Next Article in Journal
Radiometric Resolution Analysis and a Simulation Model
Next Article in Special Issue
Assessment of S-NPP VIIRS On-Orbit Radiometric Calibration and Performance
Previous Article in Journal
Multispectral Radiometric Analysis of Façades to Detect Pathologies from Active and Passive Remote Sensing
Previous Article in Special Issue
Fast and Accurate Collocation of the Visible Infrared Imaging Radiometer Suite Measurements with Cross-Track Infrared Sounder
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Remote Sens. 2016, 8(1), 79;

Improved VIIRS and MODIS SST Imagery

City College of New York, NOAA/CREST, 138th St, New York, NY 10031, USA
Global Science and Technology, Inc., Greenbelt, MD 20770, USA
NOAA STAR, NCWCP, 5830 University Research Court, College Park, MD 20740, USA
Graduate Center, City University of New York, 365 Fifth Avenue, New York, NY 10016, USA
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)
Full-Text   |   PDF [5082 KB, uploaded 21 January 2016]   |  


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

Figure 1

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).

Share & Cite This Article

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.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top