ARVI: A Vegetation Index That Sees Through Haze
Aerosols scatter blue light far more than red, and that asymmetry is what ARVI exploits: it uses the blue band to self-correct the red channel, so a hazy atmosphere distorts the result far less than it would a plain NDVI.
How it reads the surface
ARVI replaces NDVI's red term with a red–blue combination (2×Red − Blue). Because aerosol scattering brightens blue much more than red, subtracting a blue-weighted term cancels most of the atmospheric contamination before the normalized difference is even computed. Kaufman and Tanré built it for MODIS precisely so continental-scale mosaics would not be ruined by variable haze.
How it is calculated
where NIR is near-infrared reflectance, Red is red reflectance, Blue is blue reflectance.
What the numbers mean
Interpreted like NDVI, but more stable under hazy skies — the blue band is used to self-correct for aerosol scattering.
Band configuration
| Sentinel-2 | NIR B8 · Red B4 · Blue B2 |
| Landsat 8/9 | NIR B5 · Red B4 · Blue B2 |
Where it is used
ARVI is valuable over regions with chronic aerosol loading — biomass-burning seasons, dusty arid margins, polluted industrial corridors — and anywhere you are stitching many scenes with inconsistent atmospheric correction.
Limitations to know
In genuinely clear air the correction can over-shoot and slightly depress values; if your scene is haze-free, standard NDVI or EVI is usually the better choice.
Compute ARVI on your own study area
Skip the code. Draw or upload a boundary and Spatial Research Suite runs ARVI on live Sentinel-2 or Landsat imagery — with cloud masking, exports and citations built in.
Run this analysis in GISforus →Frequently asked
What problem does ARVI solve?
It reduces the effect of atmospheric aerosols and haze on the vegetation signal by using the blue band to self-correct the red channel.
Should I always use ARVI over NDVI?
No — in clear conditions it can slightly over-correct. Reserve it for hazy or aerosol-heavy scenes.