Brightness Index

The Brightness Index (BI) is a remote sensing index used to assess soil brightness, which is highly correlated with soil moisture, salt content, and organic matter. Developed by Mathieu and Escadafal, it provides valuable information about soil properties and fertility. As brightness increases, soil fertility typically decreases. 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. BI is particularly suited for soil brightness assessment, soil moisture detection, salt content evaluation. The general formula is sqrt((RED^2 + GREEN^2) / 2), which requires GREEN and RED spectral bands.

BI is supported by 23 satellite sensors in our database, including BJ3A, BJ3N, Dragonette-1, Dragonette-2/3, Gaofen-1 and 18 more. Each sensor uses different band designations — for example, BJ3A uses the formula sqrt((Red^2 + Green^2) / 2), while BJ3N uses sqrt((Red^2 + Green^2) / 2). Select a sensor above to see its specific band mapping.

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

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.