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Inverse estimation of multi‐substance concentrations in coastal surface waters based on a four flux model

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Abstract:

A method based on a four flux model is proposed to accurately estimate multiple-substance concentrations in seawater. Simulations are used to confirm the uniqueness and sensitivity of the solutions of the proposed method when applied to sample water cases in which three selected substances, i.e. phytoplankton, suspended minerals and dissolved organic matter, of various concentrations are combined. The analysis is performed in the visible and near-infrared bands equivalent to Landsat Thematic Mapper (TM) sensor output. The results of inverse estimation using simulated data show that solution uniqueness is maintained within the range of concentration values examined of our target area, i.e. the northern part of Tokyo Bay. We find that the atmospheric noise remaining after atmospheric noise calibration significantly impacts the estimation accuracy. However, if the calibration is reasonably accurate and adequate optical properties are known for each substance, the concentration estimated from both airborne Multi-spectral Scanner (MSS) data and actual Landsat TM data are in good agreement with actual sea truth data for deep areas wherein the reflectance from the sea bottom can be ignored.

Document Type: Research Article

DOI: https://doi.org/10.1080/01431160500117790

Affiliations: 1: NTT Data Corporation, 1‐21‐2 Shinkawa, Chuo‐ku, Tokyo, 104‐0033, Japan 2: Department of Mechanical and Environmental Informatics, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2‐12‐1 O‐okayama, Meguro‐ku, Tokyo, 152‐8552, Japan

Publication date: 2006-01-20

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