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education and research in the areas of forest planning, forest remote sensing, forest inventory and sampling, forest mathematical statistics and landscape studies. The department is also responsible
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, biogeochemical cycles, ecosystems, and environmental conditions, and/or statistical analyses of large datasets, including from remote sensing, as well as strong quantitative and programming skills (in MatLab, R
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operations aiming to promote growth rate or improve stem. Some stand conditions and tree characteristics can be measured remotely, as for example using remote sensing technologies. Ideally, such technologies
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