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Remote Sens. 2016, 8(1), 79; doi:10.3390/rs8010079

Improved VIIRS and MODIS SST Imagery

1
City College of New York, NOAA/CREST, 138th St, New York, NY 10031, USA
2
Global Science and Technology, Inc., Greenbelt, MD 20770, USA
3
NOAA STAR, NCWCP, 5830 University Research Court, College Park, MD 20740, USA
4
Graduate Center, City University of New York, 365 Fifth Avenue, New York, NY 10016, USA
5
NOAA STAR, Regional and Mesoscale Meteorology Branch (RAMMB), Fort Collins, CO 80523, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Changyong Cao, Dongdong Wang and Prasad S. Thenkabail
Received: 4 November 2015 / Revised: 6 January 2016 / Accepted: 11 January 2016 / Published: 21 January 2016
(This article belongs to the Collection Visible Infrared Imaging Radiometers and Applications)
View Full-Text   |   Download PDF [5082 KB, uploaded 21 January 2016]   |  

Abstract

Moderate Resolution Imaging Spectroradiometers (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) radiometers, flown onboard Terra/Aqua and Suomi National Polar-orbiting Partnership (S-NPP)/Joint Polar Satellite System (JPSS) satellites, are capable of providing superior sea surface temperature (SST) imagery. However, the swath data of these multi-detector sensors are subject to several artifacts including bow-tie distortions and striping, and require special pre-processing steps. VIIRS additionally does two irreversible data reduction steps onboard: pixel aggregation (to reduce resolution changes across the swath) and pixel deletion, which complicate both bow-tie correction and destriping. While destriping was addressed elsewhere, this paper describes an algorithm, adopted in the National Oceanic and Atmospheric Administration (NOAA) Advanced Clear-Sky Processor for Oceans (ACSPO) SST system, to minimize the bow-tie artifacts in the SST imagery and facilitate application of the pattern recognition algorithms for improved separation of ocean from cloud and mapping fine SST structure, especially in the dynamic, coastal and high-latitude regions of the ocean. The algorithm is based on a computationally fast re-sampling procedure that ensures a continuity of corresponding latitude and longitude arrays. Potentially, Level 1.5 products may be generated to benefit a wide range of MODIS and VIIRS users in land, ocean, cryosphere, and atmosphere remote sensing. View Full-Text
Keywords: VIIRS; MODIS; imagery; bow-tie; aggregation; deletion; SST VIIRS; MODIS; imagery; bow-tie; aggregation; deletion; SST
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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

Gladkova, I.; Ignatov, A.; Shahriar, F.; Kihai, Y.; Hillger, D.; Petrenko, B. Improved VIIRS and MODIS SST Imagery. Remote Sens. 2016, 8, 79.

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