Package 'satellite'

Title: Handling and Manipulating Remote Sensing Data
Description: Herein, we provide a broad variety of functions which are useful for handling, manipulating, and visualizing satellite-based remote sensing data. These operations range from mere data import and layer handling (eg subsetting), over Raster* typical data wrangling (eg crop, extend), to more sophisticated (pre-)processing tasks typically applied to satellite imagery (eg atmospheric and topographic correction). This functionality is complemented by a full access to the satellite layers' metadata at any stage and the documentation of performed actions in a separate log file. Currently available sensors include Landsat 4-5 (TM), 7 (ETM+), and 8 (OLI/TIRS Combined), and additional compatibility is ensured for the Landsat Global Land Survey data set.
Authors: Thomas Nauss, Hanna Meyer, Tim Appelhans, Florian Detsch
Maintainer: Florian Detsch <[email protected]>
License: MIT + file LICENSE
Version: 1.0.5
Built: 2024-11-07 03:43:11 UTC
Source: https://github.com/environmentalinformatics-marburg/satellite

Help Index


Smorgasboard for remote sensing functions.

Description

Smorgasbord for remote sensing functions

Details

The package provides a variety of functions which are useful for handling, manipulating and visualizing remote sensing data.

Author(s)

Thomas Nauss, Hanna Meyer, Florian Detsch, Tim Appelhans

Maintainer: Florian Detsch [email protected]

References

Some functions are taken and/or adopted from Sarah C. Goslee (2011). Analyzing Remote Sensing Data in R: The landsat Package. Journal of Statistical Software, 43(4), 1-25, doi:10.18637/jss.v043.i04.

See Also

Useful links:


Align raster geometry between two data sets

Description

Align raster data by bringing it in the same geometry and extent. If the data set is not in the same projection as the template, the alignment will be computed by reprojection. If the data has already the same projection, the data set will be cropped and aggregated prior to resampling in order to reduce computation time.

Usage

## S4 method for signature 'Satellite'
alignGeometry(x, template, band_codes, type, method = c("bilinear", "ngb"))

## S4 method for signature 'RasterStack'
alignGeometry(x, template, method = c("bilinear", "ngb"))

## S4 method for signature 'RasterLayer'
alignGeometry(x, template, method = c("bilinear", "ngb"))

Arguments

x

Satellite or Raster* object to be resampled.

template

Raster* or spatial data set from which geometry can be extracted.

band_codes

Band ID(s) to be resampled. If not supplied and type is not given, too, all bands will be considered for resampling.

type

Type of bands (e.g. VIS, NIR) which should be considered. If not supplied, all types will be processed depending and bands to be processed can be defined by band_codes.

method

Method for resampling; "bilinear" for bilinear interpolation (default) or "ngb" for nearest neighbor interpolation. See e.g. resample, projectRaster.

Value

Satellite object with aligned geometries.

raster::RasterStack object with aligned layers

raster::RasterLayer object with aligned layer

Examples

path <- system.file("testdata/LC8", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC8*.TIF"), full.names = TRUE)
sat <- satellite(files)

alignGeometry(sat, template = getSatDataLayer(sat, "B008n"), 
               band_codes = "B001n")

Convert selected layers of a Satellite object to a RasterBrick

Description

Convert selected layers of a Satellite object to a RasterBrick

Usage

## S4 method for signature 'Satellite'
brick(x, layer = names(x), ...)

Arguments

x

an object of class 'Satellite'

layer

character vector (bcde codes) or integer vector (index) of the layers to be stacked

...

additional arguments passed on to brick

Examples

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

brck <- brick(sat, c("B001n", "B002n", "B003n"))
brck

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 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"))

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).

Value

Satellite object with added atmospheric corrected layers

raster::RasterStack object with atmospheric corrected layers

raster::RasterLayer object with atmospheric corrected layer

References

Chavez Jr PS (1988) An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment 24/3, 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, 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, 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, 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")

Compile dark object DN for given sensor band

Description

The function estimates the DN value of a "dark object" which is used for atmospheric correction using the DOS2 and DOS4 model. Therefore, the frequency distribution of the smallest 1% of the data values is analyzed and the value for which the first derivate has the absolute maximum is taken as the DN for a dark object.

Usage

## S4 method for signature 'Satellite'
calcDODN(x, bcde)

## S4 method for signature 'RasterLayer'
calcDODN(x)

Arguments

x

Satellite object or RasterLayer with sensor band data, e.g. returned by getSatDataLayer.

bcde

If 'x' is a Satellite object, a band code as character.

Details

The DN for a dark object is extracted from a histogram similar to Chavez (1988).

Value

Numeric value of the DN for the dark object.

References

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

See Also

The DN is used by calcPathRadDOS for computing the path radiance based on the dark object method.

Examples

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

calcDODN(sat, bcde = "B002n")
calcDODN(getSatDataLayer(sat, bcde = "B002n"))

Compute earth-sun distance based on day of the year

Description

The earth-sun distance for a particular day of the year is computed based on one of several empirical formulas.

Usage

calcEarthSunDist(date, formula = c("Spencer", "Mather", "ESA", "Duffie"))

Arguments

date

Date of the sensor overpass; either a character string in a native date format (e.g. "YYYY-MM-DD", see as.Date) or a POSIX* object (see as.POSIXct).

formula

Formula to be applied, specified through the name of the author, i.e. one of "Spencer", "Mather", "ESA" or "Duffie" (see 'Details').

Details

Computation of earth-sun distance using formulas provided by Spencer (1971), Mather (2005) or ESA. If formula = "Duffie", the inverse squared relative earth–sun distance is returned as proposed by Duffie and Beckman (1980).

Value

Numeric earth-sun distance (in AU) or, if formula = "Duffie", the relative squared earth–sun distance on the given day.

References

The formulas are taken from the following sources:

See also: Bird R, Riordan C (1984) Simple solar spectral model for direct and diffuse irradiance on horizontal and tilted planes at the Earth's surface for cloudless atmospheres. Task No. 3434.10, Solar Energy Research Institute: Golden, Colorado, http://www.nrel.gov/docs/legosti/old/2436.pdf.

Examples

calcEarthSunDist(date = "2015-01-01", formula = "Spencer") # absolute
calcEarthSunDist(date = "2015-01-01", formula = "Duffie")  # relative

Compute path radiance based on the dark object method

Description

Compute an estimated path radiance for all sensor bands, which can then be used to roughly correct the radiance values for atmospheric scattering. Path radiance estimation is based on a dark object method.

