Ågren, Anneli
- Department of Forest Ecology and Management, Swedish University of Agricultural Sciences
To meet the sustainable development goals and enable sustainable management and protection of peatlands, there is a strong need for improving the mapping of peatlands. Here we present a novel approach to identify peat soils based on a high-resolution digital soil moisture map that was produced by combining airborne laser scanning-derived terrain indices and machine learning to model soil moisture at 2 m spatial resolution across the Swedish landscape. As soil moisture is a key factor in peat formation, we fitted an empirical relationship between the thickness of the organic layer (measured at 5479 soil plots across the country) and the continuous SLU (Swedish University of Agricultural Science) soil moisture map (R2= 0.66, p
Soil
2022, volume: 8, number: 2, pages: 733-749
Soil Science
Agricultural Science
https://res.slu.se/id/publ/120026