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Electrical and
Computer Engineering |
Neural Network-Based Estimation of Chlorophyll-a Concentration in Coastal Waters
Collaborators : University of Maine and NASA Stennis Space Center, MS
Funded By : National Aeronautics and Space
Administration (NASA) and Maine Space Grant Consortium (MSGC)
Contact: Habtom Ressom, Wayne Slade, Jr, Padma Natarajan
Project Summary
The estimation of chlorophyll-a concentration is a useful mechanism in the investigation of dynamic ecological processes. Ocean color remote sensing provides an effective means to model chlorophyll-a concentration using reflectance measurements. However, the presence of dissolved organic matter, detritus, and suspended sediments creates an optically complex situation in coastal regions.This has been a limiting factor to conventional models. Neural networks are known to be very capable at mapping complex nonlinear relationships with no a priori knowledge of the system to be modeled. We plan to investigate the use of neural network models for efficient, accurate and robust estimation of chlorophyll-a concentration from ocean color.
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