Simple Ratio 695/760 Carter2

Carter2 (Ctr2) is a plant stress index that uses the ratio of reflectance at 695nm (red-edge) to 760nm (near-infrared). This index is particularly effective at detecting stress because it combines the stress-sensitive red-edge region with the NIR region where healthy vegetation shows high reflectance. 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. Ctr2 is particularly suited for plant stress detection, vegetation health monitoring, water stress assessment. The general formula is 695nm / 760nm, which requires 695 and 760 spectral bands.

Ctr2 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 Red / NIR, while BJ3N uses Red / NIR. Select a sensor above to see its specific band mapping.

Ctr2 requires 695 (695), 760 (760). 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.

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.

While NDVI is the most common vegetation index, Ctr2 provides complementary information that NDVI cannot capture on its own. The choice of index depends on your application, sensor availability, and atmospheric conditions.