Plausible scenarios of future land use derived from model projections may differ substantially from what is actually desired by society, and identifying such mismatches is important for identifying
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at risk of damage in storms.
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This report is a deliverable from the EU FP6 Integrated Project EFORWOOD – Tools for Sustainability Impact Assessment of the Forestry-Wood Chain. More information Recommended citation: Filip Aggestam
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