Usage

## S4 method for signature 'Satellite'
calcPathRadDOS(x, model = c("DOS2", "DOS4"), esun_method = "RadRef")

## S4 method for signature 'numeric'
calcPathRadDOS(
  x,
  bnbr,
  band_wls,
  radm,
  rada,
  szen,
  esun,
  model = c("DOS2", "DOS4"),
  scat_coef = c(-4, -2, -1, -0.7, -0.5),
  dos_adjust = 0.01
)

Arguments

x

A Satellite object or the value (scaled count) of a dark object in bnbr (e.g. minimum raw count of selected raster bnbr). If x is a Satellite object, the value is computed using calcDODN.

model

Model to be used to correct for 1% scattering (DOS2, DOS4; must be the same as used by calcAtmosCorr).

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")

bnbr

Band number for which DNmin is valid.

band_wls

Band wavelengths to be corrected; data.frame with min (max) in first (second) column, see details.

radm

Multiplicative coefficient for radiance transformation (i.e. slope).

rada

Additive coefficient for radiance transformation (i.e. offset).

szen

Sun zenith angle.

esun

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

scat_coef

Scattering coefficient; defaults to -4.0.

dos_adjust

Assumed reflection for dark object adjustment; defaults to 0.01.

Details

If x is a Satellite object, the minimum raw count value (x) is computed using calcDODN. If the TOA solar irradiance is not part of the Satellite object's metadata, it is computed using calcTOAIrradRadRef, calcTOAIrradTable or calcTOAIrradModel.

The dark object subtraction approach is based on an approximation of the atmospheric path radiance (i.e. upwelling radiation which is scattered into the sensors field of view, aka haze) using the reflectance of a dark object (i.e. reflectance ~1%).

Chavez (1988) proposed a method which uses the dark object reflectance in one band to predict the corresponding path radiances in all other band_wls. This is done using a relative radiance model which depends on the wavelength and overall atmospheric optical thickness (which is estimated based on the dark object's DN value). This has the advantage that the path radiance is actually correlated across different sensor band_wls and not computed individually for each band using independent dark objects. He proposed a relative radiance model which follows a wavelength dependent scattering that ranges from a power of -4 over -2, -1, -0.7 to -0.5 for very clear over clear, moderate, hazy to very hazy conditions. The relative factors are computed individually for each 1/1000 wavelength within each band range and subsequently averaged over the band as proposed by Goslee (2011).

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 for the path radiance are taken from Song et al. (2001).

For some sensors, the band wavelengths are already included. See lutInfo()[grepl("_BANDS", names(lutInfo()$META))] if your sensor is included. To retrieve a sensor, use lutInfo()$<Sensor ID>_BANDS.

Value

Satellite object with path radiance for each band in the metadata (W m-2 micrometer-1)

Vector object with path radiance values for each band (W m-2 micrometer-1)

References

Chavez Jr PS (1988) An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment 24/3, 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, doi:10.18637/jss.v043.i04.

Moran MS, Jackson RD, Slater PN, Teillet PM (1992) Evlauation of simplified procedures for rretrieval of land surface reflectane factors from satellite sensor output.Remote Sensing of Environment 41/2-3, 169-184, 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, doi:10.1016/S0034-4257(00)00169-3.

If you refer to Sawyer and Stephen 2014, please note that eq. 5 is wrong.

See Also

This function is used by calcAtmosCorr to compute the path radiance.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)
sat <- calcTOAIrradModel(sat)

bds <- "B002n"
val <- calcPathRadDOS(x = min(getValues(getSatDataLayer(sat, bds))),
                      bnbr = getSatLNBR(sat, bds),
                      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",
                      scat_coef = -4)
val

Compute top of atmosphere solar irradiance for sensor bands using LUTs

Description

Compute mean extraterrestrial solar irradiance (ESun) using tabulated mean solar spectral data and the band specific relative spectral response (rsr) functions.

Usage

## S4 method for signature 'Satellite'
calcTOAIrradModel(x, model = "MNewKur", normalize = TRUE, esd)

## S4 method for signature 'data.frame'
calcTOAIrradModel(x, model = "MNewKur", normalize = TRUE, esd)

Arguments

x

A Satellite object or the relative spectral response function for the respective band as data.frame (see details for structure).

model

Tabulated solar radiation model to be used (one of MCebKur_MChKur, MNewKur, MthKur, MoldKur, MODWherli_WMO, NN, see reference on tabulated solar irradiance below).

normalize

Logical; if TRUE, ESun is normalized to mean earth-sun distance.

esd

Earth-sun distance (AU, can be estimated using calcEarthSunDist). If x is a Satellite object and esd is not supplied and necessary for normalization, it is tried to take it from the metadata, otherwise it is estimated by the day of the year using calcEarthSunDist.

Details

Computation of ESun is taken from Updike and Comp (2011).

Tabulated values for mean earth-sun distance are taken from the data sources mentioned in the references.

If results should not be normalized to a mean earth-sun distance, the actual earth-sun distance is approximated by the day of the year using calcEarthSunDist.

Relative spectral response values have to be supplied as a data.frame which has at least the following three columns: (i) a column "Band" for the sensor band number (i.e. 1, 2, etc.), (ii) a column "WAVELENGTH" for the WAVELENGTH data in full nm steps, and (iii) a column "RSR" for the response information [0...1].

Value

If x is a Satellite object, a Satellite object with ESun information added to the metadata; if x is a data.frame, a vector containing ESun for the respective band(s).

References

Updike T, Comp C (2011) Radiometric use of WorldView-2 imagery. Technical Note, available online at http://www.pancroma.com/downloads/Radiometric_Use_of_WorldView-2_Imagery.pdf.

Tabulated relative spectral response functions (nm-1) are taken from the spectral viewer of the USGS Landsat FAQ.

Tabulated solar irradiance (W m-2 nm-1) is taken from the National Renewable Energy Laboratory.

See Also

calcTOAIrradTable for tabulated solar irradiance values from the literature or calcTOAIrradRadRef for the computation of the solar irradiance based on maximum radiation and reflection values of the dataset.

