2017
DOI: 10.3390/rs9010072
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Assessment of Mono- and Split-Window Approaches for Time Series Processing of LST from AVHRR—A TIMELINE Round Robin

Abstract: Abstract:Processing of land surface temperature from long time series of AVHRR (Advanced Very High Resolution Radiometer) requires stable algorithms, which are well characterized in terms of accuracy, precision and sensitivity. This assessment presents a comparison of four mono-window (Price 1983, Qin et al., 2001, Jiménez-Muñoz and Sobrino 2003 and six split-window algorithms (Price 1984, Becker and Li 1990, Ulivieri et al., 1994, Wan and Dozier 1996, Yu 2008, Jiménez-Muñoz and Sobrino 2008 to estimate LST fr… Show more

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Cited by 15 publications
(37 citation statements)
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“…This is done for each profile at each measurement height, and seeks to replicate the introduction of uncertainty into the atmospheric profile measurements to study sensitivity in LST retrievals. Contrary to uniformly distributed errors [70] and fixed errors [21] introduced to atmospheric profiles when assessing sensitivity, a normally distributed perturbation provides a behavior commonly found in nature [71].…”
Section: The Role Of Variability In Atmospheric Profilesmentioning
confidence: 99%
“…This is done for each profile at each measurement height, and seeks to replicate the introduction of uncertainty into the atmospheric profile measurements to study sensitivity in LST retrievals. Contrary to uniformly distributed errors [70] and fixed errors [21] introduced to atmospheric profiles when assessing sensitivity, a normally distributed perturbation provides a behavior commonly found in nature [71].…”
Section: The Role Of Variability In Atmospheric Profilesmentioning
confidence: 99%
“…to TOA spectral radiance, the quantization range of the band is used (Qcalmin -Qcalmax) and formula shown in Eq. 1 (Chandar et al, 2003 andFrey et al, 2017 (Sobrino, 2004).…”
Section: Study Areamentioning
confidence: 99%
“…There are different methods to correct for the atmospheric effects in LST derivation from remote sensing data. Radiative Transfer Models correct for the influences of the atmosphere very accurately, but they are very CPU-intensive [4], and require precise atmospheric information. Alternatively, in the field of thermal remote sensing, several algorithms for atmospheric correction have been developed, which are more efficient but not as stable in performance.…”
Section: Introductionmentioning
confidence: 99%