Tetracorder is the software tool we use to create the maps of materials, many of which are shown on this site. Tetracorder has evolved rapidly since the original concept in 1990. Tetracorder is now an "expert system of algorithms," where an algorithm can be applied to a problem, and the result evaluated and subsequent action taken through an expert system decision methodology to analyze spectra to identify components in the spectrum.
A detailed description of the Tetracorder system and its capabilities:
Clark, R. N., G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J.
Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, Imaging
spectroscopy: Earth and planetary remote sensing with the USGS
Tetracorder and expert systems, J. Geophys. Res.,
108(E12), 5131, doi:10.1029/2002JE001847, December, 2003.
Tetracorder was originally named Tricorder after the devices used on the science fiction series Star Trek. However, the name Tricorder is owned by Paramount Pictures and for over a year we have requested to formally use the name, but Paramount denied permission. The term Tetracorder implies more than a "Tricorder." After all, the Star Trek sensors never produced the spatial maps we are routinely producing today. Thus, in some ways, we have surpassed science fiction future! Fact can be more interesting than fiction.
As we have evolved Tetracorder today, we use it to identify conditions in a spectrum, as found by certain algorithms, and then based on the results, apply other algorithms. In analyzing imaging spectroscopy data sets, we have found many tens of "things" in a single scene, and believe hundreds can be found. By things, we mean minerals, water, snow, vegetation (and different vegetation types), pollution, human-made objects, etc. Because of so many different spectral signatures in a single scene, we favor, at least as first step, a spectral identification algorithm. We developed a very robust spectral feature identification algorithm in 1990:
Using this feature matching algorithm, the analysis was expanded in 1991 to analyze multiple features at one time for each unknown spectrum:
The fitting does an individual fit of each spectral feature in the spectral library to the spectrum undergoing analysis. The individual fits and band depths are are weighted by the area between each absorption feature and its continuum. The weighted fits and depths are summed to form a weighted fit and weighted depth. The fit is the correclation coefficient to the least squares routine. Multiple fits are compared and the best fit is selected. Thus the algorithm is choosing: does the spectrum being analyzed have absorption bands from material A, B, C, or ...? The choice is made on best fit and other criteria, shuch as albedo (e.g. dark magnetite should not have a reflectance of 90%), continuum slope (e.g. hematite UV bands always result in a strong positive slope to the continuum). These and other constraints were added in the newer version of Tetracorder in 1995:
The Tetracorder feature matching algorithm, described in Clark et al., (1990) is available as special function 42 in the SPECPR software. It is 2 subroutines, written in ratfor (they are not complicated and can easily be converted to Fortran or C; most Unix machine come with ratfor, and ratfor is available on the web; ratfor creates fortran as its output). The two subroutines are available here:
Tetracorder spectral feature algorithm, setup subroutine
Tetracorder spectral feature algorithm, main matching subroutine
The Effects of Detector Sampling, Bandpass, and Signal to Noise Ratio on Spectral Identification Using Imaging Spectrometer Data: Evaluation of using the USGS Tricorder Algorithm, by Swayze, G.A, R.N. Clark, R.N., Goetz, A.F., Gorelick, N.S., and Chrien, T.G., J. Geophys Res, 2002. (Status: returned to JGR after reviews.)
Clark, R.N., A.J. Gallagher, and G.A. Swayze, Material Absorption Band Depth Mapping of Imaging Spectrometer Data Using a Complete Band Shape Least-Squares Fit with Library Reference Spectra,\ \ Proceedings of the Second Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Workshop. JPL Publication 90-54, 176-186, 1990.
Clark, R.N., G.A. Swayze, A. Gallagher, N. Gorelick, and F. Kruse, Mapping with Imaging Spectrometer Data Using the Complete Band Shape Least-Squares Algorithm Simultaneously Fit to Multiple Spectral Features from Multiple Materials, Proceedings of the Third Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Workshop, JPL Publication 91-28, 2-3, 1991.
Clark, R.N. and Swayze, G.A., Mapping Minerals, Amorphous Materials, Environmental Materials, Vegetation, Water, Ice and Snow, and Other Materials: The USGS Tricorder Algorithm. Summaries of the Fifth Annual JPL Airborne Earth Science Workshop, January 23- 26, R.O. Green, Ed., JPL Publication 95-1, p. 39-40, 1995.
Phone, email and regular mail addresses of
spectroscopy lab personnel for further information.
U.S. Geological Survey,
a bureau of the U.S. Department of the Interior
This page URL= http://speclab.cr.usgs.gov/tricorder.html
This page is maintained by: Dr. Roger N. Clark firstname.lastname@example.org
Last modified February 17, 2004.