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This study developed satellite remote sensing models to detect cyanobacterial blooms via chlorophyll a in Lake Champlain. Landsat Enhanced Thematic Mapper Plus data was used to retrieve chlorophyll a concentrations, phytoplankton, and cyanobacteria biovolume by calibrating and validating with coincident observation data. Correlation analysis results showed that band 2 (green band) and the band ratio of 2/1 (green/blue) were most highly correlated to chlorophyll a concentration (r = 0.76 and 0.82, respectively). Multiple regression results identified band 2 and 3 (red), and band ratio of 2/1 and 3/1 (red/blue) as critical information to estimate chlorophyll a concentrations. The regression models accounted for 72 to 83% of the variability in chlorophyll a observations, allowing for estimates of phytoplankton and cyanobacteria levels in the lake. Satellite image processing results successfully showed the temporal and spatial distribution of chlorophyll a, phytoplankton, and cyanobacteria in the lake. This information can be used to evaluate the effect of pollution sources and weather conditions, and assist decision making for water management.

Cyanobacteria bloom events have been associated with eutrophication processes, along with hydrologic and climate factors. Missisquoi Bay is a portion of Lake Champlain (USA–Canada) that is highly eutrophic and prone to cyanobacteria blooms and cyanotoxins. This study assessed the spatial–temporal influence of nutrients, turbidity and temperature in cyanobacteria distributions during a bloom event in the summer of 2006. Correlations, generalized linear models (GLMs), geostatistics and local indications of spatial association (LISA) autocorrelation analysis tested the influence of nutrient and non-nutrient explanatory variables in cyanobacteria biovolume. Total phosphorus exhibited a high direct correlation with cyanobacteria biovolume. The best performing GLMs included total phosphorus, total nitrogen, Secchi depth (as turbidity) and temperature as explanatory variables of cyanobacteria biovolume. Variogram analysis of those variables resulted in a better understanding of the underlying spatial variation process of the cyanobacteria bloom event. The LISA test revealed a moderate but stable autocorrelation between cyanobacteria biovolume and total phosphorus from 180 to 1,000 m of weight distance, suggesting the possibility of up-scaling the current results to coarse-resolution satellite imagery for more frequent monitoring of bloom events. The LISA test also revealed the spatial–temporal dynamic (movement of cyanobacteria scums) of high cyanobacteria blooms with high total phosphorus concentration.

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