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Remote Sens. 2016, 8(1), 1; doi:10.3390/rs8010001

Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing

1
Centre for Intelligent Sensing, Queen Mary University of London, London, E1 4NS, UK
2
National Oceanic and Atmospheric Administrations, Center for Satellite Applications and Research, College Park, MD 20740, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Xiaofeng Li and Prasad S. Thenkabail
Received: 5 October 2015 / Revised: 21 November 2015 / Accepted: 24 November 2015 / Published: 22 December 2015
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Abstract

Accurate correction of the corrupting effects of the atmosphere and the water’s surface are essential in order to obtain the optical, biological and biogeochemical properties of the water from satellite-based multi- and hyper-spectral sensors. The major challenges now for atmospheric correction are the conditions of turbid coastal and inland waters and areas in which there are strongly-absorbing aerosols. Here, we outline how these issues can be addressed, with a focus on the potential of new sensor technologies and the opportunities for the development of novel algorithms and aerosol models. We review hardware developments, which will provide qualitative and quantitative increases in spectral, spatial, radiometric and temporal data of the Earth, as well as measurements from other sources, such as the Aerosol Robotic Network for Ocean Color (AERONET-OC) stations, bio-optical sensors on Argo (Bio–Argo) floats and polarimeters. We provide an overview of the state of the art in atmospheric correction algorithms, highlight recent advances and discuss the possible potential for hyperspectral data to address the current challenges. View Full-Text
Keywords: atmospheric correction; hyperspectral; multispectral; ocean colour; remote sensing atmospheric correction; hyperspectral; multispectral; ocean colour; remote sensing
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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

Emberton, S.; Chittka, L.; Cavallaro, A.; Wang, M. Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing. Remote Sens. 2016, 8, 1.

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