Atmospheric Corrections and Multi-Conditional Algorithm for Multi-Sensor Remote Sensing of Suspended Particulate Matter in Low-to-High Turbidity Levels Coastal Waters

Atmospheric Corrections and Multi-Conditional Algorithm for Multi-Sensor Remote Sensing of Suspended Particulate Matter in Low-to-High Turbidity Levels Coastal Waters

The accurate measurement of suspended particulate matter (SPM) concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM...

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Bibliographic Details
Main Authors: Stéfani Novoa, David Doxaran, Anouck Ody, Quinten Vanhellemont, Virginie Lafon, Bertrand Lubac, Pierre Gernez
Format: Article
Language:English
Published: MDPI AG 2017-01-01
Series:Remote Sensing
Subjects:
remote sensing
suspended particulate matter
coastal waters
river plumes
multi-conditional algorithm
Online Access:http://www.mdpi.com/2072-4292/9/1/61

Internet

http://www.mdpi.com/2072-4292/9/1/61

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