Identification of materials based on spectral reflectance is confounded by variations in reflectance magnitude that are independent of the spectral shape. Local variations such as viewing/illumination angles, multiscale soil surface roughness that causes shadows and redistributes light, and soil moisture content, all drive changes in magnitude that are distinct from the spectral variations, and complicate identification and modeling of targets based on spectral features. Normalization metrics that remove magnitude variations can greatly clarify the nature of spectral differences, simplifying interpretation of reflectance features in spectral imagery. Normalized difference measures are particularly useful because of the simplicity of the computation, the convenient scaling, and the ease with which the normalized difference procedure can be extended to multiple dimensions. The twodimensional normalized difference space described here allows for improved discrimination among bare soils and emergent vegetation when there are multiple soil types in the scene. A 2-D model of soil-specific change in vegetation density is presented. An application of the vector index to mineral identification and mapping is also presented, with an emphasis on band selection.
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