1.What are harmful algal blooms (HABs)? Contrast of HABs to functional groups What must be known to detect HABs Environment Simple physiology and ecology Ecological conditions “Operational” vs research considerations Work exercise: A strategy to respond to reports of a HAB 2.Methods Chlorophyll Change detection Analytical algorithms Spectral shape (MCI, FLH, CI) Other algorithms (brightness, empirical, etc.) Ancillary data (SST, winds) Ensemble methods Work exercise: Case Study (to be provided) 3.Using satellite Limitations defined by objective, method, species, environment Satellite strengths and weakness Algorithm failures Atmospheric correction challenges Work exercise: identify best method for a case study (to be provided) 4.Validation Quantitative data vs qualitative data False positives and false negatives Field observations (ocean color, cells, toxins, impacts) Work exercise: sampling strategy 5.Applications Advisories Forecasts “Event response” (dead marine mammals, fish kills, bird kills, sickness) Discussion of case studies Bibliography J. GOWER, S. KING, G. BORSTAD and L. BROWN (2005). Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer International Journal of Remote Sensing 26(9): 2005–2012 Stumpf, R.P. and M.C. Tomlinson (2005) Remote sensing of harmful algal blooms. In: Miller, R.L., C.E. Del Castillo, and B.A. McKee, eds. Remote Sensing of Coastal Aquatic Environments. Springer, AH Dordrecht, The Netherlands, chapter 12, pp. 277‐296. Stumpf, R.P. (2006) Forecasting Harmful Algal Blooms: The Roles of Optical Oceanography and Remote Sensing. Material presented at Ocean Optics XVIII. Wynne, T. T., Stumpf, R. P., Tomlinson, M. C., and Dyble, J. (2010). Characterizing a cyanobacterial bloom in western Lake Erie using satellite imagery and meteorological data. Limnol. Oceanogr., 55(5), 2025–2036