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Automated lithological mapping using airborne hyperspectral thermal infrared data: A case study from Anchorage Island, Antarctica

Black, Martin; Riley, Teal R.; Ferrier, Graham; Fleming, Andrew H.; Fretwell, Peter T.

Authors

Martin Black

Teal R. Riley

Andrew H. Fleming

Peter T. Fretwell



Abstract

The thermal infrared portion of the electromagnetic spectrum has considerable potential for mineral and lithological mapping of the most abundant rock-forming silicates that do not display diagnostic features at visible and shortwave infrared wavelengths. Lithological mapping using visible and shortwave infrared hyperspectral data is well developed and established processing chains are available, however there is a paucity of such methodologies for hyperspectral thermal infrared data. Here we present a new fully automated processing chain for deriving lithological maps from hyperspectral thermal infrared data and test its applicability using the first ever airborne hyperspectral thermal data collected in the Antarctic. A combined airborne hyperspectral survey, targeted geological field mapping campaign and detailed mineralogical and geochemical datasets are applied to small test site in West Antarctica where the geological relationships are representative of continental margin arcs. The challenging environmental conditions and cold temperatures in the Antarctic meant that the data have a significantly lower signal to noise ratio than is usually attained from airborne hyperspectral sensors. We applied preprocessing techniques to improve the signal to noise ratio and convert the radiance images to ground leaving emissivity. Following preprocessing we developed and applied a fully automated processing chain to the hyperspectral imagery, which consists of the following six steps: (1) superpixel segmentation, (2) determine the number of endmembers, (3) extract endmembers from superpixels, (4) apply fully constrained linear unmixing, (5) generate a predictive classification map, and (6) automatically label the predictive classes to generate a lithological map. The results show that the image processing chain was successful, despite the low signal to noise ratio of the imagery; reconstruction of the hyperspectral image from the endmembers and their fractional abundances yielded a root mean square error of 0.58%. The results are encouraging with the thermal imagery allowing clear distinction between granitoid types. However, the distinction of fine grained, intermediate composition dykes is not possible due to the close geochemical similarity with the country rock.

Citation

Black, M., Riley, T. R., Ferrier, G., Fleming, A. H., & Fretwell, P. T. (2016). Automated lithological mapping using airborne hyperspectral thermal infrared data: A case study from Anchorage Island, Antarctica. Remote Sensing of Environment, 176, 225-241. https://doi.org/10.1016/j.rse.2016.01.022

Journal Article Type Article
Acceptance Date Jan 28, 2016
Online Publication Date Feb 11, 2016
Publication Date 2016-04
Deposit Date Feb 26, 2016
Publicly Available Date Feb 26, 2016
Journal Remote sensing of environment
Print ISSN 0034-4257
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 176
Pages 225-241
DOI https://doi.org/10.1016/j.rse.2016.01.022
Keywords Hyperspectral, Thermal infrared, Geology, Automated, Mapping, Antarctica
Public URL https://hull-repository.worktribe.com/output/471719
Publisher URL http://www.sciencedirect.com/science/article/pii/S0034425716300232
Additional Information Authors' accepted manuscript of article published in: Remote sensing of environment, 2016, v.176.
Contract Date Feb 26, 2016

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