抽出値

Question

pcaRasters 
$call 
rasterPCA(img = predictors) 

$model 
Call: 
princomp(cor = spca, covmat = covMat[[1]]) 

Standard deviations: 
     Comp.1  Comp.2  Comp.3  Comp.4  Comp.5  Comp.6  Comp.7  Comp.8  Comp.9 
498.96308248 356.19955279 166.82560362 79.75533403 28.30786958 18.01329729 11.05097697 5.90091966 4.85153037 
    Comp.10  Comp.11  Comp.12  Comp.13  Comp.14  Comp.15  Comp.16  Comp.17  Comp.18 
    3.96912826 2.92429575 2.32486057 1.74476578 1.37242353 0.99700591 0.69100295 0.52470761 0.38599513 
    Comp.19  Comp.20  Comp.21  Comp.22  Comp.23 
    0.30199746 0.12861497 0.05112695 0.01751713 0.00000000 

23 variables and 1034761 observations. 

$map 
class  : RasterBrick 
dimensions : 959, 1079, 1034761, 23 (nrow, ncol, ncell, nlayers) 
resolution : 0.008333334, 0.008333334 (x, y) 
extent  : 24.99168, 33.98334, -23.00833, -15.01666 (xmin, xmax, ymin, ymax) 
coord. ref. : +proj=longlat +ellps=WGS84 +no_defs 
data source : in memory 
names  :   PC1,   PC2,   PC3,   PC4,   PC5,   PC6,   PC7,   PC8,   PC9,   PC10,   PC11,   PC12,   PC13,   PC14,   PC15, ... 
min values : -1.525414e+03, -8.294717e+02, -1.597420e+03, -2.924969e+02, -4.018654e+02, -9.054122e+01, -4.005998e+01, -1.802074e+01, -2.699063e+01, -2.808965e+01, -1.337488e+01, -1.268085e+01, -1.224565e+01, -1.060565e+01, -4.378304e+00, ... 
max values : 1.589643e+03, 1.964028e+03, 3.989713e+02, 3.699300e+02, 1.310118e+02, 7.833018e+01, 6.450310e+01, 2.629923e+01, 3.463626e+01, 2.732504e+01, 1.044373e+01, 1.601244e+01, 3.073991e+01, 5.426831e+00, 7.680870e+00, ... 

Answer 1

#sample data 

data(rlogo) 
ggRGB(rlogo, 1,2,3) 
pcaRasters <- rasterPCA(rlogo) 

アクセス値：

getValues(pcaRasters$map) 
        PC1   PC2   PC3 
    [1,] -118.27810276 -4.054375764 0.726071167 
    [2,] -118.27810276 -4.054375764 0.726071167 
    [3,] -118.27810276 -4.054375764 0.726071167 

プロットラスタ：

plot(pcaRasters$map) 

ディスクへの保存

：

writeRaster(pcaRasters$map, "filename.tif")