The Use of Mid-Infrared Spectroscopy in Remote Sensing of Space Targets

Logan, Lloyd M.; Hunt, Graham R.; Salisbury, John W.

doi:10.1016/b978-0-12-399950-4.50010-0

Cited by 16 publications

(16 citation statements)

References 17 publications

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“…The strong feature centered at 12.5 tzm agrees with the reflectivity of the SiC single crystal and with the emissivity of Globar [Silverman, 1948]. The decrease of spectral contrast with decreasing grain size diameter is a well-known effect [Logan et al, 1974] in a region where surface scattering dominates. The situation in the short-wavelength region is puzzling, and the result is rather disappointing.…”

Section: Stability and Reproducibility For Calibration Use; (2) Represupporting

confidence: 62%

Spectral properties of land surfaces in the thermal infrared: 1. Laboratory measurements of absolute spectral emissivity signatures

Nerry¹,

Labed²,

Stoll³

1990

J. Geophys. Res.

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A laboratory procedure to obtain absolute spectral emissivity signatures of soils in the thermal infrared is developed and discussed. Particular attention is given to correction for environmental radiation and to the estimation of the final accuracy attainable. The study covers the [3.0–5.5] μm and the [8.0–13.5] μm bands with a spectral resolution of 2.5% of λ. The method does not require any a priori assumption on the physical parameters, nor does it require any direct temperature measurement. Absolute emissivity signature ελ can be measured within ±0.6%. Bidirectional reflectivity signatures, ρbλ(0, 0), are obtained as well, against a reflectivity standard: a flame‐sprayed aluminum diffusor. It is spectrally flat and has been calibrated. SiC powder, SiO2 sand, a number of soil samples, montmorillonite, and kaolinite have been measured. Good correlation is found between ελ and ρbλ(0, 0) as to the spectral information involved. An attempt to calculate the form factor Fλ(0) from the emissivity and reflectivity signatures is made. Fλ(0) is related to the bidirectional reflectivity. The accuracy, however, is poor. No spectral information can be inferred from the data. Agricultural soils have very similar signatures in the [8.0–13.5] μm band, dominated by the SiO2 content. Above 10 μm, ελ is rather flat and of the order of 0.97±0.01. Emissivity of clays is very flat and high above 8 μm. In the [3.0–5.5] μm band, emissivity ratios can be large. Characteristic spectral features can be resolved (CaCO3). Thus simultaneous use of both thermal infrared atmospheric windows would certainly improve the interpretation of remotely sensed data.

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Section: Stability and Reproducibility For Calibration Use; (2) Represupporting

confidence: 62%

Spectral properties of land surfaces in the thermal infrared: 1. Laboratory measurements of absolute spectral emissivity signatures

Nerry¹,

Labed²,

Stoll³

1990

J. Geophys. Res.

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“…Differences are observed between transmittance spectra peak positions and reflectance/emission spectra peak positions because transmittance spectra depend only on the absorption properties, whereas reflectance and emission spectra are a function of both the real, n, and imaginary, k, indices of refraction (e.g., Logan et al 1975;Hapke 1981;McMillan and Hofmeister 1988). Reflectance and emission spectra in the mid-IR region are dominated by surface scattering for coarse-grained materials or surfaces resulting in strong reststrahlen bands and by volume scattering for fine particles resulting in weaker reststrahlen bands and strong transparency features (Salisbury and Wald 1992;Mustard and Hays 1997;Lane 1999;Bishop et al 2004).…”

Section: Discussion ν 3 Vibrationsmentioning

confidence: 98%

“…Two blackbody targets (at ~70 and 100 °C) were measured to determine the instrument response function and instrument temperature used for data calibration. The emission spectra of the minerals were obtained by reducing the raw wavelength and temperature-dependent data according to the one-temperature procedure of Ruff et al (1997), assuming that sample emission equals unity at the Christiansen feature (e.g., Logan et al 1975;Salisbury 1993). …”

