Goals
Identification of individual trees in the forest and detecting their physical attributes (trunk diameter, height, volume, etc.)
Tasks
Producing thematic maps and layers by processing aerial remote sensing data and field data.
Applied technologies
- aerial hyperspectral imagery
- airborne laser scanning technology (LiDAR)
- digital medium format imagery
- ground based surveys
End products
Map of tree species
Detecting diseased tree species (red) in a forested area
Maps of invasive species
Map of tree species
Map of general health of trees
Digital orthophoto map of a forest
Terrain and surface models of forest
LiDAR point cloud coloured by tree species
Canopy detection model
Transformed hyperspectral bands visualised in LiDAR point cloud
Canopy models segmented on a topographical model
How can these technologies help forest management?
- The data process and integrated analysis of data assessed by modern active and passive remote sensing technologies basic data is produced that is applicable to evaluate the actual state of the forest together with the information related to the relief characteristics of the examined area (aspect, slope, elevation above sea level).
- The produced information contributes to:
- the improvement of forest management planning protocol either in state owned or private forests;
- map the health condition of the forest, determine the various applicable management methods, and identify the areas of encroachment.
- Data retrieved from aerial remote sensing can help to identify tree species, to detect invasive species, to determine the points of intervention and to determine the health condition of the forest.
- Basic maps supplied by this new information increase the real estate value of a given forest. Repeated assessments give the possibility of monitoring the growth and health condition changes of the trees.