i.pca.1grass

Langue: en

Version: 337979 (ubuntu - 24/10/10)

Section: 1 (Commandes utilisateur)

NAME

i.pca - Principal components analysis (pca) program for image processing.

KEYWORDS

imagery, image transformation, PCA

SYNOPSIS

i.pca
i.pca help
i.pca input=name[,name,...] output=name [rescale=min,max] [--overwrite] [--verbose] [--quiet]

Flags:

--overwrite

Allow output files to overwrite existing files
--verbose

Verbose module output
--quiet

Quiet module output

Parameters:

input=name[,name,...]

Name of two or more input raster maps
output=name

Base name for output raster maps
A numerical suffix will be added for each component map
rescale=min,max

Rescaling range for output maps (for no rescaling use 0,0)
Default: 0,255

DESCRIPTION

i.pca is an image processing program based on the algorithm provided by Vali (1990), that processes n (n >= 2) input raster map layers and produces n output raster map layers containing the principal components of the input data in decreasing order of variance ("contrast"). The output raster map layers are assigned names with .1, .2, ... .n suffixes. The current geographic region definition and MASK settings are respected when reading the input raster map layers. When the rescale option is used, the output files are rescaled to fit the min,max range.

OPTIONS

Parameters:

input=name,name[,name,name,...]

Name of two or more input raster map layers.
output=name

The output raster map layer name to which suffixes are added. Each output raster map layer is assigned this user-specified name with a numerical (.1, .2, ...
rescale=min,max

The optional output category range. (Default: 0,255) If rescale=0,0, no rescaling is performed on output files.
If output is rescaled, the output raster will be of type CELL. If the output is not rescaled, the output raster will be of type DCELL.

NOTES

Richards (1986) gives a good example of the application of principal components analysis (pca) to a time series of LANDSAT images of a burned region in Australia.

Eigenvalue and eigenvector information is stored in the output maps' history files. View with r.info.

EXAMPLE

Using the Spearfish Imagery sample dataset
i.pca in=spot.ms.1,spot.ms.2,spot.ms.3 out=spot_pca

r.info -h spot_pca.1

   Eigen values, (vectors), and [percent importance]:

   PC1   1170.12 ( -0.63 -0.65 -0.43 ) [ 88.07% ]

   PC2    152.49 (  0.23  0.37 -0.90 ) [ 11.48% ]

   PC3      6.01 (  0.75 -0.66 -0.08 ) [  0.45% ]

SEE ALSO

Richards, John A., Remote Sensing Digital Image Analysis, Springer-Verlag, 1986.

Vali, Ali R., Personal communication, Space Research Center, University of Texas, Austin, 1990.

i.cca
i.class
i.fft
i.ifft
m.eigensystem
r.covar
r.mapcalc

AUTHOR

David Satnik, GIS Laboratory

Major modifications for GRASS 4.1 were made by
Olga Waupotitsch and Michael Shapiro, U.S.Army Construction Engineering Research Laboratory

Rewritten for GRASS 6.x and major modifications by
Brad Douglas

Last changed: $Date: 2009-03-03 00:44:13 +0100 (mar, 03 mar 2009) $

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