Skip to main content
Skip table of contents



Material Identification and Classification Algorithm Expert System based on publicly available USGS PRISM MICA expert system for material classification.



Group similar types of minerals with a predefined name and color

  • Default mineral group

  • Generalized mineral group

  • None


Select up to 5 MICA mcf files


In button-up applied order ⬆️ , meaning UV is applied first then Center and so on.

  • Savitzky-Golay

  • Derivative

  • SNV (Standard Normal Variate)

  • Logarithm

  • Center

  • UV (Unit Variance) scaling

For more on each type of pretreatment see: Pretreatments


Minimum score value required for classification of a specific class

Rule images

Calculates each pixel based on each class and see how well they compare to each other. The lower the value the more accurate the pixel spectra are to the class spectrum from the MICA file.

✅ Apply the rule images to all the classes in the library.

⬜ Rule images are not applied.

Show majority class

Show majority class category in table

Save all statistics

Default saving fit value. With all statistics depth and weighted fit depth will also be saved in measurement prediction file


Smooth prediction result using median filter kernel

  • None

    • No Smoothing prediction.

  • Low

    • Smoothing using median filter kernel with 5x5 pixel box

  • Medium

    • Smoothing using median filter kernel with 10x10 pixel box

  • High

    • Smoothing using median filter kernel with 15x15 pixel box


  • Type

    • Depicts the classified pixels in the table view.

  • Depth

    • Depicts how certain the model is in its classification. Values are between (0 - 1).


  • Clark, R. N. (1995). Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice and snow, and other materials: The USGS tricorder algorithm. Clark, Roger N. SwaySummaries of the Fifth Annual JPL Airborne Earth Science Workshop. Volume 1: AVIRIS Workshopze, Gregg A., 39–40.

  • Clark, R. N. (2003). Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems. Journal of Geophysical Research, 108(E12), 5131.

  • Kokaly, R. F. (2011). PRISM: Processing Routines in IDL for Spectroscopic Measurements (Installation Manual and User’s Guide, Version 1.0=. In U.S. Geological Survey Open-File Report 2011-1155.

  • Kokaly, R. F., King, T. V. V., & Hoefen, T. M. (2011). Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA). International Geoscience and Remote Sensing Symposium (IGARSS).

  •, & Kokaly, R. F. (2014). USGS PRISM

  • Swayze, G. A., Clark, R. N., Goetz, A. F. H., Chrien, T. G., & Gorelick, N. S. (2003). Effects of spectrometer band pass, sampling, and signal‐to‐noise ratio on spectral identification using the Tetracorder algorithm. Journal of Geophysical Research, 108(E9), 5105.

JavaScript errors detected

Please note, these errors can depend on your browser setup.

If this problem persists, please contact our support.