satellite (version 1.0.5)

calcAtmosCorr: Atmospheric correction of remote sensing data

Description

The function computes an atmospheric scattering correction and converts the sensors digital numbers to reflectances using

• absolute radiance correction

• DOS2: a dark object substraction model by Chavez (1996)

• DOS4: a dark object substratcion model by Moran et al. (1992)

Usage

# S4 method for Satellite
calcAtmosCorr(x, model = c("DOS2", "DOS4"), esun_method = "RadRef")
# S4 method for RasterStack
calcAtmosCorr(x, path_rad, esun, szen, model = c("DOS2", "DOS4"))
# S4 method for RasterLayer
calcAtmosCorr(x, path_rad, esun, szen, model = c("DOS2", "DOS4"))

Value

Satellite object with added atmospheric corrected layers

raster::RasterStack object with atmospheric corrected layers

raster::RasterLayer object with atmospheric corrected layer

Arguments

x

Satellite or Raster* object providing the radiance at the sensor.

model

Model to be used to correct for 1% scattering (DOS2, DOS4).

esun_method

If x is a Satellite object, name of the method to be used to compute esun using one of calcTOAIrradRadRef ("RadRef"), calcTOAIrradTable ("Table") or calcTOAIrradModel ("Model").

path_rad

Path radiance, e.g. returned from calcPathRadDOS.

esun

Actual (i.e. non-normalized) TOA solar irradiance, e.g. returned from calcTOAIrradRadRef, calcTOAIrradTable or calcTOAIrradModel.

szen

Sun zenith angle.

Details

If a Satellite object is passed to the function, and if the required pre-processing has not been performed already, the path radiance is computed based on a dark object's scaled count value using calcPathRadDOS which will also take care of the TOA solar irradiance by calling calcTOAIrradModel, calcTOAIrradRadRef or calcTOAIrradTable (depending on esun_method) if necessary. The bands' scaled counts are converted to radiance using convSC2Rad.

The radiometric correction is based on a dark object approach using either the DOS2 (Chavez 1996) or DOS4 (Moran et al. 1992) model.

The minimum reflectance values for the dark object are identified using the approximation of Chavez (1988, see calcPathRadDOS for details).

The estimated values of the solar irradiance required for the path radiance can be computed by one of calcTOAIrradTable which is used to get readily published values of ESun, calcTOAIrradRadRef which computes ESun based on the actual radiance and reflectance in the scene, or calcTOAIrradModel which computes ESun based on look-up tables for the sensor's relative spectral response and solar irradiation spectral data.

The atmospheric transmittance towards the sensor (Tv) is approximated by 1.0 (DOS2, Chavez 1996) or Rayleigh scattering (DOS4, Moran et al. 1992).

The atmospheric transmittance from the sun (Tz) is approximated by the cosine of the sun zenith angle (DOS2, Chavez 1996) or again using Rayleigh scattering (DOS4, Moran et al. 1992).

The downwelling diffuse irradiance is approximated by 0.0 (DOS2, Chavez 1996) or the hemispherical integral of the path radiance (DOS4, Moran et al. 1992).

Equations are taken from Song et al. (2001).

References

Chavez Jr PS (1988) An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment 24/3, tools:::Rd_expr_doi("10.1016/0034-4257(88)90019-3").

Chavez Jr PS (1996) Image-based atmospheric corrections revisited and improved. Photogrammetric Engineering and Remote Sensing 62/9, available online at https://www.researchgate.net/publication/236769129_Image-Based_Atmospheric_Corrections_-_Revisited_and_Improved

Goslee SC (2011) Analyzing Remote Sensing Data in R: The landsat Package. Journal of Statistical Software,43/4, 1-25, tools:::Rd_expr_doi("10.18637/jss.v043.i04").

Moran MS, Jackson RD, Slater PN, Teillet PM (1992) Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output.Remote Sensing of Environment 41/2-3, 169-184, tools:::Rd_expr_doi("10.1016/0034-4257(92)90076-V").

Song C, Woodcock CE, Seto KC, Lenney MP, Macomber SA (2001) Classification and Change Detection Using Landsat TM Data: When and How to Correct Atmospheric Effects? Remote Sensing of Environment 75/2, tools:::Rd_expr_doi("10.1016/S0034-4257(00)00169-3").

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)
sat_atmos <- calcAtmosCorr(sat, model = "DOS2", esun_method = "RadRef")

bcde <- "B002n"

sat <- calcTOAIrradRadRef(sat, normalize = FALSE)

path_rad <- calcPathRadDOS(x = min(getValues(getSatDataLayer(sat, bcde))),
                           bnbr = getSatLNBR(sat, bcde),
                           band_wls = 
                             data.frame(LMIN = 
                                          getSatLMIN(sat, 
                                                     getSatBCDESolar(sat)), 
                                        LMAX = 
                                          getSatLMAX(sat, 
                                                     getSatBCDESolar(sat))),
                           radm = getSatRADM(sat, getSatBCDESolar(sat)),
                           rada = getSatRADA(sat, getSatBCDESolar(sat)),
                           szen = getSatSZEN(sat, getSatBCDESolar(sat)),
                           esun = getSatESUN(sat, getSatBCDESolar(sat)),
                           model = "DOS2")

sensor_rad <- convSC2Rad(x = getSatDataLayer(sat, bcde), 
                         mult = getSatRADM(sat, bcde), 
                         add = getSatRADA(sat, bcde), getSatSZEN(sat, bcde))

ref_atmos <- calcAtmosCorr(x = sensor_rad,
                           path_rad = path_rad[names(path_rad) == bcde],
                           esun = getSatESUN(sat, bcde),
                           szen = getSatSZEN(sat, bcde), 
                           model = "DOS2")