Preliminary on-orbit performance of the Thermal Infrared Sensor (TIRS) on board Landsat 8

Montanaro, Matthew; Tesfaye, Zelalem; Lunsford, Allen; Wenny, Brian N.; Reuter, Dennis C.; Markham, Brian L.; Smith, Ramsey L.; Thome, Kurtis J.

doi:10.1117/12.2025650

Cited by 5 publications

(3 citation statements)

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“…In addition, the standard deviations about the mean bias are significantly higher for Landsat 8, particularly in band 11, even though the instrument signal to noise ratios (SNRs) for Landsat 8 are higher than those for earlier instruments. Since the methodology is identical and the SNR for Landsat 8 is higher, this large variation is likely due to actual changes in the calibration; the correlation of error with scene radiance [19] suggests there is a variable source of calibration error that is not fully accounted for by the combined use of on board [20] and vicarious calibration described here. This residual error has been attributed to a ghosting or stray light problem associated with radiation from outside the detectors nominal point spread function (PSF) impinging on the detector (see Section 6).…”

Section: Landsat 8 Results Using Operational Approachmentioning

confidence: 99%

Development of an Operational Calibration Methodology for the Landsat Thermal Data Archive and Initial Testing of the Atmospheric Compensation Component of a Land Surface Temperature (LST) Product from the Archive

et al. 2014

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Abstract:The Landsat program has been producing an archive of thermal imagery that spans the globe and covers 30 years of the thermal history of the planet at human scales (60-120 m). Most of that archive's absolute radiometric calibration has been fixed through vicarious calibration techniques. These calibration ties to trusted values have often taken a year or more to gather sufficient data and, in some cases, it has been over a decade before calibration certainty has been established. With temperature being such a critical factor for all living systems and the ongoing concern over the impacts of climate change, NASA and the United States Geological Survey (USGS) are leading efforts to provide timely and accurate temperature data from the Landsat thermal data archive. This paper discusses two closely related advances that are critical steps toward providing timely and reliable temperature image maps from Landsat. The first advance involves the development and testing of an autonomous procedure for gathering and performing initial screening of large amounts of vicarious calibration data. The second advance discussed in this paper is the per-pixel atmospheric compensation of the data to permit calculation of the emitted surface radiance (using ancillary sources of emissivity data) and the corresponding land surface temperature (LST).

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Section: Landsat 8 Results Using Operational Approachmentioning

confidence: 99%

Development of an Operational Calibration Methodology for the Landsat Thermal Data Archive and Initial Testing of the Atmospheric Compensation Component of a Land Surface Temperature (LST) Product from the Archive

et al. 2014

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“…The approach is very similar to that developed for the Thermal Infrared Sensor (TIRS) on the Landsat 8 platform which uses an identical ROIC as in SOLARIS. 6 The linearity correction developed for SOLARIS has been shown to be more accurate than that for TIRS, but is still too large for the CLARREO mission. Evaluations are currently underway to determine whether an alternate correction approach can reduce the errors or whether a different electronics design is needed for CLARREO.…”

Section: Sensor Linearitymentioning

confidence: 99%

Demonstrating the error budget for the Climate Absolute Radiance and Refractivity Observatory through solar irradiance measurements

Thome

McCorkel

McAndrew

2015

Earth Observing Systems XX

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The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe highaccuracy, long-term climate change trends and to use decadal change observations as a method to determine the accuracy of climate change. A CLARREO objective is to improve the accuracy of SI-traceable, absolute calibration at infrared and reflected solar wavelengths to reach on-orbit accuracies required to allow climate change observations to survive data gaps and observe climate change at the limit of natural variability. Such an effort will also demonstrate National Institute of Standards and Technology (NIST) approaches for use in future spaceborne instruments.The current work describes the results of laboratory and field measurements with the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. SOLARIS allows testing and evaluation of calibration approaches, alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. Results of laboratory calibration measurements are provided to demonstrate key assumptions about instrument behavior that are needed to achieve CLARREO's climate measurement requirements. Absolute radiometric response is determined using laser-based calibration sources and applied to direct solar views for comparison with accepted solar irradiance models to demonstrate accuracy values giving confidence in the error budget for the CLARREO reflectance retrieval.

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“…However, the magnitude of errors for band 11 are more alarming and we would not be confident in producing a land surface temperature product using this radiance data. However, current studies show that there are actual changes in the Landsat 8 calibration, more prevalent in band 11; it is believed that there is still currently a variable source of calibration error, correlated to scene radiance, that can be attributed to stray light from outside the detectors nominal point spread function impinging on the detector , (Montanaro et al, 2013). Therefore, these results, rather than acting as a reflection of the performance of our current methodology, will be utilized in the continuing calibration work and attempts to solve the stray light problem, and a more in depth analysis of the ability to process Landsat 8 using the current methodology will be revisited after there is more confidence in the calibration and characterization of the Landsat 8 thermal bands.…”

Section: Landsat 8 Mean [K] Sd [K]mentioning

confidence: 99%

The Atmospheric Compensation Component of a Landsat Land Surface Temperature (LST) Product: Assessment of Errors Expected for a North American Test Product

Cook

Schott

2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The Landsat archive of thermal data (Landsats 4, 5 and 7) has gone through a rigorous calibration assessment and update. However, in order to be useful to most users the calibrated sensor reaching radiance must be corrected to surface temperatures by first compensating for atmospheric effects and then emissivity variations. The USGS is exploring the possibility of producing a LST product through a joint program with RIT (the atmospheric compensation component) and JPL (the emissivity compensation component). This paper addresses the atmospheric compensation component for an initial North American pilot study. In particular, the results of a comparison of retrieved water surface temperature (where emissivity is well known) and truth temperatures for over 800 sites are presented. The errors are broken down by cloud conditions with extremely good results for cloud-free conditions (errors less than 1K). The results of the error assessment for North America by cloud class are presented along with a discussion of potential quality data for a LST product. An initial assessment of the LST errors observed for Landsat 8 bands 10 and 11 are also presented. The next steps on this effort include testing of a global atmospheric compensation approach and full integration of the atmospheric and emissivity compensation tools into an operational LST product.

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Preliminary on-orbit performance of the Thermal Infrared Sensor (TIRS) on board Landsat 8

Cited by 5 publications

References 0 publications

Development of an Operational Calibration Methodology for the Landsat Thermal Data Archive and Initial Testing of the Atmospheric Compensation Component of a Land Surface Temperature (LST) Product from the Archive

Development of an Operational Calibration Methodology for the Landsat Thermal Data Archive and Initial Testing of the Atmospheric Compensation Component of a Land Surface Temperature (LST) Product from the Archive

Demonstrating the error budget for the Climate Absolute Radiance and Refractivity Observatory through solar irradiance measurements

The Atmospheric Compensation Component of a Landsat Land Surface Temperature (LST) Product: Assessment of Errors Expected for a North American Test Product

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