Objectives

The goal of the proposed research is to explore whether the combination of hyperspectral remote sensing, ground based spectroradiometry, GIS, and water sampling and analysis can simplify and accelerate the protocol for assessing water quality with an acceptable degree of accuracy.  The test areas include lakes in Iowa (inland lakes) and near the east Florida coast in the protected reserve at the Kennedy Space Center (coastal lakes). This project has the following four major components and actions:

Component 1: Ground-based data collection.  

• Collect field-based hyperspectral data by spectroradiometry

• Collect water samples from study areas and conduct in situ and laboratory analyses

Component 2: Hyperspectral remote-sensing imagery. 

• Investigate potential for hyperspectral remote sensing to quantify and assess various water- quality constituents of inland and coastal areas, as determined by the laboratory analyses

• Study seasonal variations in water-quality assessment by remote sensing

• Determine the optimal bands for water-quality monitoring

Component 3: GIS databases and procedures for prediction modeling. 

• Study relationships between hyperspectral data classification and laboratory measurements using geostatistical analyses

• Investigate GIS-based bathymetry and effluent information to aid the development of remote sensing algorithms when comparing spectral data with in situ chemical analysis

• Explore possible differences between coastal and inland waters

• Predict water quality conditions and provide information in a form that is understandable to decision-makers

Component 4: Dissemination of data to end-users. 

• Create a web-based tool for dissemination of models, protocols, and data to stakeholders