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Breaking the barriers to adopting satellite remote sensing for water quality management: ?monitoring cyanobacteria blooms
Citation:
Schaeffer, B., R. Conmy, R. Lunetta, R. Stumpf, AND D. Keith. Breaking the barriers to adopting satellite remote sensing for water quality management: ?monitoring cyanobacteria blooms. Presented at World Lake Conference, Perugia, ITALY, September 01 - 05, 2014.
Impact/Purpose:
The goal of this project was to validate a cyanobacteria algorithm and develop a stakeholder tool with the capability to monitor cyanobacteria blooms near real-time.
Description:
Remote sensing technology has the potential to inform and accelerate the engagement of communities and managers in the implementation and performance of best management practices. Over the last few decades, satellite technology has allowed measurements on a global scale over long time periods, and is now proving useful in characterizing lakes and reservoirs, which are relevant to water quality managers. Comprehensive water quality climate data records have the potential to provide rapid water quality assessments, thus providing new and enhanced decision analysis methodologies and improved temporal/spatial diagnostics. Four main barriers were identified by water quality managers that inhibit the consideration of satellite remote sensing data: cost, accuracy of data products in the particular waterbody of interest, satellite mission continuity, and obtaining management approval for including satellite data into their work. In the research presented here, a study on the monitoring of cyanobacteria from the European Space Agency’s MEdium Resolution Imaging Spectrometer (MERIS) instrument was used to understand how some of these barriers could be addressed. Cyanobacteria cell count data from eight U.S. states were derived with data from MERIS. A validation of satellite estimates of cell counts was performed using available in situ data assembled over a 39-month period spanning 2009–2012. The goal of this project was to validate a cyanobacteria algorithm and develop a stakeholder tool with the capability to monitor cyanobacteria blooms near real-time.
