Oral Session 9

Thursday, October 10
14:50–15:50

Oral Session | 1 | 2 | 3 | 4 | 5 | 67 | 8 | 9 | 10 | 11 | InstructionsSchedule at a Glance

15:10-15:30 | ABSTRACT 1007

Using hyperspectral imagery to discriminate cyanobacteria harmful algal blooms at relevant field scales: from unmanned aircraft systems to emerging satellites

Harmful algal blooms (HABs) pose a significant threat to water quality as they adversely affect public health, the aquatic environment, and the economy. As natural resource agencies are increasingly monitoring for HABs, remote sensing tools offer a consistent, spatiotemporal approach to assess water quality. To date, multispectral remote sensing has been utilized to quantify HABs by estimating algal biomass proxies such as chlorophyll-a, phycocyanin pigment concentrations, and cell counts. Emerging technologies like hyperspectral imagers (HSIs) and unmanned aircraft systems (UAS) may significantly improve monitoring of cyanobacteria blooms. HSIs enable capturing subtle differences in the reflectance of phytoplankton types at different taxonomic levels. Thus, HSIs may offer capabilities to monitor phytoplankton community composition. This study conducted a UAS-HSI survey in Milford Lake, KS, USA, to demonstrate that HSIs could discriminate different species of cyanobacteria. This study compared field imagery to a previously constructed cyanobacteria spectral library spanning over 17 unique strains of cyanobacteria. A spectral classifier pipeline was developed from reflectance measurements to predict the dominant cyanobacteria species. The validation of the spectral classifier on hyperspectral data cubes collected from the UAS platform showed remarkable accuracy, instilling confidence in the method’s effectiveness and transferability of the spectral library for routine monitoring. The application of the spectral classifier to NOAA’s HAB Mapper, another UAS-HSI sensing platform, and PACE-OCI image data in larger water bodies will be discussed, highlighting the potential for mapping cyanobacteria species and the overall success and challenges of deriving phytoplankton community composition from space.

Sachidananda Mishra, NOAA, USA, https://orcid.org/0000-0001-6613-3103

Scott Bourne, Environmental Laboratory, US Army Engineer Research and Development Center, USA

Laura Webb, US Environmental Protection Agency (EPA) Region 7, USA

Michael Baker, Environmental Laboratory, US Army Engineer Research and Development Center, USA

Kenneth Matheson, Environmental Laboratory, US Army Engineer Research and Development Center, USA

David Berthold, University of Florida, USA

Dail Laughinghouse, University of Florida, USA

Richard Johansen, Environmental Laboratory, US Army Engineer Research and Development Center, USA

Molly Reif, Environmental Laboratory, US Army Engineer Research and Development Center, USA

Richard Stumpf, NOAA National Centers for Coastal Ocean Science, USA

Kaytee Pokrzywinski, NOAA National Centers for Coastal Ocean Science, USA

Oral Session | 1 | 2 | 3 | 4 | 5 | 6
 7 | 8 | 9 | 10 | 11
InstructionsSchedule at a Glance

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