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

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 produ...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2016-12, Vol.16 (12), p.2075-2075
Main Authors: Zeng, Chen, Xu, Huiping, Fischer, Andrew M
Format: Article
Language:English
Subjects:
Abundance
Algorithms
Antarctic Regions
Chlorophyll
Chlorophyll - analysis
chlorophyll-a estimation
Chlorophylls
Clouds
Computer Simulation
High resolution
Light
MODIS
Ocean color
Oceans and Seas
Optical Phenomena
Peninsulas
Phytoplankton
Reflectance
Reflectivity
Remote Sensing Technology
Satellites
skylight downwelling radiance
VIIRS
Water - chemistry
water leaving reflectance
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Summary: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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s16122075