A comparison of techniques for extracting emissivity information from thermal infrared data for geologic studies

Hook, Simon J.; Gabell, A. R.; Green, A. A.; Kealy, Peter Sean

doi:10.1016/0034-4257(92)90096-3

Cited by 223 publications

(101 citation statements)

References 12 publications

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“…It acquires day and night multi-spectral infrared images at 100 meters per pixel spatial resolution, and one-band visible images at 18 meters per pixel (Christensen et al, 2004). Infrared imagery allows physical surface characteristics to be better distinguished than images taken at visible light wavelengths (Hook, Gabell, Green, & Kealy, 1992;Kahle, Gillespie, & Goetz, 1976;Watson, 1975). THEMIS has an extensive coverage of Mars, which is almost complete in the infrared (≈96% for daytime and ≈82% nighttime coverage, Figure 2).…”

Section: Thermal Emision Imaging System (Themis)mentioning

confidence: 99%

Geology of the Ariadnes Basin, NE Eridania quadrangle, Mars – 1:1Million

Molina¹,

Pablo²,

Hauber³

et al. 2014

Journal of Maps

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Here we present a 1:1,000,000 geological map of the Ariadnes basin (31 -388 S, 170-1798 E) (Mars), which is one of the topographic depressions located between Terra Sirenum and Terra Cimmeria in the Martian highlands. This basin is diverse, both in terms of morphology and mineralogy, and it is a site of major interest to study the chronological boundary between the Noachian and Hesperian periods ( 3.71 Ga). However, a detailed map of the area has not yet been published. The map described in this paper was produced through the analysis of recent images and topographic data that allow the definition of the geologic units with unprecedented detail. We distinguished eight units and diverse tectonic and geomorphic features. We also examined the regional stratigraphy by age determination using crater counting in order to constrain the geological history of the Ariadnes basin. The map provides a basis for which later analyses can build understanding of the regional paleoenvironment.

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Section: Thermal Emision Imaging System (Themis)mentioning

confidence: 99%

Geology of the Ariadnes Basin, NE Eridania quadrangle, Mars – 1:1Million

Molina¹,

Pablo²,

Hauber³

et al. 2014

Journal of Maps

View full text Add to dashboard Cite

show abstract

“…The visible through SWIR bands (1-25) were processed to surface reflectance, the MIR bands (26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40) were not atmospherically corrected and the thermal bands (41)(42)(43)(44)(45)(46)(47)(48)(49)(50) were atmospherically corrected to surface radiance. The surface radiance of the thermal bands was then separated into surface temperature (T s ) and surface emissivity ( ) using the emissivity normalization method [54]. is defined as the ratio of the actual emitted radiance to the radiance emitted from a blackbody at the same thermodynamic temperature [55,56].…”

Section: Master Imagery and Preprocessingmentioning

confidence: 99%

Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data

2011

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Abstract:Wildland fires are a yearly recurring phenomenon in many terrestrial ecosystems. Accurate fire severity estimates are of paramount importance for modeling fire-induced trace gas emissions and rehabilitating post-fire landscapes. We used high spatial and high spectral resolution MODIS/ASTER (MASTER) airborne simulator data acquired over four 2007 southern California burns to evaluate the effectiveness of 19 different spectral indices, including the widely used Normalized Burn Ratio (NBR), for assessing fire severity in southern California chaparral. Ordinal logistic regression was used to assess the goodness-of-fit between the spectral index values and ordinal field data of severity. The NBR and three indices in which the NBR is enhanced with surface temperature or emissivity data revealed the best performance. Our findings support the operational use of the NBR in chaparral ecosystems by Burned Area Emergency Rehabilitation (BAER) projects, and demonstrate the potential of combining optical and thermal data for assessing fire severity. Additional testing in more burns, other ecoregions and different vegetation types is required to fully understand how (thermally enhanced) spectral indices relate to fire severity.

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“…The algorithms to separate temperature and emissivity are generally complex and problematic because of the nonlinearity in the relative contributions of temperature and emissivity effects [12][13][14]. The extracted emissivity products have a relatively high uncertainty and low contrast, which may subdue spectral features and limit the discrimination accuracy [15,16]. A rock index is generally sensitive to a specific rock or mineral and is not enough to identify other rocks [4,6].…”

Section: Introductionmentioning

confidence: 99%

Integrating Textural and Spectral Features to Classify Silicate-Bearing Rocks Using Landsat 8 Data

2016

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Abstract:Texture as a measure of spatial features has been useful as supplementary information to improve image classification in many areas of research fields. This study focuses on assessing the ability of different textural vectors and their combinations to aid spectral features in the classification of silicate rocks. Texture images were calculated from Landsat 8 imagery using a fractal dimension method. Different combinations of texture images, fused with all seven spectral bands, were examined using the Jeffries-Matusita (J-M) distance to select the optimal input feature vectors for image classification. Then, a support vector machine (SVM) fusing textural and spectral features was applied for image classification. The results showed that the fused SVM classifier achieved an overall classification accuracy of 83.73%. Compared to the conventional classification method, which is based only on spectral features, the accuracy achieved by the fused SVM classifier is noticeably improved, especially for granite and quartzose rock, which shows an increase of 38.84% and 7.03%, respectively. We conclude that the integration of textural and spectral features is promising for lithological classification when an appropriate method is selected to derive texture images and an effective technique is applied to select the optimal feature vectors for image classification.

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A comparison of techniques for extracting emissivity information from thermal infrared data for geologic studies

Cited by 223 publications

References 12 publications

Geology of the Ariadnes Basin, NE Eridania quadrangle, Mars – 1:1Million

Geology of the Ariadnes Basin, NE Eridania quadrangle, Mars – 1:1Million

Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data

Integrating Textural and Spectral Features to Classify Silicate-Bearing Rocks Using Landsat 8 Data

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