Peatlands are prevalent across northern regions, including bogs, fens, marshes, meadows, and select tundra wetlands that all vary in size (e.g., 0.01 s to 10 s km2) and shape (e.g., circular to elongated). However, our best remotely sensed products describing the regional-scale distribution of peatland extents are constrained to 1 km2 pixels, often representing notable sub-pixel heterogeneity and local-scale uncertainties. Here we develop a new 20 m spatial resolution wall-to-wall ~1.5 million km2 peatland map of Alaska, using peat cores, ground observations, and sub-meter resolution image interpretation. Ground-data were used to train machine learning classifiers to detect peatlands using a fusion of Sentinel-1 (Dual-polarized Synthetic Aperture Radar), Sentinel-2 (Multi-Spectral Imager), and derivatives from the Arctic Digital Elevation Model (ArcticDEM), that were spatially constrained by a peatland suitability model. Statewide peatland mapping (overall agreement:85%) identified peatlands to cover 4.6, 10.4, and 5.3% of polar, boreal, and maritime ecoregions, respectively, and 7.3% of the total terrestrial land area. This new dataset will improve the representation of peatland carbon, nutrient, and fire dynamics across Alaska.
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