Inferring sandstone grain size using spectral datasets: An example from the Bresnahan Group, Western Australia

Ashley L. Uren, Carsten Laukamp, Annette D. George, Sandra A. Occhipinti, Alan R.A. Aitken

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6 Citations (Scopus)


Remotely sensed hyperspectral datasets were integrated with petrographic data to map the distribution of sedimentary rocks in order to infer grain size variations within the siliciclastic, Paleoproterozoic Bresnahan Group in Western Australia. Finer sandstones have greater compositional variation compared to coarser sandstones, with higher modal proportions of mudstone intraclasts, K-feldspar, and muscovite laths, and lower modal quartz. Partial Least Squares modelling indicates a link between visible to shortwave infrared spectral data collected on samples and their average grain size. Specific electronic absorptions are important for defining this relationship, particularly in the blue-green visible spectra, wavelengths related to water or hydroxyl bonds, along with certain wavelengths in the shortwave infrared (SWIR) spectra. The results from field samples were compared to airborne hyperspectral datasets which showed broad scale regional variations in composition could be discerned from processed white mica abundance maps and images that use spectral bands 2350 nm and 2200 nm. The remotely sensed compositional variations are relatable to changes in sandstone grain size. Diagenetic alteration and surface weathering may influence the absorption spectra, although the effect of the latter can be reduced by using processed white mica abundance maps. Overall, the results show that airborne hyperspectral datasets, particularly the SWIR part of the spectra, can be useful to remotely map spatial compositional variations associated with sandstone grain size. This shows the method can be used to remotely map siliciclastic successions in other sedimentary basins by aiding recognition of grain size trends and significant stratal surfaces associated with changes in composition. However, the important wavelengths may differ due to other controls on sandstone composition such as uplift history of the source region, changes in sediment dispersal, and transport mechanisms.

Original languageEnglish
Article number112109
JournalRemote Sensing of Environment
Publication statusPublished - Jan 2021


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