The Sentinel program is composed of two satellites (Sentinel 2A, 2B) and was developed to monitor land surface changes in vegetation, the environment, and land cover. Sentinel-2 spatial, spectral, and temporal resolutions allow for imagery to be processed at sufficient spatial and temporal detail that is optimal for field scale land surface monitoring, management, and research. Sentinel-2 datasets are available for Sentinel 2A, 2B, and composite of 2A/2B using top of atmosphere or at surface reflectance data.
Soil Adjusted Vegetation Index (SAVI) provides information on vegetation growth and productivity while correcting for influences of soil reflectance. Effects due to climate, weather, fire, water, and vegetation and crop management can be assessed through developing and visualizing maps, time series, and anomalies of SAVI.
SAVI is calculated as the normalized difference between the red and near infrared (NIR) bands following the equation (NIR – Red) / (NIR + Red + L), where L is a soil brightness correction factor which is typically 0.5 (Huete 1988; Ray 2020). Soil reflectance adjustments have shown to be useful for applications in sparse vegetative cover.
Red: 0.6645 μm (S2A) / 0.665 μm (S2B)
Near Infrared (NIR): 0.8351 μm (S2A) / 0.833 μm (S2B)
Period of Record
Huete, A. R. (1988) A Soil-Adjusted Vegetation Index (SAVI). Remote Sensing of Environment, vol. 25:295-309.
Ray, T.W. (Accessed July 27th, 2020). A FAQ on vegetation in remote sensing. http://www.remote-sensing.info/wp-content/uploads/2012/07/A_FAQ_on_Vegetation_in_Remote_Sensing.pdf
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