Mapping of peatlands in the forested landscape of Sweden using LiDAR-based terrain indices

Abstract. Globally, northern peatlands are major carbon deposits with important implications for the climate system. It is therefore crucial to understand their spatial occurrence, especially in the context of peatland degradation by land cover and climate change. This study was aimed at mapping peatlands in the forested landscape of Sweden by modelling soil data against LiDAR-based terrain indices. Machine learning methods were used to produce nation-wide raster maps at 10 m spatial resolution indicating presence-or-not of peatlands. Four different definitions of peatlands were examined: 30, 40, 50 and 100 cm thickness of the organic horizon. Depending on peatland definition, testing with a hold-out dataset indicated Accuracy of 0.89–0.91 and Matthew’s correlation coefficient of 0.79–0.81. The final maps showed a national forest peatland extent of 60,726–72,604 km², estimates which are in range with previous studies employing traditional soil maps. In conclusion, these results emphasize the possibilities of mapping boreal peatlands with LiDAR-based terrain indices. The final peatland maps are publicly available and may be employed for spatial planning, estimating carbon stocks and evaluate climate change mitigation strategies.