Normalized Near-Infrared

Normalized near-infrared reflectance component for vegetation analysis. Highlights vegetation structural properties and biomass distribution. 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. Norm NIR is particularly suited for vegetation analysis, biomass assessment, canopy structure analysis. The general formula is NIR / (NIR + Red + Green), which requires Green and Red and NIR spectral bands.

Norm NIR 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 NIR / (NIR + Red + Blue), while BJ3N uses NIR / (NIR + Red + Blue). Select a sensor above to see its specific band mapping.

Norm NIR requires Green (490-570 nm), Red (640-760 nm), NIR (780-1400 nm). 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, Norm NIR provides complementary information that NDVI cannot capture on its own. The choice of index depends on your application, sensor availability, and atmospheric conditions.