Section: Measurement Of Emission Spectramentioning

confidence: 99%

Spectral properties of Ca-sulfates: Gypsum, bassanite, and anhydrite

Bishop

Lane

Dyar

et al. 2014

American Mineralogist

130

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This study of the spectral properties of Ca-sulfates was initiated to support remote detection of these minerals on Mars. Gypsum, bassanite, and anhydrite are the currently known forms of Ca-sulfates. They are typically found in sedimentary evaporites on Earth, but can also form via reaction of acidic fluids associated with volcanic activity. Reflectance, emission, transmittance, and Raman spectra are discussed here for various sample forms. Gypsum and bassanite spectra exhibit characteristic and distinct triplet bands near 1.4-1.5 μm, a strong band near 1.93-1.94 μm, and multiple features near 2.1-2.3 μm attributed to H 2 O. Anhydrite, bassanite, and gypsum all have SO 4 combination and overtone features from 4.2-5 μm that are present in reflectance spectra. The mid-IR region spectra exhibit strong SO 4 ν 3 and ν 4 vibrational bands near 1150-1200 and 600-680 cm -1 (~8.5 and 16 μm), respectively. Additional weaker features are observed near 1005-1015 cm -1 (~10 μm) for ν 1 and near 470-510 cm -1 (~20 μm) for ν 2 . The mid-IR H 2 O bending vibration occurs near 1623-1630 cm -1 (~6.2 μm). The visible/near-infrared region spectra are brighter for the finer-grained samples. In reflectance and emission spectra of the mid-IR region the ν 4 bands begin to invert for the finer-grained samples, and the ν 1 vibration occurs as a band instead of a peak and has the strongest intensity for the finer-grained samples. The ν 2 vibration is a sharp band for anhydrite and a broad peak for gypsum. The band center of the ν 1 vibration follows a trend of decreasing frequency (increasing wavelength) with increasing hydration of the sample in the transmittance, Raman, and reflectance spectra. Anhydrite forms at elevated temperatures compared to gypsum, and at lower temperature, salt concentration, and pH than bassanite. The relative humidity controls whether bassanite or gypsum is stable. Thus, distinguishing among gypsum, bassanite, and anhydrite via remote sensing can provide constraints on the geochemical environment.

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“…In conjunction with instrument development, considerable effort has been expended in collecting spectral data in the laboratory [Lyon, 1964;Logan et al, 1975;Lyon and Green, 1975] and in developing models in order to apply these data in remote sensing. attempted to correlate the position of the minimum emittance in reststrahlen spectra directly with silica content but noted that SiO 2 is a poor indicator of rock composition.…”

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confidence: 99%

Spectral characterization of igneous rocks in the 8‐ to 12‐μm region

Walter¹,

Salisbury²

1989

J. Geophys. Res.

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107

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Variation in the spectral response of silicates in the thermal infrared (TIR) from 8 to 12 μm is the foundation for potentially important applications in the lithologic characterization of terrestrial and extraterrestrial surfaces. The purpose of this study is to elucidate the crystallo‐chemical basis for the variation in spectral behavior in terms which may be useful in remote sensing. This has led to the definition of a new parameter, SCFM, which is defined as the ratio SiO2/(SiO2 + CaO + FeO + MgO) in minerals and rocks. This parameter reflects the degree of depolymerization of the silica tetrahedra and is therefore highly correlated with the structure of TIR reflectance spectra of major silicate minerals in both fine‐ and coarse‐grained igneous rocks. It is also a good numerical descriptor of igneous rock composition. Thus SCFM is proposed as a very useful determinant for spectral identification of igneous rocks. The SCFM parameter was used to assess the effect of variations in location, number, and width of bands in discriminating rock composition. (An unfortunate ambiguity exists in the use of the term “band” which in spectroscopy indicates a feature in a spectrum and in remote sensing signifies a specific wavelength increment or channel. The latter definition is used in this paper.) Spectra of coarse‐particulate mineral and solid rock samples were acquired in the laboratory. A regression analysis of bands varying in width from 0.2 to 1.4 μm versus SCFM results in coefficients of determination (correlation coefficients), R2, ranging from 0.88 (for two 1.2‐μm‐wide bands) to 0.97 (for seven 0.2‐μm‐wide bands). Deletion of bands in the ozone absorption region (9.4–10.2 μm) results in a decrease in R2 by only 0.01. Stimulation of system noise by addition of ±5% random counts to the bands decreases R2 by only 0.03. Because spectra structure is modified by weathering, alteration, and texture of the samples, the validity of these results is limited to fresh igneous rocks. With this constraint, it is concluded that accurate spectral identification of igneous rock composition is not greatly affected by bandwidth or system noise. It is the overall spectral envelope rather than the fine structure in the TIR which contains most of the information diagnostic of igneous rock composition. This permits design of remote sensing systems with broad bands and corresponding higher signal‐to‐noise, which can be traded off against the important requirement for higher spatial resolution.

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The Use of Mid-Infrared Spectroscopy in Remote Sensing of Space Targets

Cited by 16 publications

References 17 publications

Spectral properties of land surfaces in the thermal infrared: 1. Laboratory measurements of absolute spectral emissivity signatures

Spectral properties of land surfaces in the thermal infrared: 1. Laboratory measurements of absolute spectral emissivity signatures

Spectral properties of Ca-sulfates: Gypsum, bassanite, and anhydrite

Spectral characterization of igneous rocks in the 8‐ to 12‐μm region

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