The Second Brightness Index (BI2) is an enhanced version of the Brightness Index that includes the near-infrared band in addition to red and green bands. Developed by Escadafal and Huete, it provides improved assessment of soil properties, particularly soil organic carbon content and moisture levels.

Used in crop monitoring, and forest monitoring.

When to use

  • Soil mapping in agricultural and arid environments
  • Salinity monitoring in irrigated areas
  • Erosion hazard assessment on bare ground
  • Organic matter and fertility surveys
  • Soil moisture inference (combined with other indices)
  • soil brightness assessment
  • soil organic carbon estimation

Limitations

  • Vegetation cover blocks the soil signal — most reliable on bare or sparse ground
  • Surface roughness and tilling state affect reflectance
  • Soil moisture varies daily and biases brightness measurements
  • Cannot directly measure subsurface properties
  • Mineral composition variability affects index calibration across regions

General Formula

GREEN 560
RED 665
NIR 842

Sensor-Specific Formulas

Most-used sensors — click to show code below

SensorProviderFormulaBand Mapping
21ATsqrt((Red^2 + Green^2 + NIR^2) / 3)GREEN→Green, RED→Red, NIR→NIR
CG Satellitesqrt((Red^2 + Green^2 + NIR^2) / 3)GREEN→Green, RED→Red, NIR→NIR
USGS/NASAsqrt((B4^2 + B3^2 + B5^2) / 3)GREEN→B3, RED→B4, NIR→B5
USDAsqrt((Red^2 + Green^2 + NIR^2) / 3)GREEN→Green, RED→Red, NIR→NIR
ESAsqrt((B4^2 + B3^2 + B8^2) / 3)GREEN→B3, RED→B4, NIR→B8
MAXARsqrt((Red^2 + Green^2 + NIR1^2) / 3)GREEN→Green, RED→Red, NIR→NIR1
MAXARsqrt((Red^2 + Green^2 + NIR1^2) / 3)GREEN→Green, RED→Red, NIR→NIR1

Spectral Band Visualization — BJ3A

Code Examples

Adapted for BJ3A bands —

bi2_bj3a.py

Frequently Asked Questions

What is the BI2 (Second Brightness Index) and when should I use it?

The Second Brightness Index (BI2) is an enhanced version of the Brightness Index that includes the near-infrared band in addition to red and green bands. Developed by Escadafal and Huete, it provides improved assessment of soil properties, particularly soil organic carbon content and moisture levels. Soil indices characterise surface properties including brightness, moisture content, organic matter, and salinity. They work best on bare or sparsely vegetated ground where the soil spectral signal is not obscured. BI2 is particularly suited for soil brightness assessment, soil organic carbon estimation, soil moisture detection. The general formula is sqrt((RED^2 + GREEN^2 + NIR^2) / 3), which requires GREEN and RED and NIR spectral bands.

Which satellite sensors can I use to calculate BI2?

BI2 is supported by 22 satellite sensors in our database, including BJ3A, BJ3N, Dragonette-2/3, Gaofen-1, Gaofen-2 and 17 more. Each sensor uses different band designations — for example, BJ3A uses the formula sqrt((Red^2 + Green^2 + NIR^2) / 3), while BJ3N uses sqrt((Red^2 + Green^2 + NIR^2) / 3). Select a sensor above to see its specific band mapping.

What spectral bands does BI2 require and why?

BI2 requires GREEN (560), RED (665), NIR (842). These wavelength regions target the specific spectral features that this index is designed to measure.

How do I calculate BI2 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.

BI2 vs other soil indices

IndexNameHow it differs
BIBrightness IndexAlternative soil index — different band combination
CIColoration IndexAlternative soil index — different band combination
NSDSNormalized Shortwave Infrared Difference Soil-MoistureAlternative soil index — different band combination
NSDSI1Normalized Shortwave-Infrared Difference Bare Soil Moisture Index 1Alternative soil index — different band combination

Related Soil Indices

References

Escadafal, R. and Huete, A. (1992) - Improvement in remote sensing of low vegetation cover in arid regions by correcting for soil 'brightness'

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