Unmanned Aerial Vehicles, or Drones, have become inexpensive tools for not only high quality aerial video and photography, but also spectral and topographic mapping.
Drones have become ubiquitous tools in the Natural Resources Industry.
Applications in forest harvesting can be grouped into pre-harvest applications and post-harvest applications.
Figure 1. Upper panels: Pre-harvest forest Stands; Lower panels: Post-harvest.
Orthophotos (aerial imagery) from reconaissance flights reveal details that are not possible to discern from the ground. Additionally, Drones quickly cover areas that would take days more to cover on foot.
The best forest stands can be identified from Drone aerial orthophotos. This optimizes the process of selecting locations for new cutblocks which to apply for.
During cutblock layout (where to cut, where to preserve), those same orthophotos can help pre-determining areas to partial out, such as due to wildlife reasons or forest stand composition.
Additionally, we have had ground crews (e.g., bunchers) mentioning that real-time georeferenced access to a detailed top-down view of the trees is of great help as they progress through the cutblock.
Legally-binding site plans are necessary and determine where harvest is to take place, but often do not include recent and detailed aerial imagery. But there is no reason to not include that kind of information, if available, into a site plan or a relativity lean logging plan.
Post harvest aerial photo-mosaics address one important component of licensees obligations: report to the government what was done relative to what had been planned. Post-harvest aerial photomosaics can be used for a detailed mapping of the post-harvest cutblock area.
Drones are also increasingly used for stock imaging and volume estimation purposes in lumber mills in general, pellet plants, biomass plants, etc.
Many companies are developing new applications. It is likely that Drones will be systematically used in the near future for silvicultural activities such as tree planting, at least in certain environments.