Quantitative estimation of granitoid composition from thermal infrared multispectral scanner (TIMS) data, Desolation Wilderness, northern Sierra Nevada, California

Sabine, Charles; Realmuto, Vincent J.; Taranik, James V.

doi:10.1029/93jb03127

Cited by 37 publications

(10 citation statements)

References 15 publications

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“…It has long been known that rocks can be distinguished from each other under ideal conditions by their spectral signatures in the thermal emission region of the spectrum (e.g. Lahren et al, 1988;Sabine et al, 1994). Representative spectra of sedimentary, igneous and metamorphic rocks are given in Figure 4.…”

Section: Spectral Signature Of Minerals and Rocksmentioning

confidence: 99%

Application of remote sensing and GIS in mineral resource mapping-An overview

Rajesh

2004

Journal of Mineralogical and Petrological Sciences

110

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Remote sensing, as a direct adjunct to field, lithologic and structural mapping, and more recently, GIS have played an important role in the study of mineralized areas. A review on the application of remote sensing in mineral resource mapping is attempted here. It involves understanding the application of remote sensing in lithologic, structural and alteration mapping. Remote sensing becomes an important tool for locating mineral deposits, in its own right, when the primary and secondary processes of mineralization result in the formation of spectral anomalies. Reconnaissance lithologic mapping is usually the first step of mineral resource mapping. This is complimented with structural mapping, as mineral deposits usually occur along or adjacent to geologic structures, and alteration mapping, as mineral deposits are commonly associated with hydrothermal alteration of the surrounding rocks. In addition to these, understanding the use of hyperspectral remote sensing is crucial as hyperspectral data can help identify and thematically map regions of exploration interest by using the distinct absorption features of most minerals. Finally coming to the exploration stage, GIS forms the perfect tool in integrating and analyzing various georeferenced geoscience data in selecting the best sites of mineral deposits or rather good candidates for further exploration.

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Section: Spectral Signature Of Minerals and Rocksmentioning

confidence: 99%

Application of remote sensing and GIS in mineral resource mapping-An overview

Rajesh

2004

Journal of Mineralogical and Petrological Sciences

110

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“…An additional approach to visual spectral analysis in areas where the wavelength of the minimum of the reststrahlen feature is expected to shift due to known compositional variations would be to fit a Gaussian function to the TIMS alpha residual spectrum and regress the calculated minimum against the chemical composition of field samples. This approach has been developed by Sabine et al [1994]; it would be a logical follow-on to this study in areas where a firm mineralogical basis now exists for separating two units, such as the Precambrian muscovite-rich versus biotite-rich sediments.…”

Section: Discussionmentioning

confidence: 99%

Mapping the Piute Mountains, California, with thermal infrared multispectral scanner (TIMS) images

Hook¹,

Karlstrom²,

Miller³

et al. 1994

J. Geophys. Res.

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Thermal infrared multispectral scanner (TIMS) data were acquired in 1990 over the Piute Mountains, California, to evaluate their usefulness for lithologic mapping in an area of metamorphosed, structurally complex, igneous and sedimentary rocks. The data were calibrated and atmospherically corrected, and emissivity variations in the form of alpha residuals were extracted from which color composite images were made. There was an excellent visual correlation between the units revealed in the color composite image and the lithologic units mapped in the eastern side of the area. It was also possible to correct, improve, and extend the recent map. For example, several areas mapped as granodioritic gneiss had TIMS alpha residual spectra consistent with mafic rocks and were subsequently mapped as amphibolite. The presence of a swarm of mafic dikes, of which only a few had previously been identified, was also revealed. The images also showed color variations in granitoid plutons that correlated with compositional variations previously determined by extensive field and geochemical work. The western Piute Mountains is an area that has proven to be especially difficult to map with field and air photographic methods, due to heterogeneous nature of certain units and various levels of desert varnish. The images permitted the extremely heterogeneous Proterozoic schists, gneisses, and granites to be easily mapped because the small‐scale compositional variability was averaged to the TIMS pixel size (12 m × 12 m square). Areal measurements from the images show that the Proterozoic rocks in the Piute Mountains consist of granitoids (∼50%), biotite gneiss (∼15%), pelitic gneiss (∼15%), quartzite (∼10%), and amphibolite (∼10%). TIMS data can dramatically increase the efficiency and the quality of geologic mapping in well‐exposed heterogeneous areas with minimal vegetation cover where detailed mapping of lithologic contacts by traditional methods is unusually difficult.

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“…These properties, in addition to the broad spectral bands that may not be sufficient to resolve important spectral features, limit accurate classification of surface composition using spectral analysis methods with TIR data (Collins, 1991). Although multispectral TIR scanners cannot compete with their counterpart VNIR and SWIR imaging spectrometers in geological mapping most alteration minerals, emissivity spectra derived from multispectral TIR data do have potential for discriminating many rocks and minerals, especially silicates and oxides (Collins, 1991;Hook et al, 1994;Rowan & Mars, 2003;Sabine et al, 1994). The emissivity spectral features of silicates and oxides relate to Si-O bonding, ion mass, and crystal structure (Farmer, 1974;Karr, 1975;Lazarev, 1972).…”

Section: Introductionmentioning

confidence: 99%

Integrating visible, near-infrared and short-wave infrared hyperspectral and multispectral thermal imagery for geological mapping at Cuprite, Nevada

Chen

Warner

Campagna

2007

Remote Sensing of Environment

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This study investigated the potential value of integrating hyperspectral visible, near-infrared, and short-wave infrared imagery with multispectral thermal data for geological mapping. Two coregistered aerial data sets of Cuprite, Nevada were used: Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral data, and MODIS/ASTER Airborne Simulator (MASTER) multispectral thermal data. Four classification methods were each applied to AVIRIS, MASTER, and a combined set. Confusion matrices were used to assess the classification accuracy. The assessment showed, in terms of kappa coefficient, that most classification methods applied to the combined data achieved a marked improvement compared to the results using either AVIRIS or MASTER thermal infrared (TIR) data alone. Spectral angle mapper (SAM) showed the best overall classification performance. Minimum distance classification had the second best accuracy, followed by spectral feature fitting (SFF) and maximum likelihood classification. The results of the study showed that SFF applied to the combination of AVIRIS with MASTER TIR data are especially valuable for identification of silicified alteration and quartzite, both of which exhibit distinctive features in the TIR region. SAM showed some advantages over SFF in dealing with multispectral TIR data, obtaining higher accuracy in discriminating low albedo volcanic rocks and limestone which do not have unique, distinguishing features in the TIR region.

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Quantitative estimation of granitoid composition from thermal infrared multispectral scanner (TIMS) data, Desolation Wilderness, northern Sierra Nevada, California

Cited by 37 publications

References 15 publications

Application of remote sensing and GIS in mineral resource mapping-An overview

Application of remote sensing and GIS in mineral resource mapping-An overview

Mapping the Piute Mountains, California, with thermal infrared multispectral scanner (TIMS) images

Integrating visible, near-infrared and short-wave infrared hyperspectral and multispectral thermal imagery for geological mapping at Cuprite, Nevada

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