Soil-Adjusted Vegetation Index

Other Names:



In areas where vegetative cover is low (i.e., < 40%) and the soil surface is exposed, the reflectance of light in the red and near-infrared spectra can influence vegetation index values. This is especially problematic when comparisons are being made across different soil types that may reflect different amounts of light in the red and near infrared wavelengths (i.e., soils with different brightness values). The soil-adjusted vegetation index was developed as a modification of the to correct for the influence of soil brightness when vegetative cover is low.

The SAVI is structured similar to the NDVI but with the addition of a “soil brightness correction factor,”
where NIR is the reflectance value of the near infrared band, RED is reflectance of the red band, and L is the soil brightness correction factor. The value of L varies by the amount or cover of green vegetation: in very high vegetation regions, L=0; and in areas with no green vegetation, L=1. Generally, an L=0.5 works well in most situations and is the default value used. When L=0, then SAVI = NDVI.

Similar Methods



The output of SAVI is a new image layer with values ranging from -1 to 1. The lower the value, the lower the amount/cover of green vegetation.

Successful Rangeland Uses

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Application References

  • Richardson, A.J. and J.H. Everitt. 1992. Using spectral vegetation indices to estimate rangeland productivity. Geocarto International 7(1):63-69. – Compared several different vegetation indices (including SAVI) to see which ones performed best for predicting biomass in rangelands. SAVI performed about as well as other vegetation indices.
  • Lyon, J.G., Yuan, D., Lunetta, R.S., and C.D. Elvidge. 1998. A change detection experiment using vegetation indices. Photogrammetric Engineering and Remote Sensing 64(2):143-150. // – compared different vegetation indices for use in change detection applications. SAVI and NDVI performed best of the seven indices considered.//
  • Senseman, G.M., Bagley, C.F., and S.A. Tweddale. 1996. Correlation of rangeland cover measures to satellite-imagery-derived vegetation indices. Geocarto International 11(3):29-38.

Technical References


Adjusting for the influence of soils comes at a cost to the sensitivity of the vegetation index. Compared to NDVI, SAVI is generally less sensitive to changes in vegetation (amount and cover of green vegetation), and more sensitive to atmospheric differences.

Data Inputs

Calculating the SAVI requires a red and a near infrared band, and specification of the soil brightness correction factor, L. As such, SAVI can be performed on almost any type of imagery that has a red and near infrared band (e.g., Landsat, Ikonos, Quickbird, MODIS).

Software/Hardware Requirements

SAVI is relatively easy to calculate and can be done with any remote sensing package (e.g., ERDAS Imaging, ENVI, Idrisi) or with a GIS program that can handle raster processing (e.g., ArcGIS with Spatial Analyst extension, GRASS).

Sample Graphic

NDVI and SAVI calculated from a Landsat TM5 image of southwestern Owyhee County, Idaho. This image shows a section of the South-Fork Owyhee River canyon. Notice how the NDVI image has high index values in the rocky river canyon, suggesting much more vegetative cover than is actually there. The SAVI for the canyon gives a much better approximation of the amount and cover of vegetation in the canyon as well as in the upland.

Additional Information

Existing datasets

  • None known

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