Vogelmann Red Edge Index 3

A simple ratio vegetation index using red edge wavelengths to assess vegetation health and chlorophyll content. The ratio of 715nm to 705nm provides information about the red edge position and slope. 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. VOG3 is particularly suited for chlorophyll content estimation, vegetation stress detection, leaf area index estimation. The general formula is re1_715 / re1_705, which requires re1_705 and re1_715 spectral bands.

VOG3 is supported by 3 satellite sensors in our database, including Dragonette-1, Dragonette-2/3, GeoEye-1. Each sensor uses different band designations — for example, Dragonette-1 uses the formula Band 17 / Band 16, while Dragonette-2/3 uses Band21 / Band20. Select a sensor above to see its specific band mapping.

VOG3 requires re1_705 (705), re1_715 (715). 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, VOG3 provides complementary information that NDVI cannot capture on its own. The choice of index depends on your application, sensor availability, and atmospheric conditions.