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-driven, machine learning approaches. The biomass data product will be validated by data from an international network of ground-truth forest sites (GEO-TREES, geo-trees.org). The developed algorithms thus
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to mountains in Central and Southern Europe), covering climatic and N-P deposition gradients. The project consists of an interdisciplinary consortium, with a core of hydro(geo)logists and biogeochemists, with
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as source for input into our GIC simulations. b) Develop efficient optimization algorithms to identify geo-electric fields and GIC hotspots in Sweden. The two year long postdoctoral project is financed
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