Created by Thomas Ostersen

Hyperspectral data sets measure the intensity of reflected or emitted light across a wide range of the electromagnetic spectrum. In geoscientific applications, these data sets tend to focus on the analysis of geological materials such as rocks and soils. Reflectance spectra obtained from these materials contain subtle features that are sensitive to the presence and composition of various spectrally active mineral phases. 

A significant enabler of spectral geoscience has been the collection and dissemination of spectral libraries. These hyperspectral data collections include analyses of ‘pure’ minerals, which provide valuable reference spectra against which in-the-field measurements can be compared and assessed. Examples of publicly available spectral libraries include the USGS Spectral Library v7 (Kokaly et al. 2017) and the ECOSTRESS spectral library (Meerdink et al. 2019).

We spend a lot of time looking at spectra here at Datarock. Whether its training models to identify subtle alteration signatures or identifying deposits in airborne or satellite hyperspectral imagery, or developing geometallurgical classification and regression pipelines on FTIR spectra at mine sites, we regularly pull up reference spectra in public spectral libraries to check our work. 

This blog post accompanies the release of Datarock’s Spectral Library Viewer web application. Built with shiny-python, the app allows users to search spectral libraries and visualise calibrated spectra in a single interactive plot built with plotly. The search functionality employs ngram to provide some robustness to incorrectly spelled materials, which is very crude, but works. At this stage, only spectra from the USGS library are included, with potential for future updates to include spectra from other libraries. If you’re interested, check out the app here: https://datarock.shinyapps.io/speclib_viewer/. And reach out if you want to know more about Datarock’s approach to hyperspectral modelling.

References

Kokaly, R. F., Clark, R. N., Swayze, G. A., Livo, K. E., Hoefen, T. M., Pearson, N. C., … & Klein, A. J. (2017). Usgs spectral library version 7 data: Us geological survey data release. United States Geological Survey (USGS): Reston, VA, USA, 61.

Meerdink, S. K., Hook, S. J., Roberts, D. A., & Abbott, E. A. (2019). The ECOSTRESS spectral library version 1.0. Remote Sensing of Environment, 230, 111196.