SATELLITE MONITORING OF INCIPIENT CYANOBACTERIAL BLOOMS IN THE GREAT LAKES

An algorithm has been developed and published (Vincent et al, 2004) for mapping water content of phycocyanin, a pigment more uniquely associated with cyanobacteria than is chlorophyll, from LANDSAT TM data, which has 16-day repeat cycles and 30 m pixels. Though produced by multiple regression from water samples collected during one LANDSAT TM overpass, the algorithm has been tested on water samples collected on other overpass dates, as well. Incipient blooms, with phycocyanin content between 1-6 µg/liter, were used to develop the algorithm, which appears to work well for phycocyanin contents up to approximately 20 µg/liter. Other algorithms that work for SeaWiFS and MODIS are being developed, with satellite sensors that have much larger pixel sizes (250-1,000 m), but provide much more frequent (1-day) repeat cycles. Regular monitoring of incipient blooms in the Great Lakes by satellites would help warn municipal water plants that have water intakes from the Great Lakes (such as Toledo and Cleveland) or from smaller lakes (down to 50-acre drinking water reservoirs in the case of LANDSAT TM data) of potential blooms, permitting them to chemically destroy the blooms while they are small, or to stock chemicals necessary for the plants to handle the toxins sometimes released by blooms that are permitted to become large. Such monitoring would also be helpful in searching for correlations, if any, between cyanobacterial blooms and anoxic ( or “dead”) zones near the bottom of Lake Erie in the Central Basin.

Vincent, R.K., X. Qin, R. M. L. McKay, J.Miner, K. Czajkowski, J. Savino, and T. Bridgeman, 2004, Phycocyanin Detection from LANDSAT TM Data for Mapping Cyanobacterial Blooms in Lake Erie, Remote Sensing of Environment, Vol. 89, No. 3, pp 381-392.