Remote sensing time series observations of Lake Michigan Water Quality Parameters
Remote sensing provides a method to accurately assess water quality for current and historical conditions in large lakes such as Lake Michigan. Satellite sensors such as SeaWiFS and MODIS collect data that span large geographic areas and have been in operation for more than a decade, with some satellite programs that have existed since the 1970s. This remote sensing “time machine” allows scientist to analyze a time series of data and determine how water quality conditions have changed, particularly in light of a changing climate. Augmentation of remotely sensed data with sound in-situ measurements allows scientists to gain a deeper understanding of changes in the Great Lakes. This presentation reviews a variety of methods/products produced by Michigan Tech Research Institute that aid in the assessment of changes in water quality. Using remote sensing derived data, ancillary observations (meteorological, stream-flow, etc…) that help describe the time series analysis, and in-situ measurements the water quality and water characteristics of Lake Michigan over time can be accurately assessed. Remote sensing analysis outputs included retrieving color-producing agent (CPA) products (chlorophyll, suspended minerals, and dissolved organic carbon concentrations), sediment plume extents, optical water parameters, and in areas such as Green Bay, harmful algal bloom extents.
Lake Michigan: State of the Lake, Great Lakes Beach Association Conference 2013
Banach, D. M.,
Remote sensing time series observations of Lake Michigan Water Quality Parameters.
Lake Michigan: State of the Lake, Great Lakes Beach Association Conference 2013,
Retrieved from: http://digitalcommons.mtu.edu/mtri_p/122