Remote sensing spectral indices — indices • ForesToolboxRS

This function allows to obtain several remote sensing spectral indices in the optical domain.

indices(
  index,
  blue = NULL,
  green = NULL,
  red = NULL,
  nir = NULL,
  redEdge = NULL,
  swir = NULL,
  coefs = list(Lsavi = 0.5, G = 2.5, C1 = 6, C2 = 7.5, Levi = 1)
)

Arguments

index: Character, index name.
blue: Blue band, raster object.
green: Green band, raster object.
red: Red band, raster object.
nir: Near-infrared band, raster object.
redEdge: Red-edge band, raster object.
swir: Short-wave-infrared band, raster object.
coefs: List of coefficients to be used in some indices (Lsavi = 0.5, G = 2.5, C1 = 6, C2 = 7.5, Levi = 1).

Note

Currently implemented for satellites such as Landsat-4 TM, Landsat-5 TM, Landsat-7 ETM+, Landsat-8 OLI and Sentinel-2, and any other sensor who has the appropriate bands. It is possible to obtain spectral indices through digital number or top of atmosphere reflectance (toa), however in order to calculate indices such as SAVI or EVI, the the data must be in surface reflectance.

References

Rouse, J.W., Hass, R.H., Schell, J.A., and Deering, D.W. (1973). Monitoring vegetation systems in the Great Plains with ERTS. Proceedings of the Third ERTS Symposium, 1.

Huete, A.R. (1988). A Soil-Adjusted Vegetation Index (SAVI). Remote Sensing of Environment, 25,295-309.

Huete, A.R., Justice, C., Liu, H. (1994). Development of vegetation and soil indices for MODIS-EOS. Remote Sensing of Environment, 49, 224-234.

Gao, B.C. (1996). NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257-266.

Key, C.H.; Benson, N.C. Landscape Assessment: Ground Measure of Severity, the Composite Burn Index, and Remote Sensing of Severity, the Normalized Burn Index. In FIREMON: Fire Effects Monitoring and Inventory System; Lutes, D., Keane, R., Caratti, J., Key, C.H., Benson, N.C., Sutherland, S., Gangi, L., Eds.; Rocky Mountains Research Station, USDA Forest Service: Fort Collins, CO, USA, 2005.

Camps-Valls, G., et al. (2021). A unified vegetation index for quantifying the terrestrial biosphere. Science Advances, 7(9).

Examples

library(ForesToolboxRS)
library(raster)

# Load an example dataset
data(img_l8)

# Obtain bands
nirBand <- img_l8[[4]]
redBand <- img_l8[[3]]

# Obtain NDVI
ndvi <- indices(index = "NDVI", nir = nirBand, red = redBand)
plot(ndvi)