NDLI: Quality Assessment of S-NPP VIIRS Land Surface Temperature Product

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Quality Assessment of S-NPP VIIRS Land Surface Temperature Product

Content Provider	MDPI
Author	Liu, Yuling Yu, Yunyue Yu, Peng Göttsche, Frank Trigo, Isabel
Abstract	The VIIRS Land Surface Temperature (LST) Environmental Data Record (EDR) has reached validated (V1 stage) maturity in December 2014. This study compares VIIRS v1 LST with the ground in situ observations and with heritage LST product from MODIS Aqua and AATSR. Comparisons against U.S. SURFRAD ground observations indicate a similar accuracy among VIIRS, MODIS and AATSR LST, in which VIIRS LST presents an overall accuracy of −0.41 K and precision of 2.35 K. The result over arid regions in Africa suggests that VIIRS and MODIS underestimate the LST about 1.57 K and 2.97 K, respectively. The cross comparison indicates an overall close LST estimation between VIIRS and MODIS. In addition, a statistical method is used to quantify the VIIRS LST retrieval uncertainty taking into account the uncertainty from the surface type input. Some issues have been found as follows: (1) Cloud contamination, particularly the cloud detection error over a snow/ice surface, shows significant impacts on LST validation; (2) Performance of the VIIRS LST algorithm is strongly dependent on a correct classification of the surface type; (3) The VIIRS LST quality can be degraded when significant brightness temperature difference between the two split window channels is observed; (4) Surface type dependent algorithm exhibits deficiency in correcting the large emissivity variations within a surface type.
File Size	7106560
Ending Page	12241
Page Count	27
Starting Page	12215
File Format	PDF
e-ISSN	20724292
DOI	10.3390/rs70912215
Journal	Remote Sensing
Issue Number	9
Volume Number	7
Language	English
Publisher Date	2015-09-21
Access Restriction	Open
Subject Keyword	VIIRS LST EDR split window algorithm surface type dependency LST uncertainty
Content Type	Text
Resource Type	Article

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