High-spectral-resolution remote-sensing data are first transformed so that the noise covariance matrix becomes the identity matrix. Then the principal components transform is applied. This transform is equivalent to the maximum noise fraction transform and is optimal in the sense that it maximizes the signal-to-noise ratio (SNR) in each successive transform component, just as the principal component transform maximizes the data variance in successive components. Application of this transform requires knowledge or an estimate of the noise covariance matrix of the data. The effectiveness of this transform for noise removal is demonstrated in both the spatial and spectral domains. Results that demonstrate the enhancement of geological mapping and detection of alteration mineralogy in data from the Pilbara region of Western Australia, including mapping of the occurrence of pyrophyllite over an extended area, are presented. >

Enhancement of high spectral resolution remote-sensing data by a noise-adjusted principal components transform

Analysis of spectral absorption features in hyperspectral imagery

Use of airborne imaging spectrometer data to map minerals associated with hydrothermally altered rocks in the northern grapevine mountains, Nevada, and California

Improvements in optical remote sensing spectral resolution and increased data volumes necessitates the development of improved techniques for quantitative geological analysis. Laboratory spectral studies indicate that absorption band positions, depths and widths are correlated with diagnostic physicochemical mineral properties such as composition and abundance. Most current analytical techniques are incapable of providing comprehensive quantitative analysis of hyperspectral geological remote sensing data. Factors which must be considered for hyperspectral remote sensing campaigns include spectral resolution, analytical technique, band pass positions and spatial resolution. In many cases the volume of data required to address specific issues can be reduced through intelligent selection of band passes and analytical techniques.

Review Article Hyperspectral geological remote sensing: evaluation of analytical techniques

Expert system-based mineral mapping in northern death valley, California/Nevada, using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

Spectra from airborne systems must be analyzed in terms of their mineral-related absorption features. Methods for removing backgrounds and extracting these features one at a time from reflectance spectra are discussed. Methods for converting radiance spectra into a form similar to reflectance spectra so that the feature extraction procedures can be implemented on aircraft spectrometer data are also discussed.

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M. D. Craig

Papers

Analysis of aircraft spectrometer data with logarithmic residuals