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Lidar-based Norwegian tree species detection using deep learning
Methods: We present a deep learning based tree species classification model utilizing only lidar (Light Detection And Ranging) data.
Prediction of butt rot volume in Norway spruce forest stands using harvester, remotely sensed and environmental data
We found that forest attributes characterizing the maturity of forest, such as remote sensing-based height, harvested timber volume and quadratic mean diameter at breast height, were among the most important predictor variables.
National mapping and estimation of forest area by dominant tree species using Sentinel-2 data
However, even for municipalities with a decent number of NFI plots, direct NFI estimates were sometimes more precise than MA estimates.
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