Discipline: Ecology Environmental and Earth Sciences
Subcategory: Geosciences and Earth Sciences
Room: Exhibit Hall
Sulayman Konateh - Bronx Community College
Co-Author(s): Dr Marzi Azarderakhsh City Tech, Dr Reginald Blake City Tech and Dr Hamidreza Norouzi City Tech
Potential Satellite Imagery for Detecting Harmful Algal Blooms Over New York Lakes. Authors:Marzi Azarderakhsh, Sulayman Konateh, Reginald Blake, Hamidreza Norouzi Recently , many national economies have been devastated by the increasing growth and the extensive prevalence of autotrophic algae and heterotrophic protists that are collectively called harmful algal blooms (HABs). HABs occur naturally (circulation, upwelling relaxation, river flow) and anthropogenic waterway discharges that lead to eutrophication. When colonies of these cyanobacteria grow out of control, they deplete oxygen in waters and/or release toxins that put human health at risk, aquatic ecosystems, and livestock resulting in overall adverse impacts to economies. Moreover, these colonies also threaten the water quality of lakes and limit water availability .For decades, methods were developed to detect HABs in potential areas of interest . A possible alternative manner of monitoring the water’s algae levels would be remote sensing, and Landsat-8 and Sentinel-2 observations are well-suited for this type of monitoring application. In this study, we utilized these satellite observations in conjunction with in situ data to examine the effectiveness of existing satellite remote sensing algorithms to develop a regionally robust method that is applicable for lakes in New York. The Google Earth Engine Cloud-based platform and a Machine Learning model were used to develop a monitoring system to detect HABs. The model is trained and validated using Chl-a measurements from various monitoring stations. This approach largely outperforms other traditional experimental algorithms as it is tailored for each individual lake and takes into account other variables including water depth, vegetated water bodies, and previous algal bloom activities. The method presented here may indicate location with high exposure to HABs. However, they might need to be developed and revised specifically on a region by region basis.
Funder Acknowledgement(s): I am going to take this opportunity to acknowledge and thank NSF-REU for this amazing research project. I also wan to say thank to Dr Marzi Azarderakhsh, Dr Reginald Blake, Dr Hamidreza Norouzi, and Prof. Julia Rivera.
Faculty Advisor: Dr Marzi Azarderakhsh, firstname.lastname@example.org