A vegetation index that accounts for soil background effects by using a perpendicular approach. Can estimate leaf area index and green biomass, useful for analyzing crop canopies and vegetation health. The index helps evaluate vegetation characteristics while accounting for soil influences.

Used in crop monitoring, and forest monitoring.

When to use

  • Time-series monitoring of crop health, growth stages, and stress detection
  • Land cover classification and vegetation type discrimination
  • Biomass estimation and net primary productivity studies
  • Drought impact assessment over agricultural and forest areas
  • Phenology tracking — green-up, peak season, and senescence
  • Vegetation assessment
  • Leaf area index estimation

Limitations

  • Saturates in dense canopies (LAI > 3) — values plateau and lose discrimination ability
  • Sensitive to atmospheric scattering, especially blue-band haze
  • Soil background contaminates measurements in sparsely vegetated areas
  • Sun-sensor geometry (BRDF effects) introduces variability across acquisitions
  • Cloud cover and shadows produce invalid pixels that need masking

What the values mean

-1 Water / Snow
-0.1 Bare ground / Built-up
0.1 Sparse / Stressed
0.3 Moderate vegetation
0.5 Healthy vegetation
0.7 Dense canopy
Surface typeTypical PVI
Open water, snow-0.3 to -0.1
Bare soil, urban-0.1 to 0.2
Sparse or stressed crops0.2 to 0.4
Healthy crops, grassland0.4 to 0.7
Dense forest, peak season0.7 to 0.9

General Formula

Sensor-Specific Formulas

Most-used sensors — click to show code below

SensorProviderFormulaBand Mapping

Code Examples

pvi_generic.py

PVI vs other vegetation indices

IndexNameHow it differs
ARIAnthocyanin Reflectance IndexAlternative vegetation index — different band combination
mARIModified Anthocyanin Reflectance IndexRefined formulation for specific conditions
ARVIAtmospherically Resistant Vegetation IndexAtmospherically corrected version
ARVI2Atmospherically Resistant Vegetation Index 2Atmospherically corrected version

Related Vegetation Indices

References

Bannari et al. (1995)
Baret & Guyot (1991)
Huete (1988)

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