I was doing PCA on 35 rasters with some environmental data (climond). Everything works fine and I use this command in R to perform a PCA on raster stack:
pca<-princomp(na.omit(values(s)), cor=TRUE)
All the rasters look fine but each of the components is exaplaining exactly the same proportion of variance (0.029), so in the end they sum to 1. It's a bit strange for me because I'm used to the result that e.g. first three pca axes explain e.g. 50% of variance and the rest of the components is exaplaining less and less of it. So is my result correct or should I do some modification the the princcomp? That's how it looks like:
Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6 Comp.7 Comp.8 Comp.9
SS loadings 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
Proportion Var 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029
Cumulative Var 0.029 0.057 0.086 0.114 0.143 0.171 0.200 0.229 0.257
Comp.10 Comp.11 Comp.12 Comp.13 Comp.14 Comp.15 Comp.16 Comp.17
SS loadings 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
Proportion Var 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029
Cumulative Var 0.286 0.314 0.343 0.371 0.400 0.429 0.457 0.486
Comp.18 Comp.19 Comp.20 Comp.21 Comp.22 Comp.23 Comp.24 Comp.25
SS loadings 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
Proportion Var 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029
Cumulative Var 0.514 0.543 0.571 0.600 0.629 0.657 0.686 0.714
Comp.26 Comp.27 Comp.28 Comp.29 Comp.30 Comp.31 Comp.32 Comp.33
SS loadings 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
Proportion Var 0.029 0.029 0.029 0.029 0.029 0.029 0.029 0.029
Cumulative Var 0.743 0.771 0.800 0.829 0.857 0.886 0.914 0.943
Comp.34 Comp.35
SS loadings 1.000 1.000
Proportion Var 0.029 0.029
Cumulative Var 0.971 1.000
However the eigenvalues (or standard deviation here) is decreasing:
Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6
4.129756e+00 2.608465e+00 1.679122e+00 1.514034e+00 1.380337e+00 1.196104e+00
Comp.7 Comp.8 Comp.9 Comp.10 Comp.11 Comp.12
8.529524e-01 7.653760e-01 5.784449e-01 5.179734e-01 4.731845e-01 3.555741e-01
Comp.13 Comp.14 Comp.15 Comp.16 Comp.17 Comp.18
2.995183e-01 2.672110e-01 2.287449e-01 1.907395e-01 1.776953e-01 1.665386e-01
Comp.19 Comp.20 Comp.21 Comp.22 Comp.23 Comp.24
1.547910e-01 1.389805e-01 1.216129e-01 1.167798e-01 1.106441e-01 8.282240e-02
Comp.25 Comp.26 Comp.27 Comp.28 Comp.29 Comp.30
7.930042e-02 7.283533e-02 6.605863e-02 6.310874e-02 4.944323e-02 4.318459e-02
Comp.31 Comp.32 Comp.33 Comp.34 Comp.35
3.272761e-02 2.591280e-02 2.395581e-02 1.479677e-02 1.191348e-07
I hope it is a relevant question! Thank's in advance for answering.
