No. 53, May/June 2003
Using geospatial technologies to develop
participatory tools for natural resources management
A vegetation index is a quantitative measure used to measure biomass or vegetative vigor, usually formed from combinations of several spectral bands (range of wavelength), whose values are added, divided, or multiplied in order to yield a single value that indicates the amount or vigor of vegetation. The simplest form of vegetation index is a ratio between near-infrared and red reflectance. For healthy living vegetation, this ratio will be high due to the inverse relationship between vegetation brightness in the red and infrared regions of the spectrum.
The NDVI, perhaps the most commonly used vegetation index, provides a standardized method of comparing vegetation greenness between satellite images.
The formula to calculate NDVI is:
NDVI = (near infrared band - red band) / (near infrared band + red band)
The underlying principle of the formula is that radiation from visible red light is considerably absorbed (or poorly reflected) by chlorophyll in green plants, while radiation from near infrared light is strongly reflected by the spongy mesophyll leaf structure (Tucker 1979; Jackson, Slater and Pinter 1983; Tucker et al. 1991).
Index values can range from -1.0 to 1.0, but vegetation values typically range between 0.1 and 0.7. Higher index values are associated with higher levels of healthy vegetation cover. However, clouds and snow will cause index values near zero, making it appear that the vegetation is less green.
Bands from the following satellite sensors can be used to calculate NDVI:
NDVI can be used as an indicator of relative biomass and greenness (Boone et al. 2000; Chen and Brutsaert 1998). If sufficient ground data are available, the NDVI can also be used to calculate and predict primary production, dominant species, and grazing impact and stocking rates (Ricotta, Qvena and Palma 1999; Oesterheld, Dibella and Kerdiles 1998; Paruelo et al. 1997; Peters et al. 1997; Diallo et al. 1991). It is also highly correlated with climatic variables, such as the El Niño Southern Oscillation (ENSO) (Li and Kafatos 2000; Boone et al. 2000) and precipitation (Schmidt and Karnieli 2000).
The above text was modified from the RangeView glossary (http://rangeview.arizona.edu/glossary/glossary.html), the EO Library (http://earthobservatory.nasa.gov/Library/MeasuringVegetation/) and the Goddard Space Flight Center (http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/LAND_BIO/ndvi.html.
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