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.
The order of the input bands does not matter for the output maps (PC scores), but does matter for the vectors (loadings), since each loading refers to a specific input band.
If the output is not rescaled (rescale=0,0, the output raster maps will be of type DCELL, otherwise the output raster maps will be of type CELL.
By default, the values of the input raster maps are centered for each map separately with x - mean. With -n, the input raster maps are normalized for each map separately with (x - mean) / stddev. Normalizing is highly recommended when the input raster maps have different units, e.g. represent different environmental parameters.
The -f flag, together with the percent option, can be used to remove noise from input bands. Input bands will be recalculated from a subset of the principal components (inverse PCA). The subset is selected by using only the most important (highest eigenvalue) principal components which explain together percent percent variance observed in the input bands.
Eigenvalue and eigenvector information is stored in the output maps' history files. View with r.info.
g.region raster=lsat7_2002_10 -p i.pca in=lsat7_2002_10,lsat7_2002_20,lsat7_2002_30,lsat7_2002_40,lsat7_2002_50,lsat7_2002_70 \ out=lsat7_2002_pca r.info -h lsat7_2002_pca.1 Eigen values, (vectors), and [percent importance]: PC1 4334.35 ( 0.2824, 0.3342, 0.5092,-0.0087, 0.5264, 0.5217) [83.04%] PC2 588.31 ( 0.2541, 0.1885, 0.2923,-0.7428,-0.5110,-0.0403) [11.27%] PC3 239.22 ( 0.3801, 0.3819, 0.2681, 0.6238,-0.4000,-0.2980) [ 4.58%] PC4 32.85 ( 0.1752,-0.0191,-0.4053, 0.1593,-0.4435, 0.7632) [ 0.63%] PC5 20.73 (-0.6170,-0.2514, 0.6059, 0.1734,-0.3235, 0.2330) [ 0.40%] PC6 4.08 (-0.5475, 0.8021,-0.2282,-0.0607,-0.0208, 0.0252) [ 0.08%] d.mon wx0 d.rast lsat7_2002_pca.1 # ... d.rast lsat7_2002_pca.6
Vali, Ali R., Personal communication, Space Research Center, University of Texas, Austin, 1990.
Principal Components Analysis article
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Olga Waupotitsch and Michael Shapiro, U.S.Army Construction Engineering Research Laboratory
Principal Components Analysis article (GRASS Wiki)
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© 2003-2020 GRASS Development Team, GRASS GIS 7.6.2dev Reference Manual