Geographic Information Systems Asked on July 11, 2021
I am struggling to understand the interpretation for eigenvalues for a false-color NIR LANDSAT TM image. The image is shown below. (Note: I’m using ENVI Classic, but this is a general question and not necessarily software specific).
To see how the bands correlate to one another, I generated the correlation matrix and the eigenvector matrix, as seen below:
Correlation Band 1 Band 2 Band 3 Band 4 Band 5 Band 6
Band 1 1.000000 0.961168 0.939219 -0.199623 0.458798 0.694562
Band 2 0.961168 1.000000 0.960990 -0.197893 0.509627 0.718807
Band 3 0.939219 0.960990 1.000000 -0.338474 0.524662 0.781865
Band 4 -0.199623 -0.197893 -0.338474 1.000000 0.214992 -0.107974
Band 5 0.458798 0.509627 0.524662 0.214992 1.000000 0.876531
Band 6 0.694562 0.718807 0.781865 -0.107974 0.876531 1.000000
Eigenvector Band 1 Band 2 Band 3 Band 4 Band 5 Band 6
Band 1 -0.286913 -0.180856 -0.327835 -0.045758 -0.754041 -0.454781
Band 2 -0.184842 -0.107840 -0.256091 0.914194 0.209379 -0.095033
Band 3 -0.585081 -0.319049 -0.435785 -0.377332 0.467093 0.073647
Band 4 0.175129 0.203321 0.011737 -0.120604 0.408026 -0.864189
Band 5 0.693180 -0.204841 -0.679428 -0.068775 0.022622 0.103332
Band 6 -0.173279 0.877821 -0.418657 -0.022377 -0.049092 0.145671
Bands 1-3 are highly correlated in the correlation matrix because they are in the visible spectrum. There is less correlation in the eigenvector matrix; what exactly is the purpose of looking at the eigenvector matrix, and what is a practical interpretation for this data?
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