The Problem:
Monitoring and mapping inland water quality is critical for sustainability of water supplies for human consumption, agriculture, industry, and other economic activities. In previous studies, empirical models have been widely used to map water quality parameters for inland waters using remotely sensed imagery. Due to the complex optical properties of inland waters, empirical models often have limited performances and they cannot be extended or reused across space and time.
The Solution:
Researchers at the University of Alabama have developed a method of utilizing a set of heterogeneous empirical models for different parts of a water body having different characteristics (opposed to single model for all sections). This technology efficiently measures and monitors water quality parameters weekly, seasonally and annually at regional, national and continental scales using satellite and aerial multispectral or hyperspectral imagery.
Chlorophyll Distribution derived from Ensemble Model
Reflectance Spectra of Field Water
Benefits:
·Significantly improved prediction accuracy. (50-100%)
·Spatial extensibility. (regional, national, and continental scales)
·Temporal extensibility. (weekly, seasonal, annual, and decadal)
·Significant reduction of the cost and time for water quality remote sensing.
The University of Alabama Research Office of Innovation and Commercialization (OIC) is a non-profit corporation that is responsible for commercializing University of Alabama technologies and for supporting University research. At OIC, we seek parties that are interested in learning more about our technologies and commercialization opportunities, and we welcome any inquiries you may have.
