Pest and disease detection

Pest and disease detection maps crop stress caused by insects, fungi, bacteria, or viruses through spectral and textural changes in canopy reflectance.^[1][2]

Hyperspectral imaging is the strongest EO route for early plant disease detection because narrow contiguous bands can capture physiological stress before symptoms are obvious in broad-band imagery.^[1][2]

Multispectral vegetation indices support broad screening, but they cannot reliably separate pest or pathogen damage from drought, nutrient deficiency, or other canopy stress without models and ground truth.^[1][3]

Operational value depends on crop, pathogen, growth stage, cloud-free cadence, and validation data, and disease-specific classifiers do not transfer automatically across regions.^[2][3]