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.

Publication Date



"Spectral signature databases and their application/misapplication to modeling and exploitation of multispectral/hyperspectral data," Proceedings of SPIE, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, Vol. 5806. The International Society of Optical Engineers. Held in Orlando, Florida: April 2005. This paper is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. Special thanks to the many members (especially the students) of the Digital Image and Remote Sensing laboratory at the Rochester Institute of Technology for the many long hours they have spent making spectral measurements of the same materials, over and over again. It is their willingness to try different things, answer our questions like “what if we did it this way?” and not believe anything they are told without proving it to themselves that let us put this work together. Keep questioning everything - that is how you figure out phenomenology.ISSN:0277-786X Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type


Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


RIT – Main Campus