Water quality monitoring in coastal ocean estuaries and inland lakes is critical for ecosystems and fisheries management and safe drinking water. Remote sensing of water quality parameters has conventionally used data from multispectral sensors (e.g., Aqua-MODIS, Landsat-OLI, Sentinel-3 OLCI, Sentinel-2 MSI) with a limited number of spectral bands. There have been research missions with hyperspectral sensors (e.g., EO-Hyperion, HICO) that have demonstrated that hyperspectral data (bandwidth 10 nm) can capture more detailed information about water surface reflectance and enable the detection of a wide variety of water pollutants. Plankton, Aerosol, Cloud, ocean, Ecosystem (PACE), a new NASA mission, was launched on 8 February 2024. PACE – Ocean Color Instrument (OCI) collects global, hyperspectral observations for water quality monitoring.
This three-part introductory training will provide an overview of past and current hyperspectral sensors. Specifically, the training will provide information on NASA’s PACE mission, its sensors and data products, webtools to access data, and software for processing hyperspectral data and water quality parameters derived from PACE/OCI. The training will also highlight some advantages and limitations of PACE data. This will be the first ARSET training focusing on the use of hyperspectral data for water quality applications.
Agenda
Prerequisites:
Fundamentals of Remote Sensing
Monitoring Coastal and Estuarine Water Quality: Transitioning from MODIS to VIIRS (Part 1)
Overview of SeaDAS 8.4.1 for the Processing, Analysis, and Visualization of Optical Remote Sensing Data for Water Quality Monitoring
Jupyter Notebooks and Python 3.X installed on your computer (optional)