PROJECT TITLE:

Retrieving Vegetation Reradiation Patterns by Means of Artificial Neural Networks

ABSTRACT:

Modeling vegetation sometimes implies obtaining experimental knowledge by means of measurement campaigns. Generally, the foremost correct models want the reradiation pattern of the vegetation volume beneath study, or a number of its connected parameters. Getting this perform might not be straightforward, and therefore the measurement procedure might introduce errors relying on the placement of the vegetation mass. An correct tool to simplify this process is presented, based mostly on the flexibility of artificial neural networks to infer behavioral patterns. This proposal reduces the acquisition of the experimental information to a scarce set of angles around the tree or bush, which will then be used to train a neural network capable of retrieving the specified reradiation operate desired.