Inversion of Chromophoric Dissolved Organic Matter From EO-1 Hyperion Imagery for Turbid Estuarine and Coastal Waters

• Published in: IEEE transactions on geoscience and remote sensing Vol. 51; no. 6; pp. 3286 - 3298
• Main Authors: Zhu, Weining, Yu, Qian
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.06.2013; Institute of Electrical and Electronics Engineers
• Subjects: Absorption; Algorithm design and analysis; Applied geophysics; Atmospheric modeling; Chromophoric dissolved organic matter (CDOM); Earth sciences; Earth, ocean, space; EO-1 Hyperion; Exact sciences and technology; Internal geophysics; ocean color; Oceans; quasi-analytical algorithm (QAA); Remote sensing; Rivers; Sea measurements; South America; Queensland Australia; Moreton Bay; United States; Louisiana; Atchafalaya River; Amazon River; Australia; Mississippi River; algorithms; extension; color; biogeochemical cycle; plumes; Australasia; accuracy; North America; ocean color; currents; coastal zone; quasi-analytical algorithm (QAA); imagery; estuaries; calibration; uncertainties; high resolution; sea water; inverse problem; salinity; absorption; Space remote sensing; coastal environment; Chromophoric dissolved organic matter (CDOM); EO-1 Hyperion; water quality; algorithm performance; Hyperion Satellite; organic materials; errors
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2012.2224117

The significant implication of chromophoric dissolved organic matter (CDOM) for water quality and biogeochemical cycle leads to an increasing need of CDOM monitoring in coastal regions. Current ocean-color algorithms are mostly limited to open-sea water and have high uncertainty when directly applied to turbid coastal waters. This paper presents a semianalytical algorithm, quasi-analytical CDOM algorithm (QAA-CDOM), to invert CDOM absorption from Earth Observing-1 (EO-1) Hyperion satellite images. This algorithm was developed from a widely used ocean-color algorithm QAA and our earlier extension of QAA. The main goal is to improve the algorithm performance for a wide range of water conditions, particularly turbid waters in estuarine and coastal regions. The algorithm development, calibration, and validation were based on our intensive high-resolution underwater measurements, International Ocean Color Coordinating Group synthetic data, and global National Aeronautics and Space Administration Bio-Optical Marine Algorithm Data Set data. The result shows that retrieved CDOM absorption achieved accuracy (root mean square error (RMSE) = 0.115 m -1 and R 2 = 0.73) in the Atchafalaya River plume area. QAA-CDOM is also evaluated for scenarios in three additional study sites, namely, the Mississippi River, Amazon River, and Moreton Bay, where ag (440) was in the wide range of 0.01-15 m -1 . It resulted in expected CDOM distribution patterns along the river salinity gradient. This study improves the high-resolution observation of CDOM dynamics in river-dominated coastal margins and other coastal environments for the study of land-ocean interactive processes.