Estimating forest stands vigor from airborne images and neural networks

摘要

The vigor of a tree defines its ability to grow and is associated with its productivity ([1]; [2]). The measurement of a tree's vigor makes it possible to evaluate its general state of health and its development over time. This task is traditionally performed by identifying defects affecting the vigor such as visible signs and symptoms on the tree, like fungi on the main stem, significant forks, cracks, wounds, competition and the percentage of living crown ([2]). The vigor and quality of trees are important factors used by forest managers in the application of silvicultural prescriptions at stand and landscape levels. The estimation of the level of risk of vigor loss in forest stands thus becomes a major and essential issue for the management and the improvement of the productivity of forests in a context of sustainable development.