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Article

A New Approach to Defining Uncertainties for MODIS Land Surface Temperature

1
National Centre for Earth Observation (NCEO), Department of Physics & Astronomy, University of Leicester, University Road, Leicester LE1 7RH, UK
2
Earth Observation Science, Department of Physics & Astronomy, University of Leicester, University Road, Leicester LE1 7RH, UK
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(9), 1021; https://doi.org/10.3390/rs11091021
Received: 1 March 2019 / Revised: 17 April 2019 / Accepted: 25 April 2019 / Published: 30 April 2019
The accuracy of land surface temperature (LST) observations is critical to many applications. Any observation of LST is subject to incomplete knowledge, so an accurate assessment of the uncertainty budget is critical. We present a comprehensive and consistent approach to determining an uncertainty budget for LST products. We apply this approach to the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on-board the Aqua satellite. In order to generate the uncertainty model, a new implementation of the generalised split-window algorithm is applied, in which retrieval coefficients are categorised by viewing angle and water vapour. Validation of the LST against in situ data shows a mean absolute bias of 0.37 K for daytime and 0.73 K for nighttime. The average standard deviation per site is 1.53 K for daytime and 1.21 K for nighttime. Uncertainties from the implemented model are estimates in their own right and are also validated. We do this by comparing the standard deviation of the differences between the satellite and in situ LSTs, and the total uncertainties of the validation matchups. We show that the uncertainty model provides a good fit. Our approach offers a framework for quantifying uncertainties for LST that is equally applicable across different sensors and different retrieval approaches. View Full-Text
Keywords: land surface temperature (LST); consistent uncertainty model; uncertainty validation land surface temperature (LST); consistent uncertainty model; uncertainty validation
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MDPI and ACS Style

Ghent, D.; Veal, K.; Trent, T.; Dodd, E.; Sembhi, H.; Remedios, J. A New Approach to Defining Uncertainties for MODIS Land Surface Temperature. Remote Sens. 2019, 11, 1021. https://doi.org/10.3390/rs11091021

AMA Style

Ghent D, Veal K, Trent T, Dodd E, Sembhi H, Remedios J. A New Approach to Defining Uncertainties for MODIS Land Surface Temperature. Remote Sensing. 2019; 11(9):1021. https://doi.org/10.3390/rs11091021

Chicago/Turabian Style

Ghent, Darren, Karen Veal, Tim Trent, Emma Dodd, Harjinder Sembhi, and John Remedios. 2019. "A New Approach to Defining Uncertainties for MODIS Land Surface Temperature" Remote Sensing 11, no. 9: 1021. https://doi.org/10.3390/rs11091021

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