Coloration Index

The Coloration Index (CI) was developed by Pouget et al. (1990) to characterize soil color properties in arid and semi-arid regions. Low CI values correlate with high concentrations of carbonates or sulfates, while higher values correlate with crusted soils and sands. The index helps monitor surface degradation and infiltrability variations. 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. CI is particularly suited for soil color characterization, carbonate and sulfate detection, surface degradation monitoring. The general formula is (RED - GREEN) / (RED + GREEN), which requires GREEN and RED spectral bands.

CI 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 (Red - Green) / (Red + Green), while BJ3N uses (Red - Green) / (Red + Green). Select a sensor above to see its specific band mapping.

CI requires GREEN (520-600), RED (640-760). 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.