1 January 2011 Examination of spaceborne imaging spectroscopy data utility for stratigraphic and lithologic mapping
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Abstract
Due to the increasing development of image spectroscopy techniques, airborne and spaceborne hyperspectral images have in recent years become readily available for use in geological applications. One of the prominent advantages of imaging spectroscopy is its high spectral resolution, producing detailed spectral information in each pixel. The current study aims at exploring the feasibility of the Earth-Observing-1 Hyperion imaging spectrometer to map the geology arena over the Dana Geology National Park, Jordan. After overcoming the common preprocessing difficulties (e.g., smile effect), a classification scheme of two levels was applied. The first level resulted in a stratigraphic classification product of eleven classes and the second level in a lithologic classification product of six classes. The overall accuracy of the stratigraphic product was 57%, while that of the lithologic product was 79%. Mismatches in classification were mostly related to terrestrial cover of the lower topography formation by rock and sand debris. In addition, low accuracy values can be attributed to Hyperion's high sensitivity, leading to recognition of different mineral compositions as different classes within a rock formation, while the conventional geology-stratigraphic map generalizes these different classes into one formation. The methods practiced in the current research can advance the Hyperion's classification capabilities and therefore can be applied in different geological settings and additional disciplines such as penology, agriculture, ecology, forestry, urban, and other environmental studies.
©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Alon Dadon, Eyal Ben-Dor, Michael Beyth, and Arnon Karnieli "Examination of spaceborne imaging spectroscopy data utility for stratigraphic and lithologic mapping," Journal of Applied Remote Sensing 5(1), 053507 (1 January 2011). https://doi.org/10.1117/1.3553234
Published: 1 January 2011
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CITATIONS
Cited by 14 scholarly publications.
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KEYWORDS
Imaging spectroscopy

Signal to noise ratio

Geology

Minerals

Associative arrays

Reflectivity

Image classification

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