GVI — Tasselled Cap - vegetation | Spectral Index Calculator

The vegetation component of the Tasselled Cap transformation, which measures the amount of green vegetation present. High values indicate dense, healthy vegetation.

-0.2848 * Blue - 0.2435 * Green - 0.5436 * Red + 0.7243 * NIR + 0.0840 * SWIR1 - 0.1800 * SWIR2

Bands: blue, green, red, nir, swir1, swir2
Range: -1 to 1
Typical: Most vegetation 0.2 to 0.8

Used in crop monitoring, forest monitoring, and mineral exploration.

When to use

Time-series monitoring of crop health, growth stages, and stress detection
Land cover classification and vegetation type discrimination
Biomass estimation and net primary productivity studies
Drought impact assessment over agricultural and forest areas
Phenology tracking — green-up, peak season, and senescence
Vegetation density assessment
Forest monitoring

Limitations

Saturates in dense canopies (LAI > 3) — values plateau and lose discrimination ability
Sensitive to atmospheric scattering, especially blue-band haze
Soil background contaminates measurements in sparsely vegetated areas
Sun-sensor geometry (BRDF effects) introduces variability across acquisitions
Cloud cover and shadows produce invalid pixels that need masking
Requires sensors with SWIR bands — not available on all platforms

What the values mean

-1 Water / Snow

-0.1 Bare ground / Built-up

0.1 Sparse / Stressed

0.3 Moderate vegetation

0.5 Healthy vegetation

0.7 Dense canopy

Surface type	Typical GVI
Open water, snow	-0.3 to -0.1
Bare soil, urban	-0.1 to 0.2
Sparse or stressed crops	0.2 to 0.4
Healthy crops, grassland	0.4 to 0.7
Dense forest, peak season	0.7 to 0.9

General Formula

blue 450-520

green 520-600

red 630-690

nir 760-900

swir1 1550-1750

swir2 2080-2350

Sensor-Specific Formulas

Most-used sensors — click to show code below

Sensor	Provider	Formula	Band Mapping
Landsat 8/9	USGS/NASA	`-0.2848 * B1 - 0.2435 * B3 - 0.5436 * B4 + 0.7243 * B5 + 0.0840 * B6 - 0.1800 * B7`	blue→B1, green→B3, red→B4, nir→B5, swir1→B6, swir2→B7
Sentinel-2	ESA	`-0.2848 * B1 - 0.2435 * B3 - 0.5436 * B4 + 0.7243 * B8 + 0.0840 * B11 - 0.1800 * B12`	blue→B1, green→B3, red→B4, nir→B8, swir1→B11, swir2→B12
WorldView 3	MAXAR	`-0.2848 * Blue - 0.2435 * Green - 0.5436 * Red + 0.7243 * NIR1 + 0.0840 * SWIR2 - 0.1800 * SWIR6`	blue→Blue, green→Green, red→Red, nir→NIR1, swir1→SWIR2, swir2→SWIR6

Spectral Band Visualization — Landsat 8/9

Code Examples

Adapted for Landsat 8/9 bands —

gvi_tc_landsat-8-9.py

Frequently Asked Questions

What is the GVI (Tasselled Cap - vegetation) and when should I use it?

The vegetation component of the Tasselled Cap transformation, which measures the amount of green vegetation present. High values indicate dense, healthy vegetation. 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. GVI is particularly suited for vegetation density assessment, forest monitoring, agricultural crop analysis. The general formula is -0.2848 * Blue - 0.2435 * Green - 0.5436 * Red + 0.7243 * NIR + 0.0840 * SWIR1 - 0.1800 * SWIR2, which requires blue and green and red and nir and swir1 and swir2 spectral bands.

Which satellite sensors can I use to calculate GVI?

GVI is supported by 3 satellite sensors in our database, including Landsat 8/9, Sentinel-2, WorldView 3. Each sensor uses different band designations — for example, Landsat 8/9 uses the formula -0.2848 * B1 - 0.2435 * B3 - 0.5436 * B4 + 0.7243 * B5 + 0.0840 * B6 - 0.1800 * B7, while Sentinel-2 uses -0.2848 * B1 - 0.2435 * B3 - 0.5436 * B4 + 0.7243 * B8 + 0.0840 * B11 - 0.1800 * B12. Select a sensor above to see its specific band mapping.

What spectral bands does GVI require and why?

GVI requires blue (450-520), green (520-600), red (630-690), nir (760-900), swir1 (1550-1750), swir2 (2080-2350). 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.

How do I calculate GVI in Python or R?

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.

How does GVI compare to NDVI and other vegetation indices?

While NDVI is the most common vegetation index, GVI incorporates additional spectral bands to reduce atmospheric interference and soil background effects. The choice of index depends on your application, sensor availability, and atmospheric conditions.

GVI vs other vegetation indices

Index	Name	How it differs
ARI	Anthocyanin Reflectance Index	Alternative vegetation index — different band combination
mARI	Modified Anthocyanin Reflectance Index	Refined formulation for specific conditions
ARVI	Atmospherically Resistant Vegetation Index	Atmospherically corrected version
ARVI2	Atmospherically Resistant Vegetation Index 2	Atmospherically corrected version

Related Vegetation Indices

References

Bannari et al. (1995). A review of vegetation indices.

Crist & Cicone (1984). A Physically-Based Transformation of Thematic Mapper Data---The TM Tasseled Cap.

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