calcAtmosCorr | R Documentation |
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)
## S4 method for signature 'Satellite'
calcAtmosCorr(x, model = c("DOS2", "DOS4"), esun_method = "RadRef")
## S4 method for signature 'RasterStack'
calcAtmosCorr(x, path_rad, esun, szen, model = c("DOS2", "DOS4"))
## S4 method for signature 'RasterLayer'
calcAtmosCorr(x, path_rad, esun, szen, model = c("DOS2", "DOS4"))
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 |
path_rad |
Path radiance, e.g. returned from
|
esun |
Actual (i.e. non-normalized) TOA solar irradiance, e.g. returned
from |
szen |
Sun zenith angle. |
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).
Satellite object with added atmospheric corrected layers
raster::RasterStack object with atmospheric corrected layers
raster::RasterLayer object with atmospheric corrected layer
Chavez Jr PS (1988) An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment 24/3, \Sexpr[results=rd]{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, \Sexpr[results=rd]{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, \Sexpr[results=rd]{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, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/S0034-4257(00)00169-3")}.
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")
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