Digital classification of contact metamorphic rocks in Extremadura, Spain, using Landsat thematic mapper data

Abstract

Landsat Thematic Mapper (TM) images of an extensively cultivated part of Extremadura, Spain, have been used to distinguish soil developed on contact metamorphic rocks in aureoles around late Hercynian granitic plutons from soil formed on stratigraphically equivalent Late Proterozoic slate and metagraywacke that has been regionally metamorphosed to the greenschist facies. Reflectance spectra of contact metamorphic soil have lower reflectance, especially in the 1.6 μm wavelength region, and weaker Al‐OH, Mg‐OH, and [Formula: see text] absorption features than do spectra of the slate‐metagraywacke soil. These spectral differences are attributed to highly absorbing carbonaceous material in the contact metamorphic soil that was subjected to high temperatures during emplacement of the plutons. These spectral reflectance differences are evident in a density‐sliced TM band 5 image, in color‐ratio composite images that incorporate TM 4 : 5, 4 : 3, and 3 : 1 ratios, and in principal‐component composite images. Digital classification of the numerous tilled, vegetation‐free fields was used to map the contact metamorphic soil in an August, 1984, TM scene of the Caceres study area. First, TM 4 : 3 was used to identify these fields. Then ranges of TM 5 and TM 3 : 1 values were determined for selected tilled fields within and outside the contact aureoles. Field evaluation of a classification map based on TM 5 plus TM 3 : 1 shows more extensive aureoles than published geologic maps and few misclassified areas. Similar results were achieved using TM 4 : 5 instead of TM 5. This approach was subsequently used to map two linear zones of contact metamorphic rocks in the San Nicolas mine area where only two small exposures of granite have been documented. Landsat Multispectral Scanner (MSS) images can also be used to map contact aureoles in the study areas, but extensive field evaluation is required because of more frequent misclassification.

Discrimination of sedimentary lithologies using Hyperion and Landsat Thematic Mapper data: a case study at Melville Island, Canadian High Arctic

“…TM data have also been used effectively in mapping igneous and metamorphic rocks (e.g. Rowan et al 1987, Abrams et al 1988, Pontual 1989, Spatz and Taranik 1989, Qari 1992, Mustard 1994, van der Meer et al 1995, Kavak 2005. Notably, the effectiveness of TM data in the discrimination of rock and soil classes is not uniform over all geographic regions, but instead is primarily determined by amounts of exposure and by the spectral distinctiveness of the classes being mapped (e.g.…”

Evaluation of visible and near‐infrared and thermal‐infrared reflectance spectra for studying thermal alteration of Pierre Shale, Wolcott, Colorado

“…The principal mineralogical difference, a higher muscovite content of the soil within the aureoles, does not account for the distinctive reflectance differences. Therefore, Rowan et al [1988] concluded that the differences in reflectance between these soils is related to the differences in thermal maturity of the OM. However, vitrinite reflectance and organic geochemical analyses of a few rock samples were inconclusive because of the very fine dissemination of the kerogen and low total organic carbon content, respectively.…”

“…Our work was motivated initially by the results of an investigation in western Spain where digital classification of a Landsat Thematic Mapper (TM) image was used to map soil derived from contact-metamorphosed slate and metagraywacke within aureoles related to Hercynian plutons [Rowan et al, 1988]. The classification was based on the lower near-infrared reflectance of the soil within the aureoles compared with soil derived from stratigraphically equivalent rocks outside of the aureoles.…”

A Comparison of Different Remotely Sensed Data for Classifying Bedrock Types in Canada’s Arctic: Application of the Robust Classification Method and Random Forests

“…The use of machine learning algorithms, primarily classification, for mapping rocks has been applied mostly in arid environments (Rowan et al 1987;Macias 1995;Glikson and Creasey 1995;El Rakaiby 1995;Van de Meer et al 1995;Rowan et al 2005;Kavak 2005;Peña and Abdelsalam 2006;Saadi and Watanabe 2009;Rajendran et al 2012). A number of examples can also be found for Arctic environments (Leverington 2001(Leverington , 2010Lorenz 2004;Harris et al 2005Harris et al , 2008aHarris et al , c, 2009Harris et al , 2010Wickert et al 2008;Schetselaar and Ryan 2008;Leverington and Moon 2012;Behnia et al 2012).…”