Bayesian estimation for land surface temperature retrieval: the nuisance of emissivities

Morgan, J. A.

doi:10.1109/tgrs.2005.845637

Cited by 14 publications

(42 citation statements)

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“…Due to some anomalies reported for emissivity estimations by some researchers [10,14,15], surface emissivity is influenced by local climatic conditions, land cover, seasons e.t.c. We assume that the ≈ so as to accommodate the anomalies majorly influenced via .…”

Section: Theoretical Implication Of the Remote Sensing Techniquesmentioning

confidence: 99%

Thermal Infrared Remote Sensing of Hydrocarbon in Lagos- Southern Nigeria: Application of the Thermographic Model

Emetere¹

2017

GEOMATE

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ABSTRACT:The paper presents a technique for investigating remote sensing imagery to explore hydrocarbon sites, oil traps and spills. This research adopts a model approach to oil exploration against conventional or traditional methods. The model used here is the Environmental Thermographic Model (ETM). Key parameters such as surface emissivity, surface temperature, long wave radiation and geological mapping which constitute the model were used alongside data generated from the Moderate Resolution Imaging Spectro-radiometer (MODIS) in order to identify the location of prospective oil or gas reservoir in Lagos-Southern Nigeria. MODIS data generated over a period of ten years was analyzed. The ETM model and a temperature polynomial expansion scheme (TPES) were used to validate the remote sensing data by using calculated surface emissivity and long wave technique. Two thermal infrared sources were deployed to aid oil field investigations. The consistency of the Landsat 8 OLI and ETM imagery further confirms the reliability of the method in determining the characteristics of the hydrocarbon habitat, as well as the lineaments.

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Section: Theoretical Implication Of the Remote Sensing Techniquesmentioning

confidence: 99%

Thermal Infrared Remote Sensing of Hydrocarbon in Lagos- Southern Nigeria: Application of the Thermographic Model

Emetere¹

2017

GEOMATE

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“…As in [1], two equally cogent observers must relate their descriptions of radiance, and of calibration error, by a Lorentz transformation [8], [9] connecting one (primed) coordinate description moving with velocity v along the observation axis with respect to the other (unprimed) one by…”

Section: Prior Probability For Calibration Error Parametersmentioning

confidence: 99%

“…The treatment of spectral quantities integrated over a passband follows the equivalent discussion in [1]. In practice, (28) will be unaltered for band-integrated radiances.…”

Section: Extended Lst Estimatormentioning

confidence: 99%

“…However, by integrating over ǫ first, it is possible to take advantage of the closed-form result for the LST posterior probability derived in [1]:…”

Section: Extended Lst Estimatormentioning

confidence: 99%

“…While all forms of quantitative exploitation of radiometric data in remote sensing are afflicted to some degree by calibration error effects, this problem may be a special concern for the Bayesian multiband LST algorithm [1]. That is because the Bayesian algorithm iterates on a range of plausible surface temperatures, within which the estimated LST value is obtained as an expected value.…”

Section: Introductionmentioning

confidence: 99%

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A Bayesian Estimator for Linear Calibration Error Effects in Thermal Remote Sensing

Morgan¹

2006

IEEE Geosci. Remote Sensing Lett.

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Abstract-The Bayesian Land Surface Temperature estimator previously developed has been extended to include the effects of imperfectly known gain and offset calibration errors. It is possible to treat both gain and offset as nuisance parameters and, by integrating over an uninformitave range for their magnitudes, eliminate the dependence of surface temperature and emissivity estimates upon the exact calibration error.

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Comparisons of emissivity observations from satellites and the ground at the CRCS Dunhuang Gobi site

Yong

2014

JGR Atmospheres

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Two sets of field-measured hyperspectral resolution infrared (IR) emissivity spectra were taken from the China Radiometric Calibration Sites (CRCS) Dunhuang site in China, with one representing daytime and the other representing nighttime. Comparisons of the two sets show that the daytime emissivity is smaller than the nighttime emissivity in almost the entire spectrum between 7.5 and 14 μm, strong field evidence to support emissivity diurnal variations, which have been reported in previous studies using satellite observations. These emissivities are used as a reference to evaluate three different emissivity products from the same site: the Atmospheric Infrared Sounder (AIRS) operational emissivity products, the Moderate Resolution Imaging Spectroradiometer (MODIS) operational emissivity products, and the University of Wisconsin-Madison Hyperspectral Resolution IR emissivity (UWIREMIS) database. The AIRS emissivity does not agree as well with the field measurements when compared to that from MODIS and the UWIREMIS despite the fact that AIRS is hyperspectral; the likely cause for the disagreement is cloud contamination due to AIRS' large footprint. MODIS has the advantage of high spatial resolution and visible/near-infrared channels to help the cloud mask and is therefore less affected by cloud contamination. The V4.1 MODIS emissivity agrees better with the field measurement than the UWIREMIS, while the V5 does not do as well. The UWIREMIS emissivity, on the other hand, has the advantage of hyperspectral resolution, which makes it more useful for applications. The temporal analysis of the three satellite-based emissivity products is also presented.

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Bayesian estimation for land surface temperature retrieval: the nuisance of emissivities

Cited by 14 publications

References 20 publications

Thermal Infrared Remote Sensing of Hydrocarbon in Lagos- Southern Nigeria: Application of the Thermographic Model

Thermal Infrared Remote Sensing of Hydrocarbon in Lagos- Southern Nigeria: Application of the Thermographic Model

A Bayesian Estimator for Linear Calibration Error Effects in Thermal Remote Sensing

Comparisons of emissivity observations from satellites and the ground at the CRCS Dunhuang Gobi site

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