See calcEarthSunDist for calculating the earth-sun distance based on the day of the year which is called by this function if ESun should be corrected for actual earth-sun distance.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)
sat <- calcTOAIrradModel(sat)
getSatESUN(sat)

lut <- lutInfo()
calcTOAIrradModel(lut$L8_RSR, model = "MNewKur", normalize = FALSE, 
  esd = calcEarthSunDist("2015-01-01"))

Compute top of atmosphere solar irradiance using radiation vs. reflection

Description

Compute extraterrestrial solar irradiance (ESun) using the actual maximum radiation and reflection values within each band.

Usage

## S4 method for signature 'Satellite'
calcTOAIrradRadRef(x, normalize = TRUE, esd)

## S4 method for signature 'numeric'
calcTOAIrradRadRef(x, ref_max, normalize = TRUE, esd)

Arguments

x

A Satellite object or the maximum radiance of satellite band(s) as numeric object.

normalize

Logical; if TRUE, ESun is normalized to mean earth-sun distance.

esd

Earth-sun distance (AU, can be estimated using calcEarthSunDist). If x is a Satellite object and esd is not supplied and necessary for normalization, it is tried to take it from the metadata, otherwise it is estimated by the day of the year using calcEarthSunDist.

ref_max

Maximum reflextance of satellite band(s).

Details

The actual solar irradiance is computed using the following formula taken from the GRASS GIS i.landsat.toar module

ESun=(pid2)RADIANCEMAXIMUM/REFLECTANCEMAXIMUMESun = (pi d^2) RADIANCE_MAXIMUM / REFLECTANCE_MAXIMUM

where d is the earth-sun distance (in AU) and RADIANCE_MAXIMUM and REFLECTANCE_MAXIMUM are the maximum radiance and reflection values of the respective band. All these parameters are taken from the scene's metadata file if a Satellite object is passed to the function.

By default, the resulting actual ESun will be normalized to a mean earth-sun distance to be compatible with other default results from calcTOAIrradTable or calcTOAIrradModel.

Value

If x is a Satellite object, a Satellite object with ESun information added to the metadata; if x is numeric, a vector containing ESun for the respective band(s).

See Also

calcTOAIrradTable for tabulated solar irradiance values from the literature or calcTOAIrradModel for the computation of the solar irradiance based on look-up tables for the sensor's relative spectral response and solar irradiation spectral data.

See calcEarthSunDist for calculating the earth-sun distance based on the day of the year which is called by this function if ESun should be corrected for actual earth-sun distance.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)  
sat <- calcTOAIrradModel(sat)
getSatESUN(sat)

calcTOAIrradRadRef(x = getSatRadMax(sat, getSatBCDESolar(sat)), 
                   ref_max = getSatRefMax(sat, getSatBCDESolar(sat)), 
                   normalize = FALSE, 
                   esd = calcEarthSunDist("2015-01-01"))

Get top of atmosphere solar irradiance using readily tabulated values

Description

Get mean extraterrestrial solar irradiance (ESun) using published values.

Usage

## S4 method for signature 'Satellite'
calcTOAIrradTable(x, normalize = TRUE, esd)

## S4 method for signature 'factor'
calcTOAIrradTable(x, normalize = TRUE, esd)

## S4 method for signature 'character'
calcTOAIrradTable(x, normalize = TRUE, esd)

Arguments

x

A Satellite object or sensor id ("LT4, LT5, LE7") as character.

normalize

Logical; if TRUE, ESun is normalized to mean earth-sun distance.

esd

Earth-sun distance (AU, can be estimated using calcEarthSunDist). If x is a Satellite object and esd is not supplied and necessary for normalization, it is tried to take it from the metadata, otherwise it is estimated by the day of the year using calcEarthSunDist.

Details

Currently implemented sensors are Landsat 4, 5 and 7.

If results should not be normalized to a mean earth-sun distance, the actual earth-sun distance is approximated by the day of the year using calcEarthSunDist.

Please note that ESun values are not required for converting Landsat 8 data to reflectance as the corresponding metadata files provide coefficients necessary to convert digital numbers to radiance and reflectance (taken from https://www.gisagmaps.org/landsat-8-atco-guide/.

Value

Satellite object with ESun information added to the metadata

Vector object containing ESun for the respective band(s)

Vector object containing ESun for the respective band(s)

References

Tabulated values of the solar irradiance for all Landsat sensors are taken from https://www.usgs.gov/landsat-missions/using-usgs-landsat-level-1-data-product.

See Also

calcTOAIrradRadRef for the computation of the solar irradiance based on maximum radiation and reflection values of the dataset or calcTOAIrradModel for the computation of the solar irradiance based on look-up tables for the sensor's relative spectral response and solar irradiation spectral data.

See calcEarthSunDist for calculating the earth-sun distance based on the day of the year which is called by this function if ESun should be corrected for actual earth-sun distance.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LE07*.TIF"), full.names = TRUE)
sat <- satellite(files)
calcTOAIrradTable(sat)
 
calcTOAIrradTable(x = "LE7", normalize = FALSE, 
                  calcEarthSunDist("2015-01-01"))

Correct for topographic effects.

Description

Correct for topographic effects.

Usage

## S4 method for signature 'Satellite'
calcTopoCorr(x, mask = TRUE)

## S4 method for signature 'RasterStackBrick'
calcTopoCorr(x, hillsh, cloudmask = NULL, ...)

## S4 method for signature 'RasterLayer'
calcTopoCorr(x, hillsh, cloudmask = NULL, ...)

Arguments

x

Satellite or Raster* object.

mask

logical. If TRUE, the cloudmask from the Satellite object (if available) will be considered in the regression model.

hillsh

A RasterLayer created with hillShade.

cloudmask

A RasterLayer in which clouds are masked with NA values, passed to mask.

...

Additional arguments passed to writeRaster.

Details

The method of Civco (1989) is applied on atmospherically corrected bands (if not already available in the Satellite object, calcAtmosCorr is performed with its default settings.): First, an analytical hillshade image is created based on a DEM and sun elevation and sun zenith information from the metadata. A regression between the hillshade (independent variable) and each channel is then calculated with consideration of a cloudmask (if available). The regression coefficents are used to calibrate the hillshade raster (for each channel individually). Finally, the calibrated hillshade image is subtracted from the corresponding channel and the mean value of the channel is added.

Value

If x is a Satellite object, a Satellite object with added, topographic corrected layers; if x is a raster::Raster* object, a raster::Raster* object with converted layer(s).

References

CIVCO, D.L. (1989): Topographic normalization of Landsat Thematic Mapper digitalimagery. Photogrammetric Engineering & Remote Sensing, 55, 1303-1309.

