rgbIndices: RGB indices

In environmentalinformatics-marburg/satelliteTools: What the package does (short line)

Description

This function calculates various spectral indices from a RGB. It returns at least red green and blue as splitted channels in a stack. Additionally you can choose RGB indices. Raster* object.

Arguments

rgb	a RasterStack or RasterBrick object. 3 bands are mandatory (for RGB indices they should be: "red", "green" and "blue").
rgbi	the implemented RGB indices currently seealso

Value

A RasterStack object.

Author(s)

Chris Reudenbach

References

Planetary Habitability Laboratory (2015): Visible Vegetation Index (VVI). Available online via http://phl.upr.edu/projects/visible-vegetation-index-vvi.

Lacaux, J. P., Tourre, Y. M., Vignolles, C., Ndione, J. A., and Lafaye, M.: Classification of ponds from high-spatial resolution remote sensing: Application to Rift Valley Fever epidemics in Senegal, Remote Sens. Environ., 106, 66-74, 2007.

Gitelson, A., et al.: Vegetation and Soil Lines in Visible Spectral Space: A Concept and Technique for Remote Estimation of Vegetation Fraction. International Journal of Remote Sensing 23 (2002): 2537-2562. (VARI)

MADEIRA, J., BEDIDI, A., CERVELLE, B., POUGET, M. and FLAY, N., 1997, Visible spectrometric indices of hematite (Hm) and goethite (Gt) content in lateritic soils: 5490 N. Levin et al. the application of a Thematic Mapper (TM) image for soil-mapping in Brasilia, Brazil. International Journal of Remote Sensing, 18, pp. 2835-2852.

MATHIEU, R., POUGET, M., CERVELLE, B. and ESCADAFAL, R., 1998, Relationships between satellite-based radiometric indices simulated using laboratory reflectance data and typic soil colour of an arid environment. Remote Sensing of Environment, 66, pp. 17-28.

Louhaichi, M., Borman, M.M., Johnson, D.E., 2001. Spatially located platform and aerial photography for documentation of grazing impacts on wheat. Geocarto International 16, 65-70.

Tucker, C.J., 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment 8, 127-150.

See Also

A RasterLayer with the index calculates as:
BI sqrt((R**2+G**2+B*2)/3 Brightness Index
CI (R-G)/(R+G) Soil Colour Index
GLI (2*g - r - b)/(2*g + r + b) Green leaf index Vis Louhaichi et al. (2001)
HI (2*R-G-B)/(G-B) Primary colours Hue Index
NDTI (R-G)/(R+G) Normalized difference turbidity index Water
NGRDI (G-R)/(G+R) Normalized green red difference index (sometimes GRVI) Tucker (1979) RI R**2/(B*G**3) Redness Index
SI (R-B)/(R+B) Spectral Slope Saturation Index
TGI -0.5[190(R670-R550)-120(R670 - R480)] The triangular greenness index (TGI) estimates chlorophyll concentration in leaves and canopies
VARI (green-red)/(green+red-blue). A Visible Atmospherically Resistant Index (VARI)
VVI (1-(r-30)/(r+30))*(1-(g-50)/(g+50))*(1-(b-1)/(b+1))

For a comprehensive overview of remote sensing indices have a look at: http://www.indexdatabase.de/db/i.php(A database for remote sensing indices)
Wavelength ranges for overlapping digital camera bands are: red 580-670 nm, green 480-610 nm, and blue 400-520 nm (Hunt et al., 2005) http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=2161&context=usdaarsfacpub

Examples

\notrun{
library(raster)
url <- "https://upload.wikimedia.org/wikipedia/commons/2/28/RGB_illumination.jpg"
dFile <- download.file(url, "Image.jpg")
img <- stack("Image.jpg") 
plotRGB(img)
rgbi <- rgbI(img)
plot(rgbI, col = gray(255:0/255))
}

environmentalinformatics-marburg/satelliteTools documentation built on May 16, 2019, 8:16 a.m.