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Geosciences 2015, 5(4), 334-360; doi:10.3390/geosciences5040334

Evaluation of VIIRS Land Surface Temperature Using CREST-SAFE Air, Snow Surface, and Soil Temperature Data

1
National Oceanic and Atmospheric Administration-Cooperative Remote Sensing Science and Technology (NOAA-CREST) Center, The City College of New York, New York, NY 10031, USA
2
NOAA-Satellite Applications and Research (STAR), 5830 University Research Court, College Park, MD 20740, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Yongwei Sheng
Received: 21 August 2015 / Revised: 27 November 2015 / Accepted: 10 December 2015 / Published: 15 December 2015
(This article belongs to the Special Issue Advances in Remote Sensing and GIS for Geomorphological Mapping)
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Abstract

In this study, the Visible Infrared Imager Radiometer Suite (VIIRS) Land Surface Temperature (LST) Environmental Data Record (EDR) was evaluated against snow surface (T-skin) and near-surface air temperature (T-air) ground observations recorded at the Cooperative Remote Sensing Science and Technology Center—Snow Analysis and Field Experiment (CREST-SAFE), located in Caribou, ME, USA during the winters of 2013 and 2014. The satellite LST corroboration of snow-covered areas is imperative because high-latitude regions are often physically inaccessible and there is a need to complement the data from the existing meteorological station networks. T-skin is not a standard meteorological parameter commonly observed at synoptic stations. Common practice is to measure surface infrared emission from the land surface at research stations across the world that allow for estimating ground-observed LST. Accurate T-skin observations are critical for estimating latent and sensible heat fluxes over snow-covered areas because the incoming and outgoing radiation fluxes from the snow mass and T-air make the snow surface temperature different from the average snowpack temperature. Precise characterization of the LST using satellite observations is an important issue because several climate and hydrological models use T-skin as input. Results indicate that T-air correlates better than T-skin with VIIRS LST data and that the accuracy of nighttime LST retrievals is considerably better than that of daytime. Based on these results, empirical relationships to estimate T-air and T-skin for clear-sky conditions from remotely-sensed (RS) LST were derived. Additionally, an empirical formula to correct cloud-contaminated RS LST was developed. View Full-Text
Keywords: land surface temperature; snow surface temperature; near-surface air temperature land surface temperature; snow surface temperature; near-surface air temperature
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Pérez Díaz, C.L.; Lakhankar, T.; Romanov, P.; Khanbilvardi, R.; Yu, Y. Evaluation of VIIRS Land Surface Temperature Using CREST-SAFE Air, Snow Surface, and Soil Temperature Data. Geosciences 2015, 5, 334-360.

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