Description

Recent publications have shown the capabilities of ESA’s Sentinel-2 multi-spectral imager for geological remote sensing. Where existing sensors such as ASTER are suited for alteration minerals, the bands of Sentinel-2 are particularly of interest for mapping Iron oxides. Iron is an indicator for soil fertility and the usability of an area for cultivating crops, and multi-spectral remote sensing is the only suitable tool for surveying large areas at a high temporal and spatial interval.

The 20x20 meter pixel size means that pixels will contain mixtures of different iron minerals. The proposed research therefore focuses on distinguishing different iron oxides that absorb in the VNIR wavelength region. The study would first make use of hyperspectral sensors to analyze the effect of mixing, and later test the usability of Sentinel-2 spectral bands for the same purpose.

Objectives and Methodology

The following research questions could be considered:
- How does iron oxide speciation influence spectral absorbance features?
- Which iron-bearing minerals can be distinguished in multi-spectral VNIR data?
- How well can we distinguish different iron minerals in 20x20 meter Sentinel-2 data?
- What is the influence of vegetation in the reflectance spectrum of iron oxides?

The topic is both a desktop and laboratory study; the balance between these two can vary depending on your interest. The lab work could consist of creating a controlled set of rock & soil samples, including measuring with laboratory spectrometers, XRD and XRF. The desktop study could include simulation of image data from spectral libraries and testing of various spectral indices for unmixing or separating different iron oxide minerals. The desktop study can be extended to operational Sentinel-2 imagery in Google Earth Engine.

Further reading

- https://doi.org/10.1016/j.rse.2014.03.022
- https://doi.org/10.3390/rs71012635