Examples

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

## dem

files_dem <- list.files(path, pattern = "DEM", full.names = TRUE)
DEM <- raster(files_dem)

sat <- addSatDataLayer(sat, data = DEM, info = NULL, bcde = "DEM", in_bcde="DEM")

## Not run: 
sat <- calcTopoCorr(sat)

## End(Not run)

Get filename, bands and metadata file for Landsat 7 and 8 standard 1B/T format

Description

The function compiles the sensor, band, filename and metadata filename information for standard level 1B/T Landsat files.

Usage

compFilePathLandsat(files)

sortFilesLandsat(files, id = FALSE)

Arguments

files

Path and filename(s) of one or more Landsat band files or, alternatively, one or more Landsat metadata files.

id

logical, defaults to FALSE. Determines whether to return sorted band files (ie default) or sorting order.

Value

data.frame containing filepaths, band numbers and metadata filepaths.

If id = FALSE (default), sorted band files as character, else the corresponding sorting order as integer.

Functions

  • sortFilesLandsat(): Sort Landsat band files in ascending order.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)

compFilePathLandsat(files)  

sortFilesLandsat(files)
sortFilesLandsat(files, id = TRUE) # indices

Get calibration information from Landsat 8 standard level 1B/T filename

Description

The function scans a Lansat metadata file for various calibration and orbit coefficients as well as some sensor specific data.

Usage

compMetaLandsat(files)

Arguments

files

Path and filename of the Landsat metadata file.

Value

data.frame containing the following information for each band/layer:

  • DATE date (e.g. 2013-07-07)

  • SID sensor id (e.g. LC8)

  • SENSOR sensor name (e.g. Landsat 8)

  • SGRP sensor group (e.g. Landsat)

  • BID band id (e.g. 7)

  • BCDE band code (5 digit standard name, e.g B001n)

  • SRES spatial resolution of the sensor band (e.g. 30 for 30 m x 30m)

  • TYPE type of the sensor band regarding wavelength (e.g. VIS)

  • SPECTRUM spectral range regarding radiation source (e.g. solar)

  • CALIB type of applied calibration (e.g. SC for scaled counts)

  • RID region id (e.g. R00001) for multi region Satellite objects

  • RADA addtition coefficient for radiance conversion

  • RADM multiplication coefficient for radiance conversion

  • REFA addtition coefficient for reflectance conversion

  • REFM multiplication coefficient for reflectance conversion

  • BTK1 brightness temperature correction parameter

  • BTK2 brightness temperature correction parameter

  • SZEN sun zenith angle

  • SAZM sun azimuth angle

  • SELV sun elevation angle

  • ESD earth-sun distance (AU)

  • LMIN Minimum wavelength of the band (micrometer)

  • LMAX Maximum wavelength of the band (micrometer)

  • RADMIN Minimum radiance recorded by the band

  • RADMAX Maximum radiance recorded by the band

  • REFMIN Minimum reflectance recorded by the band

  • REFMAX Maximum reflectance recorded by the band

  • LNBR Layer number from 1 to n layers

  • LAYER Layer name

  • FILE Filepath of the data file

  • METAFILE Filepath of the metadata file

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
compMetaLandsat(files)

Convert a band's scaled counts to brightness temperature

Description

Convert a band's radiance values to brightness temperature without any kind of atmospheric correction etc.

Usage

## S4 method for signature 'Satellite'
convRad2BT(x)

## S4 method for signature 'RasterStack'
convRad2BT(x, k1, k2)

## S4 method for signature 'RasterLayer'
convRad2BT(x, k1, k2)

Arguments

x

An object of class Satellite, raster::RasterStack or raster::RasterLayer providing radiance values.

k1, k2

Temperature correction parameters.

Details

The conversion functions are taken from USGS' Landsat 8 Data Users Handbook which is available online at https://www.usgs.gov/landsat-missions/landsat-8-data-users-handbook.

Value

If x is a Satellite object, a Satellite object with added converted layers;
if x is a raster::Raster* object, a raster::Raster* object with converted layer(s).

See Also

calcAtmosCorr for converions of scaled counts to physical units including a scene-based atmospheric correction.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)  
sat <- convRad2BT(sat)

Convert a band's scaled counts or radiance values to reflectance

Description

Convert a band's scaled counts to reflectance using a simple linear conversion without any kind of atmospheric correction etc.

Usage

## S4 method for signature 'Satellite'
convRad2Ref(x, szen_correction = "TRUE")

## S4 method for signature 'RasterStack'
convRad2Ref(x, mult, add, szen)

## S4 method for signature 'RasterLayer'
convRad2Ref(x, mult, add, szen)

Arguments

x

An object of class Satellite, raster::RasterStack or raster::RasterLayer providing radiance values.

szen_correction

Logical; if TRUE, sun zenith correction is being applied.

mult

Multiplicative coefficient for value transformation (i.e. slope).

add

Additive coefficient for value transformation (i.e. offset)

szen

Cosine of solar zenith angle.

Details

The conversion functions are taken from USGS' Landsat 8 Data Users Handbook which is available online at https://www.usgs.gov/landsat-missions/landsat-8-data-users-handbook.

If the sensor does not provide linear conversion coefficients for reflectance computation, the reflectance is calculated using the solar irradiance following the functions taken from USGS' Landsat 7 manual, chapter 11.3.2, which is available online at https://www.usgs.gov/media/files/landsat-7-data-users-handbook.

Value

If x is a Satellite object, a Satellite object with added converted layers;
if x is a raster::Raster* object, a raster::Raster* object with converted layer(s).

See Also

calcAtmosCorr for conversions of scaled counts to physical units including a scene-based atmospheric correction.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)  
sat <- convRad2Ref(sat)

# If you use a raster layer, supply required meta information
bcde <- "B002n"
convRad2Ref(x = getSatDataLayer(sat, bcde),
            mult = getSatRADM(sat, bcde),
            add = getSatRADA(sat, bcde))

Convert reflectance to radiance using linear function coefficients

Description

The function converts the reflectance (ref) back to radiance (rad) given that linear conversion coefficients for both radiance and reflectance are available.

Usage

convRef2RadLinear(band, refm, refa, radm, rada, szen)

Arguments

band

raster::RasterStack or raster::RasterLayer containing reflectance.

refm

Multiplication coefficient for reflectance conversion.

refa

Addtition coefficient for reflectance conversion.

radm

Multiplication coefficient for radiance conversion.

rada

Addition coefficient for radiance conversion.

szen

Sun zenith angle.

