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i.pca(1grass) | Grass User's Manual | i.pca(1grass) |
NAME¶
i.pca - Principal components analysis (PCA) for image processing.KEYWORDS¶
imagery, image transformation, PCASYNOPSIS¶
i.pcaParameters:¶
- input=name[,name,...]
-
- output_prefix=string
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- rescale=min,max
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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,...]
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- output=name
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- rescale=min,max
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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 datasetEigen 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.ccaAUTHOR¶
David Satnik, GIS Laboratory Major modifications for GRASS 4.1 were made byGRASS 6.4.2 |