Drones equipped with multispectral and hyperspectral cameras can assess vegetation health by analyzing light reflected at different wavelengths. These images highlight physiological changes in plants long before symptoms are visible to the naked eye. Indices like NDVI, derived from spectral data, provide quantitative measures of forest canopy health, enabling detection of stress factors such as drought, pest infestation, or nutrient deficiencies across large areas.
Recent advancements in photogrammetry allow drones to produce detailed 3D models of forest canopies. These models offer insights into canopy density, gaps, and tree height distribution, which are critical for assessing forest structural diversity and biomass. By comparing models from different time periods, managers can monitor growth trends, the effectiveness of restoration projects, and the impact of disturbances such as storms or logging events.
Integrating thermal sensors on drones enhances detection of water stress, pest infestations, and disease outbreaks by capturing heat signatures emitted by vegetation. Warm or cool areas in thermal imagery often signal physiological changes, and when combined with visible and multispectral data, this information pinpoints areas that require urgent attention. This multi-layered mapping approach supports early intervention, safeguarding forest health on a landscape-wide scale.