Forest Resource Assessment using Stochastic Geometry

Aerial and satellite imagery has a key role to play in natural resource management, especially in forestry application. The submetric resolution of the data enables to study forests at the scale of trees, and opens up new prospects to inventories in their will to get accurate assessment of the resources, with some automatic algorithms when possible. In this paper, we present a method to extract tree crowns from high resolution aerial Color Infrared images (CIR) of forests using marked point processes. Our approach consists in modelling the trees in the forestry images as random configurations of ellipses or ellipsoids, whose points are the positions of the stems and marks their geometric features. The goal is to find the best configuration of objects, from which 2D and 3D vegetation resource parameters can be extracted. Results are shown on aerial CIR images of plantations and isolated trees provided by the French National Forest Inventory (IFN).