Details

The conversion functions are taken from USGS' Landsat 8 Data Users Handbook which is available online at https://www.usgs.gov/landsat-missions/landsat-8-data-users-handbook.

Value

raster::Raster* object with converted values.


Convert a band's scaled counts to radiance

Description

Convert a band's scaled counts to radiance using a simple linear conversion without any kind of atmospheric correction etc.

Usage

## S4 method for signature 'Satellite'
convSC2Rad(x, szen_correction = "TRUE", subset = FALSE)

## S4 method for signature 'RasterStack'
convSC2Rad(x, mult, add, szen)

## S4 method for signature 'RasterLayer'
convSC2Rad(x, mult, add, szen)

Arguments

x

An object of class Satellite, raster::RasterStack or raster::RasterLayer providing scaled counts (DNs).

szen_correction

Logical; if TRUE, sun zenith correction is being applied.

subset

Logical; if TRUE, all layers but the cropped ones are being dropped; if FALSE (default), cropped layers are appended to the Satellite object.

mult

Multiplicative coefficient for value transformation (i.e. slope).

add

Additive coefficient for value transformation (i.e. offset).

szen

Cosine of solar zenith angle.

Details

The conversion functions are taken from USGS' Landsat 8 Data Users Handbook which is available online at https://www.usgs.gov/landsat-missions/landsat-8-data-users-handbook.

Value

If x is a Satellite object, a Satellite object with added converted layers;
if x is a raster::Raster* object, a raster::Raster* object with converted layer(s).

See Also

calcAtmosCorr for conversions of scaled counts to physical units including a scene-based atmospheric correction.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)  
sat <- convSC2Rad(sat)

# If you use a raster layer, supply required meta information
bcde <- "B002n"
convSC2Rad(x = getSatDataLayer(sat, bcde),
           mult = getSatRADM(sat, bcde),
           add = getSatRADA(sat, bcde))

Convert a band's scaled counts or radiance values to reflectance

Description

Convert a band's scaled counts to reflectance using a simple linear conversion without any kind of atmospheric correction etc.

Usage

## S4 method for signature 'Satellite'
convSC2Ref(x, szen_correction = "TRUE", subset = FALSE)

## S4 method for signature 'RasterStack'
convSC2Ref(x, mult, add, szen)

## S4 method for signature 'RasterLayer'
convSC2Ref(x, mult, add, szen)

Arguments

x

An object of class Satellite, raster::RasterStack or raster::RasterLayer providing scaled counts (DNs).

szen_correction

Logical; if TRUE, sun zenith correction is being applied.

subset

Logical; if TRUE, all layers but the cropped ones are being dropped; if FALSE (default), cropped layers are appended to the Satellite object.

mult

Multiplicative coefficient for value transformation (i.e. slope).

add

Additive coefficient for value transformation (i.e. offset).

szen

Cosine of solar zenith angle.

Details

The conversion functions are taken from USGS' Landsat 8 Data Users Handbook which is available online at https://www.usgs.gov/landsat-missions/landsat-8-data-users-handbook.

If the sensor does not provide linear conversion coefficients for reflectance computation, the reflectance is calculated using the solar irradiance following the functions taken from USGS' Landsat 7 manual, chapter 11.3.2, which is available online at https://www.usgs.gov/media/files/landsat-7-data-users-handbook.

Value

If x is a Satellite object, a Satellite object with added converted layers;
if x is a raster::Raster* object, a raster::Raster* object with converted layer(s).

See Also

calcAtmosCorr for conversions of scaled counts to physical units including a scene-based atmospheric correction.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)  
sat <- convSC2Ref(sat)

# If you use a raster layer, supply required meta information
bcde <- "B002n"
convSC2Ref(x = getSatDataLayer(sat, bcde),
           mult = getSatRADM(sat, bcde),
           add = getSatRADA(sat, bcde))

Crop Satellite object

Description

The function is a wrapper around the crop function to easily crop a Satellite object by an extent object.

Usage

## S4 method for signature 'Satellite'
crop(x, y, subset = TRUE, snap = "near")

Arguments

x

Satellite object.

y

extent object.

subset

Logical; if TRUE (default), all layers but the cropped ones are being dropped; if FALSE, cropped layers are appended to the Satellite object.

snap

Direction towards which to align the extent as character. Available options are "near" (default), "in" and "out" (see alignExtent).

Details

Crop layers of a Satellite object to the size of a given raster::extent object.

Value

A Satellite object consisting of cropped layers only. If subset = FALSE, a Satellite object with the cropped layers appended.

References

Please refer to the respective functions for references.

See Also

This function is a wrapper for raster::crop.

Examples

## Not run: 
## sample data
path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)

## geographic extent of georg-gassmann-stadium (utm 32-n)
ext_ggs <- raster::extent(484015, 484143, 5627835, 5628020)

## crop satellite object by specified extent
sat_ggs <- crop(sat, ext_ggs)

plot(sat)
plot(sat_ggs)

## End(Not run)

Compute terrain characteristics from digital elevation models

Description

Compute terrain characteristics from digital elevation models (DEM) using raster::terrain or raster::hillShade.

Usage

## S4 method for signature 'Satellite'
demTools(x, method = "hillShade", bcde = "DEM")

## S4 method for signature 'RasterLayer'
demTools(x, sunElev, sunAzim, method = "hillShade")

Arguments

x

A DEM provided as an object of class Satellite or RasterLayer.

method

Currently "slope", "aspect" and "hillshade" are implemented.

bcde

The name of the DEM layer in the Satellite object.

sunElev

If method = "hillShade", the elevation angle of the sun in degrees. See parameter angle in hillShade.

sunAzim

If method = "hillShade", the sun azimuth angle in degree. See parameter direction in hillShade.

Value

If x is a Satellite object, a Satellite object with added layer containing calculated terrain information; if x is a raster::RasterLayer object, a raster::RasterLayer object with calculated terrain information.

See Also

raster::terrain, raster::hillShade.

Examples

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

## dem
files_dem <- list.files(path, pattern = "DEM", full.names = TRUE)
DEM <- raster(files_dem)

sat <- addSatDataLayer(sat, data = DEM, info = NULL, bcde = "DEM", in_bcde="DEM")
sat <- demTools(sat)

Extend a Satellite object

Description

The function is a wrapper around extend to easily extend a Satellite object to a larger spatial extent.

