This document describes a use case that makes use of machine learning techniques along with various remote sensing data sources to detect changes in land cover for Forest Health Monitoring.
The objective of this use case is to demonstrate the capacity of remote sensing in extracting adequate information that can be used for purposes of research such as:
- designation of spatial distribution of the health condition of the forests,
- multitemporal analysis of changes in the canopy condition,
- indication of crucial biotic and abiotic environmental factors, which impacts the forest condition,
- forecast of changes in the health condition of the forest.
The development of methods for the applications mentioned above might provide the new solutions for the damage evaluation and reporting, decision making policies and indicating future countermeasures in case to protect the forests.