A Simplified Approach for Interpreting Principal Component Images


Principal component transformation is a standard technique for multi-dimensional data analysis. The purpose of the present article is to elucidate the procedure for interpreting PC images. The discussion focuses on logically explaining how the negative/positive PC eigenvectors (loadings) in combination with strong reflection/absorption spectral behavior at different pixels affect the DN values in the output PC images. It is an explanatory article so that fuller potential of the PCT applications can be realized.

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R. Gupta, R. Tiwari, V. Saini and N. Srivastava, "A Simplified Approach for Interpreting Principal Component Images," Advances in Remote Sensing, Vol. 2 No. 2, 2013, pp. 111-119. doi: 10.4236/ars.2013.22015.

Conflicts of Interest

The authors declare no conflicts of interest.


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