Usage

## S4 method for signature 'Satellite'
extend(x, y, subset = TRUE, value = NA)

Arguments

x

Satellite object.

y

Target Extent, see extent.

subset

Logical. If TRUE (default), all layers but the extended ones are being dropped, else the extended layers are appended to the initial Satellite object.

value

Fill value assigned to new cells passed to extend, defaults to NA.

Value

A Satellite object consisting of extended layers only or, if subset = FALSE, a Satellite object with the extended layers appended.

See Also

This function is a wrapper around extend.

Examples

## Not run: 
## sample data
path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)

## geographic extent of georg-gassmann-stadium (utm 32-n)
ext_ggs <- raster::extent(482606.4, 482781.4, 5627239, 5627489)

## extend satellite object by specified extent
sat_ggs <- extend(sat, ext_ggs)

plot(sat)
plot(sat_ggs)

## End(Not run)

Landsat 7 sample data

Description

This dataset comes from the USGS. It contains part of the Landsat 7 scene LE07_L1TP_195025_20010730_20170204_01_T1 (Collection 1 Level-1) from 2001-07-30 over Maburg, Germany.

Format

RasterStack with bands 1-8 (incl. QA) of 41 by 41 pixels.

Details

Use of this data requires your agreement to the USGS regulations on using Landsat data.

Source

https://earthexplorer.usgs.gov/

Examples

plotRGB(l7, r = 3, b = 1, stretch = "hist")

Landsat 8 sample data

Description

This dataset comes from the USGS. It contains part of the Landsat 8 scene LC08_L1TP_195025_20130707_20170503_01_T1 (Collection 1 Level-1) from 2013-07-07 over Maburg, Germany.

Format

RasterStack with bands 1-7, 9-11 (incl. QA) of 41 by 41 pixels.

Details

Use of this data requires your agreement to the USGS regulations on using Landsat data.

Source

https://earthexplorer.usgs.gov/

Examples

plotRGB(l8, r = 4, g = 3, b = 2, stretch = "hist") # true-color composite
plotRGB(l8, r = 5, g = 4, b = 3, stretch = "hist") # false-color composite

Get or access internal LUT values used by various functions

Description

Get internal look-up table (LUT) values from sysdata.rda which have been compiled using data-raw/lut_data.R. Metadata is stored in lut$meta.

Usage

lutInfo()

lutInfoBandsFromSID(sid)

lutInfoSensorFromSID(sid)

lutInfoBCDEFromBID(sid, bid)

lutInfoBIDFromBCDE(bcde, sid)

lutInfoRSRromSID(sid)

lutInfoSIDfromFilename(files)

lutInfoSGRPfromFilename(file)

Arguments

sid

Sensor id as returned e.g. from lutInfoSensorFromSID.

bid

Band id as returned e.g. from lutInfoBIDFromBCDE.

bcde

Band code as returned e.g. from lutInfoBCDEFromBID.

files

Filename (or filepath) of one or more remote sensing data filenames

file

Filename of a remote sensing data file

Details

The functions above return the following information:

  • lutInfoBandsFromSID returns the band info block.

  • lutInfoBCDEFromBID returns the band code.

  • lutInfoBIDFromBCDE returns the band ids.

  • lutInfoRSRromSID returns the relative spectral response (rsr) for the sensor.

  • lutInfoSensorFromSID returns the sensor name.

The LUT contains the following band information taken, if not specified otherwise, from the USGS Landsat FAQ:

l4_band_wl

Minimum/maximum wavelength for Landsat 4 bands.

l5_band_wl

Minimum/maximum wavelength for Landsat 5 bands.

l7_band_wl

Minimum/maximum wavelength for Landsat 7 bands.

l8_band_wl

Minimum/maximum wavelength for Landsat 8 bands.

l7_rsr

Landat 7 rsr (nm-1) taken from the spectral viewer of the USGS Landsat FAQ.

l8_rsr

Landat 8 rsr (nm-1) taken from the spectral viewer of the USGS Landsat FAQ.

solar

Solar irradiance (W m-2 nm-1) taken from the National Renewable Energy Laboratory.

l7_esun

Tabulated ESun values from tab 11.3 (Thuillier spectrum) of the Landsat7 handbook.

l5_esun, l4_esun

Tabulated ESun values from Chander G, Markham B (2003) Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges. IEEE Transaction on Geoscience and Remote Sensing 41/11, doi:10.1109/LGRS.2007.898285.

Value

List containing several data.frame objects with LUT values.

Functions

  • lutInfoBandsFromSID():

  • lutInfoSensorFromSID():

  • lutInfoBCDEFromBID():

  • lutInfoBIDFromBCDE():

  • lutInfoRSRromSID():

  • lutInfoSIDfromFilename():

  • lutInfoSGRPfromFilename():

Examples

ls_li <- lutInfo()
# str(ls_li)

Identify pseudo-invariant features from a satellite scene

Description

Identify pseudo-invariant features from a satellite scene based on a vis, near infravis and short-wave infravis band.

Usage

## S4 method for signature 'Satellite'
maskInvarFeatures(x)

## S4 method for signature 'RasterStack'
maskInvarFeatures(x, quant = 0.01, id_vis = 1L, id_nir = 2L, id_swir = 3L)

## S4 method for signature 'RasterLayer'
maskInvarFeatures(x, nir, swir, quant = 0.01)

Arguments

x

A Satellite object or a raster::RasterLayer providing the sensor's vis band.

quant

A value v = [0...1] which is used to define the percentage threshold values (thv) for invariant features (nir/vis ratio < thv, swir band values > 1-thv).

id_vis

Index of the visible band.

id_nir

Index of the near infravis band.

id_swir

Index of the short-wave infravis band.

nir

A raster::RasterLayer containing the sensor's nir band.

swir

A raster::RasterLayer containing the sensor's swir band.

Details

Invariant features are identified as pixels which belong to the group of (i) the n lowest VIS/NIR ratios and of (ii) the highest n SWIR values. The value of n is given by the parameter quant = [0...1].

Value

If x is a Satellite object, a Satellite object with added layer;
if x is a raster::RasterLayer object, a a raster::RasterLayer object with added layers (1 indicates invariant pixels, 0 otherwise).

References

This function is taken and only slightly modified from the PIF function by Sarah C. Goslee (2011). Analyzing Remote Sensing Data in R: The landsat Package. Journal of Statistical Software,43(4), 1-25, doi:10.18637/jss.v043.i04.

