Every spectral index, for every satellite,
in one reference.
Sensor-specific formulas, ready-to-use code, and an AI assistant to help you choose the right index for your remote sensing analysis.
What are you trying to measure?
Track plant health, yield prediction, irrigation needs
Map water bodies, floods, wetlands, coastal change
Detect active fires and assess post-fire damage
Identify clay, iron oxides, hydrothermal alteration
Built-up area extraction and impervious surfaces
Canopy assessment, deforestation, biomass
Popular spectral indices
Most commonly used vegetation index to assess plant health and density. Values range from -1 to 1, with higher…
Improved vegetation index that reduces atmospheric and soil background effects. More sensitive to vegetation c…
Used to detect water bodies and monitor water content in vegetation. Positive values typically indicate water …
The Modified Normalized Difference Water Index (MNDWI) was developed by Xu (2006) as an improvement over the o…
Vegetation index that minimizes soil brightness influences. The L factor is typically set to 0.5 for moderate …
Burn severity index for detecting and monitoring fire damage in vegetation. Higher values indicate healthy veg…
Normalized Difference Red-Edge (NDRE) is a vegetation index that uses the red-edge band instead of the red ban…
Highlights built-up areas and urban development. Higher values indicate more built-up surfaces.…
All 226 indices
Environmental
2Fire
3Geology
19Kernel
5Radar
9Soil
8Urban
9Vegetation
149Water
20What are spectral indices?
Spectral indices are mathematical combinations of satellite imagery bands that highlight specific surface features. NDVI measures vegetation health by comparing how plants reflect near-infrared light versus red light. NDWI detects water by comparing green to near-infrared. Each index targets a specific signal in the spectrum.
The right index depends on your application (what you're measuring) and your sensor (which bands are available). This database catalogs every formula and sensor-specific implementation you need — with code samples in Python and R.
NDVI = (NIR − Red) / (NIR + Red)