Developing a Great Lakes remote sensing community

Abstract

Observational data collection of the Laurentian Great Lakes has advanced during the past decade to such a level as to allow real-time analysis from moorings and near real-time from satellite data. Ocean color satellite-based remote sensing provides a rich data set that when properly analyzed allows for the generation of geospatial maps of chlorophyll, dissolved organic carbon, suspended minerals, harmful algae blooms (HABs), surface plumes, benthic vegetation communities, primary productivity (pp) and optical water properties (extinction coefficient (kd), photosynthetically active radiation (PAR) and photic zone depth) on a 2 m to 1 km grid dating back in some cases to the early 1970s. Microwave satellite sensors such as synthetic aperture radar (SAR) and scatterometers provide near real-time information on lake ice cover, winds and waves. Multi-temporal Landsat and ALOS PALSAR satellite data are also being used in the Great Lakes to map wetlands and invasive plantswithin these coastal areas. Airborne LiDARs alsoprovide useful nearshore water depth and bottom type mapping in Great Lakes waters. Making the most of such improvements in the historical Great Lakes datasetwill require diligence and a comprehensive strategy, with recognition of the importance of open collaboration in developing a regional working strategy for remote sensing technologies, sensor data applications, and the datamanagementmethods thatwill integrate the technologies within regional and global observation systems. The IOOS/Great Lakes Observing System (GLOS), in collaboration with NOAA/GLERL, and in conjunction with the ongoing NOAA CoastWatch Great Lakes programwith its stakeholders that include federal, state, local government alongwith theprivate sector and academia, can implement into operational scenarios the suite of remote sensing algorithms developed to generate meaningful Great Lakes products.