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.