The underlying theory has been published by Schott RJ, Salvaggio C and Volchok WJ (1988) Radiometric scene normalization using pseudoinvariant features. Remote Sensing of Environment 26/1, doi:10.1016/0034-4257(88)90116-2.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)
sat <- maskInvarFeatures(sat)

maskInvarFeatures(x = getSatDataLayer(sat, "B004n"), 
                  nir = getSatDataLayer(sat, "B005n"), 
                  swir = getSatDataLayer(sat, "B007n"))

## when dealing with a 'RasterStack'
rst <- stack(files[c(6, 7, 9)])
maskInvarFeatures(rst)

Get/set Satellite data layer names

Description

Get/set Satellite data layer names, i.e. the BCDE id.

Usage

## S4 method for signature 'Satellite'
names(x)

## S4 replacement method for signature 'Satellite'
names(x) <- value

Arguments

x

A Satellite object.

value

Band codes of the individual data layers.

Value

Satellite data layer names as character vector.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)
names(sat)
new_names <- paste0(names(sat), "_test")
names(sat) <- new_names

Plot a Satellite object

Description

This is the standard plotting routine for the 'Satellite' class. Layers are drawn either from the start (default; limited to a maximum of 16 sub-plots) or according to the speficied band codes.

Usage

## S4 method for signature 'Satellite,ANY'
plot(x, bcde = NULL, col = grDevices::grey.colors(100), ...)

Arguments

x

A 'Satellite' object, usually returned by satellite.

bcde

Band codes to be visualized, e.g. returned by getSatBCDE. If not supplied, the initial (up to) 16 layers are being visualized.

col

Color scheme.

...

Further arguments passed on to plot.default.

See Also

plot.default, par.

Examples

## Not run: 
## sample data
path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)

## display data without quality flag layer
bds <- getSatBCDE(sat)[1:11]
plot(sat, bcde = bds)

## End(Not run)

Create a Satellite object

Description

Method to create a Satellite object.

Usage

## S4 method for signature 'character'
satellite(x, meta, log)

## S4 method for signature 'Raster'
satellite(x, meta, log)

## S4 method for signature 'list'
satellite(x, meta, log)

Arguments

x

A vector of filenames, a (multi-layered) Raster* object or a list of single RasterLayer objects (see raster). In the latter case, be aware that bands must be arranged in ascending order (eg using sortFilesLandsat).

meta

Optional metadata object (e.g. returned from compMetaLandsat). If 'x' is a satellite dataset and recognised as "Landsat", then the metadata is automatically extracted from the respective meta information file if both the satellite data and the metadata file follow the USGS Earth Explorer's naming convention.

log

Optionally supply a log entry.

Details

A Satellite object consists of three data sections: (i) a raster data section which holds the actual data values of the respective sensor bands, (ii) a metadata grid which holds meta information for each sensor band (e.g. calibration coefficients, type of sensor band etc.) and (iii) a list of log information which records the processing history of the entire dataset.

Value

A Satellite object.

See Also

(i) compMetaLandsat to get more information about the structure of the metadata component; (ii) https://www.usgs.gov/faqs/what-naming-convention-landsat-collections-level-1-scenes?qt-news_science_products=0#qt-news_science_products for detailed information about the naming conventions for Landsat scene identifiers; and (iii) sortFilesLandsat for automated rearrangement of Landsat band files.

Examples

## 'character' input (i.e. filenames)
path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)

satellite(files)

## raster::RasterStack input
satellite(l8)

An S4 class to represent a complete satellite dataset

Description

An S4 class to represent a complete satellite dataset


An S4 class to represent a satellite data file

Description

An S4 class to represent a satellite data file

Slots

name

name of the data file without extension

filepath

full path and file of the data file

path

path to the data file

file

filename incl. extension of the data file

extension

extension of the data file


An S4 class to represent satellite data

Description

An S4 class to represent satellite data

Slots

layers

a list object containing individual RasterLayer objects


An S4 class to represent satellite log data

Description

An S4 class to represent satellite log data

Slots

log

a list object containing information on individual processing steps


An S4 class to represent satellite metadata

Description

An S4 class to represent satellite metadata

Slots

meta

a data frame object containing the data


Get or access Satellite object information used by various functions

Description

Get information from class Satellite.

Usage

getSatDataLayers(sat, bcde = NULL)

getSatDataLayer(sat, bcde)

getSatMeta(sat, bcde)

getSatMetaBCDETemplate(sat, bcde)

getSatLog(sat)

setSatBCDE(sat, bcde)

createSatBCDE(sat, width = 3, flag = 0, prefix = "B", postfix = "n")

addSatMetaParam(sat, meta_param)

addSatMetaEntry(sat, meta_param)

addSatLog(
  sat,
  info = NA_character_,
  in_bcde = NA_character_,
  out_bcde = NA_character_
)

addSatDataLayer(sat, bcde, data, meta_param, info, in_bcde)

addRasterMeta2Sat(sat)

createRasterMetaData(rst)

updateRasterMetaData(sat, bcde)

countSatDataLayers(sat)

getSatParam(sat, param, bcde, return_bcde = TRUE)

getSatBCDE(sat, lnbr)

getSatBID(sat, bcde)

getSatSID(sat)

getSatSensor(sat)

getSatSensorGroup(sat)

getSatSensorInfo(sat)

getSatSpectrum(sat, bcde)

getSatBCDESolar(sat)

getSatBCDEThermal(sat)

getSatXRes(sat, bcde)

getSatYRes(sat, bcde)

getSatRes(sat, bcde)

getSatType(sat, bcde)

getSatCalib(sat, bcde)

getSatBCDEType(sat, bcde, type)

getSatBCDEFromType(sat, type = "VIS")

getSatBCDEFromSpectrum(sat, spectrum = "solar")

getSatBCDESres(sat, bcde, type)

getSatBCDECalib(sat, bcde, calib)

getSatBCDESolarCalib(sat, bcde, calib)

getSatBCDEThermalCalib(sat, bcde, calib)

getSatBandInfo(sat, bcde, return_calib = TRUE)

getSatRadMax(sat, bcde)

getSatRadMin(sat, bcde)

getSatRefMax(sat, bcde)

getSatRefMin(sat, bcde)

getSatESD(sat)

getSatESUN(sat, bcde)

getSatSZEN(sat, bcde)

getSatSAZM(sat, bcde)

getSatSELV(sat, bcde)

getSatMetaLayer(sat, bcde)

getSatLayerfromData(sat, bcde, nbr)

getSatLNBR(sat, bcde)

getSatLMIN(sat, bcde)

getSatLMAX(sat, bcde)

getSatRADA(sat, bcde)

getSatRADM(sat, bcde)

getSatREFA(sat, bcde)

getSatREFM(sat, bcde)

getSatBTK1(sat, bcde)

getSatBTK2(sat, bcde)

getSatPRAD(sat, bcde)

getSatDATE(sat, bcde)

getSatProjection(sat, bcde)

