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Keeping an Eye on Lake Erie: Using Remote Sensing Imagery to Identify Characteristics of Harmful Algal Blooms

Avouris, Dulcinea M
http://rave.ohiolink.edu/etdc/view?acc_num=kent1532560135731064

Abstract Details

2018, PHD, Kent State University, College of Arts and Sciences / Department of Earth Sciences.
Remote sensing instruments are powerful tools for discriminating between color producing agents (CPAs) that comprise the complex optical signal of Lake Erie. The western basin of Lake Erie (WBLE) is affected by annually recurring cyanobacteria and harmful algal blooms (CyanoHABs), which impact water quality, industry and tourism. In addition to cyanobacteria and algae, sediment and colored dissolved organic material contribute to the optical reflectance signal of Lake Erie waters. CyanoHABs are driven by nutrient input from the Maumee River, and grow in size from spring to fall. Due to the potential of cyanobacteria to produce toxins detrimental to humans and wildlife, identification of the constituents in the CyanoHABs is vital. Both airborne and satellite-based remote sensing instruments provide detailed spectral and spatial information at different scales, and are effective tools for assessing CyanoHABs in Lake Erie. Four images acquired in July of the 2015 CyanoHAB by the Moderate Resolution Imaging Spectroradiometer (MODIS), onboard the NASA Aqua satellite, are analyzed using the Kent State Varimax-rotated principal component analysis (VPCA) spectral decomposition method. MODIS provides basin-wide imagery with a 1 km2 pixel resolution. Four primary signals were extracted, identifying the CyanoHAB signal, a clay sediment and chlorophyll degradation product signal, a hematite and chlorophyll a signal, and a cryptophya signal. The results of the VPCA spectral decomposition of the MODIS showed good agreement with both in situ measured chlorophyll a values in the WBLE, and with the VPCA spectral decomposition results of the reflectance spectra of field samples measured in the lab. The HyperSpectral Imager v2 (HSI2) is an airborne instrument operated by a research team at NASA Glenn, and flown during the 2016 CyanoHAB season. Four images collected on 21 June 2016 and three images collected on 13 September 2016 were analyzed. These two sets of images are of near shore waters in the WBLE, Sandusky Bay, and the Maumee River mouth, and allow comparison of early, pre-bloom, conditions with late bloom conditions. The HSI2 sensor images have a pixel resolution of ~3 m2. This spatial resolution, coupled with hyperspectral band resolution provides detailed results of the spatial distribution of CPAs. A component associated with illite and diatoms was identified, and primarily visible in the images from 21 June 2016, while a component associated with the CyanoHAB signal was primarily visible in the images from 13 September 2016. The 2015 MODIS imagery analysis highlighted a clay sediment and chl- degradation product signal located in the discharge plumes of WBLE tributaries, but was very small in the Maumee River discharge area. The chl-degradation product is associated with colored-dissolved organic matter (CDOM). Wetlands produce and export high amounts of CDOM. An analysis of watershed land use/land cover characteristics was conducted to assess the connections between area of wetlands and the area of CDOM identified by the VPCA spectral decomposition results. This preliminary investigation indicates that the location of the wetland in relation to the watershed outlet plays a role in CDOM presence in the WBLE.
Joseph Ortiz (Advisor)
Anne Jefferson (Committee Member)
Elizabeth Herndon (Committee Member)
Adem Ali (Committee Member)
200 p.
Geology; Hydrology; Remote Sensing
remote sensing; MODIS; hyperspectral instruments; cyanobacteria; Harmful Algal Blooms; Lake Erie; PACE; wetlands; CDOM

Recommended Citations

Citations

  • Avouris, D. M. (2018). Keeping an Eye on Lake Erie: Using Remote Sensing Imagery to Identify Characteristics of Harmful Algal Blooms [Doctoral dissertation, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1532560135731064

    APA Style (7th edition)

  • Avouris, Dulcinea. Keeping an Eye on Lake Erie: Using Remote Sensing Imagery to Identify Characteristics of Harmful Algal Blooms. 2018. Kent State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1532560135731064.

    MLA Style (8th edition)

  • Avouris, Dulcinea. "Keeping an Eye on Lake Erie: Using Remote Sensing Imagery to Identify Characteristics of Harmful Algal Blooms." Doctoral dissertation, Kent State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=kent1532560135731064

    Chicago Manual of Style (17th edition)

kent1532560135731064
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This open access ETD is published by Kent State University and OhioLINK.
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