Automatic recognition of single trees in remote sensing data is an important research topic in the context of sustainable forest management: In many countries, single-tree related parameters are used as a basis for forest inventory, e.g. tree species, mean tree height or timber volume. Until now, the majority of these parameters are collected manually by measurement of sample plots in cost- and time-intensive field surveys. However, remote sensing-based methods have gained increasing attention during recent decades [1]. In the remote sensing context, an additional application of single tree extraction is driven by the goal to generate information for city tree cadastres or to add layers to geoinformation systems and 3D city models [2].
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Automatic recognition of single trees in remote sensing data is an important research topic in the context of sustainable forest management: In many countries, single-tree related parameters are used as a basis for forest inventory, e.g. tree species, mean tree height or timber volume. Until now, the majority of these parameters are collected manually by measurement of sample plots in cost- and time-intensive field surveys. However, remote sensing-based methods have gained increasing attention d...
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