Arguments

sat

Satellite object (see satellite).

bcde

Band code.

width, flag

Field width and format modifier for automated creation of BCDE information, defaults to '3' and '0', respectively. See formatC for further details.

prefix, postfix

Prefix and postfix to be added to the created BCDE information.

meta_param

Metadata parameters used to document new data layer

info

Log information added to metadata

in_bcde

BCDE of layer used as input dataset

out_bcde

BCDE of layer used as output dataset

data

Data layer of a Satellite object

rst

Input raster::Raster* object from which to extract metadata.

param

Parameter of the metadata set (i.e. colname)

return_bcde

Return bcde as attribute (TRUE/FALSE)

lnbr

Layer number

type

Type of the sensor band

spectrum

Spectral region, e.g. "solar" or "thermal".

calib

Calibration information.

return_calib

Return calibration information (TRUE/FALSE)

nbr

Return specific data layer selected by number

Details

The functions are generally self-explaining in that sence that get* returns the respective information and set* sets the respective information from/in the Satellite object.

addSatLog adds a log entry to the Satellite object.

Value

Objects of respective type (see satellite).

Functions

  • getSatDataLayers(): Return Satellite data layers

  • getSatDataLayer(): Return Satellite data layer i

  • getSatMeta(): Return Satellite object metadata

  • getSatMetaBCDETemplate(): Return template for Satellite object metadata which is based on existing band

  • getSatLog(): Return Satellite object log info

  • setSatBCDE(): Set BCDE/data layer names of a Satellite object

  • createSatBCDE(): If not supplied, automatically create BCDE names of a Satellite object

  • addSatMetaParam(): Add additional or overwrite metainformation parameter to Satellite object

  • addSatMetaEntry(): Add metainformation for an additional layer to Satellite object

  • addSatLog(): Add new log entry to Satellite object

  • addSatDataLayer(): Add new Satellite data layer

  • addRasterMeta2Sat(): Add raster meta data to Satellite object meta data

  • createRasterMetaData(): Create raster meta data

  • updateRasterMetaData(): Create raster meta data

  • countSatDataLayers(): Return number of Satellite data layers

  • getSatParam(): Return parameter (general method implemented by the specific functions below)

  • getSatBCDE(): Return Band code

  • getSatBID(): Return Band IDs

  • getSatSID(): Return sensor ID

  • getSatSensor(): Return sensor

  • getSatSensorGroup(): Return sensor group

  • getSatSensorInfo(): Return sensor information

  • getSatSpectrum(): Return spectrum

  • getSatBCDESolar(): Return solar band codes

  • getSatBCDEThermal(): Return thermal band codes

  • getSatXRes(): Return sensor x resolution

  • getSatYRes(): Return sensor y resolution

  • getSatRes(): Return mean sensor resolution (mean of x and y res)

  • getSatType(): Return sensor type

  • getSatCalib(): Return calibration level

  • getSatBCDEType(): Return TYPE band codes

  • getSatBCDEFromType(): Return BCDE matching TYPE

  • getSatBCDEFromSpectrum(): Return BCDE matching TYPE

  • getSatBCDESres(): Return the mean of x and y resolution for band codes matching type

  • getSatBCDECalib(): Return calibration level for band codes matching type

  • getSatBCDESolarCalib(): Return calibration level for band codes machting type and are solar bands

  • getSatBCDEThermalCalib(): Return calibration level for band codes machting type and are thermal bands

  • getSatBandInfo(): Return band information

  • getSatRadMax(): Return maximum radiance for bcde

  • getSatRadMin(): Return minimum radiance for bcde

  • getSatRefMax(): Return maximum reflectance for bcde

  • getSatRefMin(): Return minimum reflectance for bcde

  • getSatESD(): Return earth-sun distance

  • getSatESUN(): Return actual solar TOA irradiance

  • getSatSZEN(): Return sun zenith angle

  • getSatSAZM(): Return sun azimuth angle

  • getSatSELV(): Return Sun elevation

  • getSatMetaLayer(): Return Layer name from metadata

  • getSatLayerfromData(): Return Layer name from data layer

  • getSatLNBR(): Return Layer number

  • getSatLMIN(): Return minimum wavelength of the sensor band

  • getSatLMAX(): Return maximum wavelength of the sensor band

  • getSatRADA(): Return addition coefficient for SC to radiance conversion

  • getSatRADM(): Return multiplicative coefficient for SC to radiance conversion

  • getSatREFA(): Return addition coefficient for SC to reflectance

  • getSatREFM(): Return multiplicative coefficient for SC to reflectance

  • getSatBTK1(): Return calibration coefficent to convert SC to brightness temperature

  • getSatBTK2(): Return calibration coefficent to convert SC to brightness temperature

  • getSatDATE(): Return DATE

  • getSatProjection(): Return projection

Examples

# List of input files
path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)

# Raster stack l8
sat <- satellite(l8)

Convert selected layers of a Satellite object to a RasterStack

Description

Convert selected layers of a Satellite object to a RasterStack

Usage

## S4 method for signature 'Satellite'
stack(x, layer = names(x), ...)

Arguments

x

an object of class 'Satellite'

layer

character vector (bcde codes) or integer vector (index) of the layers to be stacked

...

additional arguments passed on to stack

Examples

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

stck <- stack(sat, c("B001n", "B002n", "B003n"))
stck

Subset of Satellite object data layers

Description

Create a subset of data layers from a Satellite object and return it as a standalone Satellite object.

Usage

## S4 method for signature 'Satellite'
subset(x, sid, cid)

## S4 method for signature 'Satellite,ANY,ANY'
x[[i]]

Arguments

x

Satellite object providing the source band(s) to be adjusted.

sid

Band numbers or bcde which should be extracted

cid

Calibration information used for subsetting (only works if sid is not supplied to the function)

i

Layer index(es) for subsetting.

Value

A Satellite object

A Satellite object

A Satellite object

Examples

## sample data
path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)

sat[[2:5]]
subset(sat, cid = "SC")