Using High-Resolution Airborne Data to Evaluate MERIS Atmospheric Correction and Intra-Pixel Variability in Nearshore Turbid Waters

• Published in: Remote sensing (Basel, Switzerland) Vol. 10; no. 2; p. 274
• Main Authors: Larnicol, Morgane, Launeau, Patrick, Gernez, Pierre
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2018
• Subjects: Aerosols; Airborne observation; Algorithms; Atmospheric correction; Coastal waters; Coastal zone; Environmental monitoring; High resolution; Hypercubes; Hyperspectral imaging; Image acquisition; Image resolution; Optical properties; Particulate emissions; Particulate matter; Pixels; Remote sensing; Satellite observation; Satellites; Seawater; Sensors; Spatial discrimination; Spatial resolution; Water monitoring; Water quality; Water quality management
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs10020274

The implementation of accurate atmospheric correction is a prerequisite for satellite observation and water quality monitoring in coastal areas. The potential of the fast-line-of-sight atmospheric analysis of spectral hypercubes (FLAASH) was investigated here for the medium resolution imaging spectrometer (MERIS). As the comparison between discrete field sampling points and macro-scale satellite pixels is subject to spatial biases associated with small-scale spatial patchiness in the turbid and highly dynamic nearshore zone, an alternative approach was proposed here using high spatial resolution (1 m) airborne hyperspectral images as radiometric truthing references. While FLAASH was not optimal for moderately turbid offshore waters (suspended particulate matter (SPM) concentration < 50 g∙m−3), it yields satisfactory results in the 50–1500 g∙m−3 range, where MERIS standard atmospheric correction was subject to significant biases and failures. Due to the significant intra-pixel variability of SPM distribution in highly turbid areas, the acquisition of high resolution airborne images should be considered as a consistent strategy for the validation of medium resolution satellite remote sensing in the spatially heterogeneous and optically diverse nearshore waters.