Spectral signature databases abound in the field of remote sensing. Scientists use these databases to assist in their analysis everyday. Many decisions are made about hyperspectral data and the observations made with this data based on the assumption that these databases contain “ground truth” representations of the signatures for materials sensed. For the most part, this is true if the team collecting the signatures that populate these databases follow sound practices when collecting this data. The data does, however, represent a very specific picture of the “truth”. Signatures found in databases represent a specific collection configuration or geometry. The source of illumination, whether it is artificial or natural, is in a very specific location as is the sensor used to collect radiance for the derivation of the reflectance signatures. A signature found in the database is useful for only a very specific scenario, one that matches the geometry used during ground truth collection. There are other very significant factors regarding illumination field and scattering properties of the material and reference standards that influence the computed reflectance signature. This work will illustrate some of the dramatic variation that can exist in the reflectance signatures derived for the same material using different techniques. Difference upward of 30% may exist for the same material. These observations are presented so that scientists who look to these databases in the future will consider very carefully the metadata that is presented with the signatures that they use to make sure they are applicable to the phenomenology and collection scenario that they have under study. These observations should also point out that signatures presented without detailed metadata could be very hazardous to use if the outcome of the analysis being performed relies upon the absolute reflectance spectra being known.
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Proceedings of SPIE Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI 5806 (2005) 531-541
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