Importance of Higher-Order Components to Multispectral Classification
by J. V. Dave, R. Bernstein, H. G. Kolsky
A Landsat multispectral image was combined with the corresponding digital terrain elevation data to study several information extraction procedures. Principal component and limited multispectral classification procedures were conducted on 1024 × 1024 four-band Landsat and five-band (Landsat plus terrain data) images, and color composites as well as quantitative information were generated. Selected results of this preliminary investigation confirm the usefulness of the principal component analysis in a qualitative presentation of the multi-band data and its association with a significant reduction in dimensionality. However, unlike some other investigators, we found that the full dimensionality must be retained when the information content of the data has to be preserved quantitatively.