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After years of remote sensing work, Joseph Ortiz, Ph.D., a professor in the Department of Geology in the College of Arts and Sciences at ������, and his research team recently shared their development of new cost-efficient methodologies that may lead to much safer drinking water for people in Ohio and other municipalities affected by harmful algal blooms (HAB).

While conducting fieldwork in the western basin of Lake Erie, Ortiz recently posted to his Twitter account, “The HAB was so thick you could not see 20 centimeters below the water surface. Bad, but it can get much worse.” He was one of the participants in the 2019 HAB Grab, which took place on Aug 7. 

“We are now able to get the validation data to compare the results that we are extracting from NASA Glenn aerial and orbital sensors directly with field observations,” Ortiz said. “We’re really encouraged by the results we’re seeing.”

Ortiz and his colleagues recently published two scientific papers on their spectral decomposition method in the Journal of Great Lakes Research. They also presented the results at both the International Ocean Colour Science Meeting and the National Oceanic and Atmospheric Administration Coast Watch meeting. To read the first article, visit .

To read the second article, visit .

The researchers developed a strategy to get rid of the interference seen between different types of material in the water, such as phytoplankton and algal blooms of different types, when viewed with satellite imagery. Cyanobacteria have different pigment characteristics than eukaryotes or organisms that have internal organelles. The different types of pigment can interfere with each other due to the absorption and scattering properties of the light as it is passing through those organisms. That information, along with the contributions from decaying organic matter and suspended sediment can lead to biased results from the satellite measurements.

“We’ve developed a way to separate out those complex signatures so that they don’t interfere with each other,” Ortiz said. “The real big advantage that we get from that is it lets us get better specificity, so that when we say that we are identifying something that contains chlorophyll or some other accessory pigment, we have more confidence that we’ve actually identified that properly.”

In addition, the researchers get back a lower detection limit and can use their method earlier in the season, before the bloom gets larger, by several orders of magnitude.

“Because of the increased specificity, we can separate the signal and see what is going on, even when there is suspended sediment in the water, early in the season, or when there are degraded pigments later in the season,” Ortiz said. “That lets us monitor over a much broader time period than we can with conventional remote sensing techniques.”

The researchers are trying to put together the data sets so that they can confidently show the applicability of this method in multiple environments. They have shown that it works in Lake Erie and Biscayne Bay in South Florida. They are starting to make measurements in Lake Okeechobee in Florida, as well.

“If we can use this in multiple environments, then that holds the potential to apply it to many different locations,” Ortiz said. “We’ve also made use of these with a large number of different sensors, and that gives us the opportunity to take these methods back in time so that we can see how the system has evolved from the earlier parts of remote sensing time series (as far back as the early 1980s) to present. So, that will help in terms of the future planning strategies or looking at climate change-related questions as well.”

Ortiz explained that a strength of their approach is that they can apply it to any type of visible sensor that they work with. It is platform-independent, and the results are independent of the spatial scale of the measurement. They can apply this on sensors that collect samples over a 10 centimeter spot size or a one kilometer spot size and still get very good results.    

The researchers are also able to boost the signal-to-noise ratio by a factor of 20, relative to traditional techniques using this methodology. The signal-to-noise ratio is the ratio of the signal variability divided by the noise variability across the spectrum.

“From a cost-saving standpoint, that’s huge,” Ortiz said. “One of the things that folks are really concerned about it is trying to build better sensors that have a higher signal-to-noise ratio and doing that is tough from a hardware standpoint. So, you can imagine that if we can develop a software-based approach that can be applied retroactively toward older sensors, that is a really big accomplishment.”

Ortiz collaborates with John Lekki, Ph.D., of NASA Glenn Research Center and other researchers working in Lake Erie. The research work is supported by NASA and the H.W. Hoover Foundation, a private foundation that funds water quality research both here in Ohio (based in Canton, Ohio) and Florida. The endowment, developed from the Hoover Foundation and Herbert W. Hoover Jr., was instrumental in the founding of Biscayne Bay National Park in Florida.

Several graduate students have worked with Ortiz on this research, including Dulci Avouris, Ph.D., who completed her doctoral degree in Ortiz’s lab and is currently working with him as a postdoctoral researcher, supported by the H.W. Hoover Foundation. Ortiz said, “She was instrumental in the development of the software that we use for these methods.”

Graduate student Edgar Ferguson is doing work in Lake Erie, and Scarlett Henson is working in Lake Okeechobee, along with Avouris, who is also applying the method in Biscayne Bay National Park. Taylor Judice, who is completing his master’s, applied the method in the Indian River Lagoon, also in Florida.

“What we’re are hoping is that the municipalities in the areas around Lake Erie will start to learn about the work that we’ll be doing and gain an interest in letting us apply these kind of methodologies in order to address HAB-related questions,” Ortiz said. “We are trying to increase the applicability of our methodologies to many different areas, including the ocean and coastal areas.”

For more information about ������’s Department of Geology, visit www.kent.edu/geology.

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Media Contacts:
Jim Maxwell, jmaxwel2@kent.edu, 330-672-8028
Emily Vincent, evincen2@kent.edu, 330-672-8595