Modified Anthocyanin Reflectance Index
The Modified Anthocyanin Reflectance Index (mARI or ARI2) is an enhanced version of ARI that corrects for leaf density and thickness by incorporating a near-infrared band. This modification improves the accuracy of anthocyanin estimation by accounting for leaf scattering properties.
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
- anthocyanin content estimation
- leaf density correction
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
| Surface type | Typical mARI |
|---|---|
| Open water, snow | -0.3 to -0.1 |
| Bare soil, urban | -0.1 to 0.2 |
| Sparse or stressed crops | 0.2 to 0.4 |
| Healthy crops, grassland | 0.4 to 0.7 |
| Dense forest, peak season | 0.7 to 0.9 |
General Formula
Sensor-Specific Formulas
Most-used sensors — click to show code below
| Sensor | Provider | Formula | Band Mapping |
|---|---|---|---|
| 21AT | ((1 / Green) - (1 / Red)) * NIR | 550→Green, 700→Red, NIR→NIR | |
| CG Satellite | ((1 / Green) - (1 / Red)) * NIR | 550→Green, 700→Red, NIR→NIR | |
| ESA | ((1 / B3) - (1 / B5)) * B7 | 550→B3, 700→B5, NIR→B7 | |
| MAXAR | ((1 / Green) - (1 / Red Edge)) * NIR1 | 550→Green, 700→Red Edge, NIR→NIR1 | |
| MAXAR | ((1 / Green) - (1 / Red_Edge)) * NIR1 | 550→Green, 700→Red_Edge, NIR→NIR1 |
Spectral Band Visualization — BJ3A
Code Examples
Adapted for BJ3A bands —
Frequently Asked Questions
What is the mARI (Modified Anthocyanin Reflectance Index) and when should I use it?
The Modified Anthocyanin Reflectance Index (mARI or ARI2) is an enhanced version of ARI that corrects for leaf density and thickness by incorporating a near-infrared band. This modification improves the accuracy of anthocyanin estimation by accounting for leaf scattering properties. 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. mARI is particularly suited for anthocyanin content estimation, leaf density correction, plant stress detection. The general formula is ((1 / 550nm) - (1 / 700nm)) * NIR, which requires 550 and 700 and NIR spectral bands.
Which satellite sensors can I use to calculate mARI?
mARI is supported by 21 satellite sensors in our database, including BJ3A, BJ3N, Dragonette-1, Dragonette-2/3, Gaofen-1 and 16 more. Each sensor uses different band designations — for example, BJ3A uses the formula ((1 / Green) - (1 / Red)) * NIR, while BJ3N uses ((1 / Green) - (1 / Red)) * NIR. Select a sensor above to see its specific band mapping.
What spectral bands does mARI require and why?
mARI requires 550 (550), 700 (700), NIR (760-800). 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 mARI 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 mARI compare to NDVI and other vegetation indices?
While NDVI is the most common vegetation index, mARI provides complementary information that NDVI cannot capture on its own. The choice of index depends on your application, sensor availability, and atmospheric conditions.
mARI vs other vegetation indices
| Index | Name | How it differs |
|---|---|---|
| ARI | Anthocyanin Reflectance Index | Alternative vegetation index — different band combination |
| ARVI | Atmospherically Resistant Vegetation Index | Atmospherically corrected version |
| ARVI2 | Atmospherically Resistant Vegetation Index 2 | Atmospherically corrected version |
| BGI | Blue Green Pigment Index | Uses green band for chlorophyll sensitivity |
Related Vegetation Indices
References
Need help choosing?
Ask our AI assistant for sensor recommendations, code examples, or how mARI compares to other indices for your specific use case.