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Sensors 2016, 16(12), 2075; doi:10.3390/s16122075

Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance

1
School of Ocean and Earth Science, Tongji University, Shanghai 200092, China
2
Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
3
Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, China
4
Institute for Marine and Antarctic Studies, University of Tasmania, Launceston 7250, Australia
*
Author to whom correspondence should be addressed.
Academic Editors: Assefa M. Melesse, Essayas Kaba Ayana and Gabriel Senay
Received: 8 August 2016 / Revised: 4 November 2016 / Accepted: 21 November 2016 / Published: 7 December 2016
(This article belongs to the Special Issue Sensors and Sensing in Water Quality Assessment and Monitoring)
View Full-Text   |   Download PDF [3391 KB, uploaded 7 December 2016]   |  

Abstract

Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP) on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution), simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS) water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy. View Full-Text
Keywords: water leaving reflectance; skylight downwelling radiance; chlorophyll-a estimation; MODIS; VIIRS water leaving reflectance; skylight downwelling radiance; chlorophyll-a estimation; MODIS; VIIRS
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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

Zeng, C.; Xu, H.; Fischer, A.M. Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance. Sensors 2016, 16, 2075.

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