RGB indices

Source: R/rs_textures.R, R/rs_indices.R

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.

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.

rgb_indices(
  red,
  green,
  blue,
  rgbi = c("VVI", "VARI", "NDTI", "RI", "SCI", "BI", "SI", "HI", "TGI", "GLI", "NGRDI",
    "GRVI", "GLAI", "HUE", "CI", "SAT", "SHP")
)

rgb_indices(
  red,
  green,
  blue,
  rgbi = c("VVI", "VARI", "NDTI", "RI", "SCI", "BI", "SI", "HI", "TGI", "GLI", "NGRDI",
    "GRVI", "GLAI", "HUE", "CI", "SAT", "SHP")
)

Arguments

red

a single Raster or RasterBrick band.

green

a single Raster or RasterBrick band.

blue

a single Raster or RasterBrick band.

rgbi

the implemented RGB indices currently

  • BI sqrt((R**2+G**2+B*2)/3 Brightness Index

  • SCI (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 MATHIEU et al. (1998)

  • NDTI (R-G)/(R+G) Normalized difference turbidity index Water Lacaux et al. (2007)

  • 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))

  • GLAI (25 * (green - red) / (green + red - blue ) + 1.25 )

  • GRVI (green-red)/(green+red) Green-Red Vegetation Index

  • CI (red - blue) / red Coloration Index

  • HUE atan(2 * (red - green - blue) / 30.5 * (green - blue)) Overall Hue Index

  • SAT (max(red,green,blue) - min(red,green,blue)) / max(red,green,blue) Overall Saturation Index

  • SHP 2 * (red - green - blue) / (green - blue) Shape index

Value

raster* object

raster* object

References

Planetary Habitability Laboratory (2015): Visible Vegetation Index (VVI). Available online via 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.(NDTI) )
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.(RI)
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.(BI, SI, HI)
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.
GRVI Green-Red Vegetation Index Remote Sensing 2010, 2, 2369-2387; doi:10.3390/rs2102369
CI IDB Coloration
HUE Index IDB Hue
Saturation Index IDB Saturation
Shape Index IDB Shape

Planetary Habitability Laboratory (2015): Visible Vegetation Index (VVI). Available online via 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.(NDTI) )
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.(RI)
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.(BI, SI, HI)
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.
GRVI Green-Red Vegetation Index Remote Sensing 2010, 2, 2369-2387; doi:10.3390/rs2102369
CI IDB Coloration
HUE Index IDB Hue
Saturation Index IDB Saturation
Shape Index IDB Shape

See also

For a comprehensive overview of remote sensing indices have a look at: A database for remote sensing indices
Approximatly wavelength ranges for overlapping digital camera bands are:

  • red 580-670 nm,

  • green 480-610 nm,

  • blue 400-520 nm

Hunt et al., 2005. However check the manual of your camera.

For a comprehensive overview of remote sensing indices have a look at: A database for remote sensing indices
Approximately wavelength ranges for overlapping digital camera bands are:

  • red 580-670 nm,

  • green 480-610 nm,

  • blue 400-520 nm

Hunt et al., 2005. However check the manual of your camera.

Examples

## ## ##
##- setup environment
require(uavRst)
data(rgb)

##- visualize the image
raster::plotRGB(rgb)


##- calculate the indices
rgbI<-rgb_indices(red   = rgb[[1]],
                 green = rgb[[2]],
                 blue  = rgb[[3]],
                 rgbi = c("NDTI","VARI","TGI"))
#> :::: Normalized Difference Turbidity Index  NDTI 
#> 
#> :::: Visible Atmospherically Resistant Index  VARI 
#> 
#> :::: Triangular Greenness Index  TGI 
#> 

##- visualize the indices
raster::plot(rgbI)

##+
## ## ##
##- setup environment
data(rgb)

##- visualize the image
raster::plotRGB(rgb)


##- calculate the indices
rgbI<-rgb_indices(red   = rgb[[1]],
                 green = rgb[[2]],
                 blue  = rgb[[3]],
                 rgbi = c("NDTI","VARI","TGI"))
#> :::: Normalized Difference Turbidity Index  NDTI 
#> 
#> :::: Visible Atmospherically Resistant Index  VARI 
#> 
#> :::: Triangular Greenness Index  TGI 
#> 

##- visualize the indices
raster::plot(rgbI)

##+