Ground-based hyperspectral imaging as a tool to identify different carbonate phases in natural cliffs

Beckert, Julia; Vandeginste, Veerle; McKean, Tilden J.; Alroichdi, Amer; John, Cedric M.

Abstract

Recent research has shown hyperspectral imaging to be a powerful tool to distinguish carbonate phases with slight compositional differences on quarry cliff faces. The traditional remote sensing set5up uses an optimal short distance between the hyperspectral camera mounted on a tripod and a quarry wall characterized by a planar, mostly unweathered surface. Here we present results of a modified workflow geared to the application of ground5based hyperspectral imaging of rough and weathered cliff faces in order to map large scale dolomite bodies from a distance of up to several kilometres. The goal of the study was to determine unique spectral properties of fracture5controlled dolomite bodies in order to be able to distinguish them from a dolomitic host rock. In addition, the impact of weathering on carbonate phases and thus, the modification of the spectral signature between altered and unaltered carbonates is assessed. The spectral analysis is complemented by ICP5AES measurements of the spectrally measured powders. Furthermore, we examined the detection limits and characterisation potential of dolomite bodies from hyperspectral images captured at varying distances from cliff faces in the study area. Hyperspectral images of 10 natural cliffs distributed across the Central Oman Mountains were obtained with a Push broom scanner system. The high resolution of 5.45 nm (288 bands in total) enabled the visualization of small5scale changes in the near infrared continuous spectrum of all present lithofacies types. The determination of dolomite bodies of varying sizes (metre to hundreds of metres) on natural cliffs was achieved with the hyperspectral mapping approach and mapping results have been tested with the position of visually defined dolomite bodies on field panoramas. Spectra of natural cliffs contain a strong absorption peak indicative for iron which is absent in spectra of unweathered sample powders. However, ICP5AES analysis of powders revealed relatively low contents of iron of 12392 ppm. The strong peaks in field images are interpreted as linked to intensive weathering associated with the precepitation of goethite, hematite, specularite and manganese as well as intensive dedolomitization. Dedolomitization is indicated by calcitic spectra derived from the dolomite bodies. The spectral difference of laboratory and field spectra interferes significantly the application of laboratory spectra of powdered samples for the identification of dolomite bodies in the field. Furthermore, the process of late dedolomitization puts an additional challenge on the determination of dolomite bodies. Due to these strong spectral variations between laboratory and field spectra, we recommend that the mapping approaches should not solely rely on spectral algorithms but also consider normal light field panoramas and representative outcrop analysis. We also note that the quality of resolution is too low for the determination of small5scale variations of diagenetic phases at distances larger than 4 km. However, when the limitations mentioned are taken into account, hyperspectral imaging proves to be a powerful tool that helps in the determination of the distribution of diagenetic phases, even in challenging conditions.

Citation

Beckert, J., Vandeginste, V., McKean, T. J., Alroichdi, A., & John, C. M. (in press). Ground-based hyperspectral imaging as a tool to identify different carbonate phases in natural cliffs. International Journal of Remote Sensing, 39(12), https://doi.org/10.1080/01431161.2018.1452068

• Journal Article Type: Article
• Acceptance Date: Dec 2, 2017
• Online Publication Date: Mar 23, 2018
• Deposit Date: Jan 8, 2018
• Publicly Available Date: Mar 24, 2019
• Journal: International Journal of Remote Sensing
• Print ISSN: 0143-1161
• Electronic ISSN: 0143-1161
• Publisher: Taylor & Francis Open
• Peer Reviewed: Peer Reviewed
• Volume: 39
• Issue: 12
• DOI: https://doi.org/10.1080/01431161.2018.1452068
• Public URL: https://nottingham-repository.worktribe.com/output/921372
• Publisher URL: https://www.tandfonline.com/doi/abs/10.1080/01431161.2018.1452068
• Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Remote Sensing on 23 March 2018, available online: http://www.tandfonline.com/10.1080/01431161.2018.1452068