Evaluation of hyperspectral remote sensing as a means of environmental monitoring in the St. Austell China clay (kaolin) region, Cornwall, UK [An article from: Remote Sensing of Environment]

This digital document is a journal article from Remote Sensing of Environment, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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The St. Austell granite of Cornwall, UK contains internationally important deposits of kaolin (china clay), the formation of which resulted from the alteration of a composite pluton of mineralogically and texturally different primary granite units. To assess the applicability of hyperspectral remote sensing in the St. Austell china clay region, one line of airborne HyMap(R) hyperspectral data was acquired. These data were processed to correct for atmospheric and illumination effects by calibration from radiance to reflectance data, so that mineral abundance maps could be produced. Minerals associated with the primary granite and its subsequent kaolinisation were identified by image processing and used as mapping endmembers. These minerals include kaolinite, kaolinite with smectite, montmorillonite, muscovite, lepidolite (a lithium mica) and topaz. Hyperspectral data analysis allowed for the identification of the different primary granite units. The spectrally observed compositional differences of the biotite and topaz granite units of the region allowed for fingerprinting of the source of mined waste material as originating from specific pits. The majority of waste tips in the region originate from the nearest china clay workings. However, waste material used in the construction of a mica dam and also as backfill in a disused pit is successfully identified to have been transported across a mapped granite boundary for storage. The effect of mining and mineral processing on the abundance and spatial distribution of minerals in the region is also evident. Waste tips are classified as containing the greatest abundance of mica. This distribution results from the separation of kaolinite during the mineral processing stages. Kaolinite in lower abundance, however, is also identified within these waste areas and is the result of a less than 100% recovery by mining and processing.

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