A red edge variant of VARI that uses red edge bands instead of green. This index is designed to estimate vegetation fraction with reduced atmospheric effects.

Used in crop 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 fraction estimation
  • Red edge position analysis

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 VARIrededge
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

red 620-680
re1 700-710

Sensor-Specific Formulas

Most-used sensors — click to show code below

SensorProviderFormulaBand Mapping
Wyvern(Band 16 - Band 11) / (Band 16 + Band 11)red→Band 11, re1→Band 16
ESA(B5 - B4) / (B5 + B4)red→B4, re1→B5
MAXAR(Red Edge - Red) / (Red Edge + Red)red→Red, re1→Red Edge
MAXAR(Red_Edge - Red) / (Red_Edge + Red)red→Red, re1→Red_Edge

Spectral Band Visualization — Dragonette-1

Code Examples

Adapted for Dragonette-1 bands —

vari_rededge_dragonette-001.py

Frequently Asked Questions

What is the VARIrededge (Visible Atmospherically Resistant Index Red Edge) and when should I use it?

A red edge variant of VARI that uses red edge bands instead of green. This index is designed to estimate vegetation fraction with reduced atmospheric effects. Vegetation indices quantify plant health, biomass, and photosynthetic activity by exploiting the contrast between how plants absorb visible light for photosynthesis and reflect near-infrared radiation from their cellular structure. VARIrededge is particularly suited for vegetation fraction estimation, red edge position analysis, atmospheric correction. The general formula is (RE1 - Red) / (RE1 + Red), which requires red and re1 spectral bands.

Which satellite sensors can I use to calculate VARIrededge?

VARIrededge is supported by 15 satellite sensors in our database, including Dragonette-1, Dragonette-2/3, Gaofen-1, Gaofen-2, GeoEye-1 and 10 more. Each sensor uses different band designations — for example, Dragonette-1 uses the formula (Band 16 - Band 11) / (Band 16 + Band 11), while Dragonette-2/3 uses (Band20 - Band15) / (Band20 + Band15). Select a sensor above to see its specific band mapping.

What spectral bands does VARIrededge require and why?

VARIrededge requires red (620-680), re1 (700-710). Vegetation strongly absorbs red light for photosynthesis while reflecting near-infrared light from its mesophyll cell structure, making this contrast a reliable indicator of plant vigour.

How do I calculate VARIrededge in Python or R?

Both Python and R code samples are provided above. In Python, use rasterio to load individual band GeoTIFF files and numpy for the arithmetic. In R, the terra package handles raster operations efficiently. The key is to load bands as floating-point arrays to avoid integer division, and to handle division-by-zero cases where the denominator equals zero. For production use, consider applying a valid data mask to exclude no-data pixels before calculation.

How does VARIrededge compare to NDVI and other vegetation indices?

While NDVI is the most common vegetation index, VARIrededge provides complementary information that NDVI cannot capture on its own. The choice of index depends on your application, sensor availability, and atmospheric conditions.

VARIrededge 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

Gitelson et al. (2002). Novel algorithms for remote estimation of vegetation fraction.
Gitelson et al. (2003). Remote estimation of leaf area index and green leaf biomass in maize canopies.
Ahamed et al. (2011). A review of remote sensing methods for biomass feedstock production.

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