands were differentiated with 93.3% accuracy. In the third stage, constrained to only the peatland areas, bogs, rich fens, poor fens and permafrost peat complexes were classified with 71.5% accuracy. Then, ICESat‐2 ATL08 spaceborne lidar data were used to describe regional variations in peatland vegetation height characteristics and regional and class‐wise variations based on a boreal forest wide sample. This research introduced a comprehensive large‐scale peatland sub‐class mapping framework for the Canadian boreal forest, presenting the first moderate resolution map of its kind.

Carbon Stocks and Fluxes From a Boreal Conifer Swamp: Filling a Knowledge Gap for Understanding the Boreal C Cycle

“…Although they have variable definitions across the literature, swamps across northern regions are generally characterized by having at least 25% tree cover at >5 m height, a canopy cover that in many cases is comparable to adjacent uplands, leading to the potential for misclassification based on aerial surveys (Ducks Unlimited Canada, 2021;Locky et al, 2005;NWWG, 1997). Thus, they are not yet included in some wetland mapping studies (Pontone et al, 2024). Unlike other northern wetland types, such as bogs and fens, swamps can also be considered either mineral or peat-forming and therefore have a wide range of soil carbon masses per unit area in the literature (Byun et al, 2018;Davidson et al, 2022;Dazé et al, 2022;NWWG, 1997).…”