Analysis of Coincident HICO and Airborne Hyperspectral Images Over Lake Erie Western Basin HABs

Abstract:

Harmful algal blooms (HABs) produce waterborne toxins that pose a significant threat to people, livestock, and wildlife. 40 million people in both Canada and the U.S. depend on Great Lakes water. In the summer of 2014, in the Lake Erie Western Basin, an HAB of the cyanobacteria Microsystis was so severe that a water-use ban was in effect for the greater Toledo area, Ohio. This shut off the water supply to over 400,000 people from a single water intake. We investigated bloom intensity, composition, and spatial variability by comparing hyperspectral data from NASA's HICO, multispectral data from MODIS spaceborne imagers and NASA GRC's HSI imagers to on-lake ASD radiometer measurements using in situ water quality testing as ground reference data, all acquired on a single day during the bloom in 2014. HICO imagery acquired on Aug 15, 2014 was spatially georeferenced and atmospherically corrected using empirical line method utilizing on-lake ASD spectra. HSI imagery were processed in a similar way. Cyanobacteria Index (CI) images were created from processed images using the Wynne (2010) algorithm, previously used for MODIS and MERIS imagery. This algorithm-generated CI images provide reliable results for both ground level (R²=0.7784), and satellite imagery (R²=0.7794) for seven sampling points in Lake Erie’s western basin. Spatial variability in the bloom was high, and was not completely characterized by the lower spatial resolution MODIS data. The ability to robustly atmospherically correct and generate useful CI maps from airborne and satellite sensors can provide a time- and cost-effective method for HABs analysis. Timely processing of these high spatial and spectral resolution remote sensing data can aid in management of water intake resources.