tasseledCap { RStoolbox}R Documentation

Tasseled Cap Transformation

R: Tasseled Cap Transformation

Description

Calculates brightness, greenness and wetness from multispectral imagery. Currently implemented Landsat 4 TM, Landsat 5 TM, Landsat 7ETM+, Landsat 8 OLI and MODIS.

Usage

tasseledCap(img, sat, ...)

Arguments

img

RasterBrick or RasterStack. Input image. Band order must correspond to sensor specifications (see Details and Examples)

sat

Character. Sensor; one of: c("Landsat4TM", "Landsat5TM", "Landsat7ETM", "Landsat8OLI", "MODIS"). Case is irrelevant.

...

Further arguments passed to writeRaster.

Details

Currently implemented: Landsat 4 TM, Landsat 5 TM, Landsat 7ETM+, Landsat 8 OLI and MODIS. Input data must be in top of atmosphere reflectance. Moreover, bands must be provided in ascending order as listed in the table below. Irrelevant bands, such as Landsat Thermal Bands must be omitted. Required bands are:

sat bands coefficients data unit
Landsat4TM 1,2,3,4,5,7 Crist 1985 reflectance
Landsat5TM 1,2,3,4,5,7 Crist 1985 reflectance
Landsat7ETM 1,2,3,4,5,7 Huang 2002 reflectance
Landsat8OLI 2,3,4,5,6,7 Baig 2014 reflectance
MODIS 1,2,3,4,5,6,7 Lobser 2007 reflectance

Value

Returns a RasterBrick with the thee bands: brigthness, greenness, and (soil) wetness.

References

Crist (1985) "A TM Tasseled Cap Equivalent Transformation for Reflectance Factor Data." Remote Sensing of Environment 17 (3): 301-306

Huang et al. (2002) "Derivation of a Tasselled Cap Transformation Based on Landsat 7 At-Satellite Reflectance." International Journal of Remote Sensing 23 (8): 1741-1748

Baig et al. (2014) "Derivation of a Tasselled Cap Transformation Based on Landsat 8 At-Satellite Reflectance." Remote Sensing Letters 5 (5): 423-431.

Lobser et al. (2007) "MODIS Tasselled Cap: Land Cover Characteristics Expressed through Transformed MODIS Data." International Journal of Remote Sensing 28 (22): 5079-5101.

Examples

library(raster)
data(lsat)

## Run tasseled cap (exclude thermal band 6)
lsat_tc <- tasseledCap(lsat[[c(1:5,7)]], sat = "Landsat5TM")
lsat_tc
#> class       : RasterBrick 
#> dimensions  : 310, 287, 88970, 3  (nrow, ncol, ncell, nlayers)
#> resolution  : 30, 30  (x, y)
#> extent      : 619395, 628005, -419505, -410205  (xmin, xmax, ymin, ymax)
#> coord. ref. : +proj=utm +zone=22 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 
#> data source : in memory
#> names       : brightness, greenness,  wetness 
#> min values  :    33.0776,  -17.5292, -95.8932 
#> max values  :   254.0931,   73.0650,   9.0928
plot(lsat_tc)

plot of chunk unnamed-chunk-1


[Package RStoolbox version 0.2.0 Index]