EO·Atlas
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]
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- [1]Hyperspectral image analysis techniques for early plant disease and stress detectionpeer reviewed2017-10-052026-05-27
- [2]Current state of hyperspectral remote sensing for early plant disease detectionpeer reviewed2022-01-202026-05-27
- [3]FAO geospatial focus: land cover and crop monitoringagency doc-2026-05-27
How to cite this page
Plain text
Pest and disease detection. EO-Atlas, SpectraWorks B.V., last reviewed 2026-05-27. https://eo-atlas.org/topics/pest-disease (CC BY 4.0)
BibTeX
@misc{eoatlas:topics:pest-disease,
title = {Pest and disease detection},
author = {{EO-Atlas}},
publisher = {SpectraWorks B.V.},
year = {2026},
note = {Last reviewed 2026-05-27. CC BY 4.0},
url = {https://eo-atlas.org/topics/pest-disease}
}