Date of Award
Open Access Dissertation
Doctor of Philosophy in Geology (PhD)
Administrative Home Department
Department of Geological and Mining Engineering and Sciences
Committee Member 1
Committee Member 2
Freshwater lakes are an important component contributing to ecosystem health and biodiversity on local, regional, and global scales. And while lakes only represent <5% of the global surface area, they are often very productive systems which contribute significantly to carbon cycling dynamics and freshwater fish production on a number of spatial scales. Due to the remote location and sheer size of some of these lakes it has proven difficult to adequately document changes in water quality. Significant challenges exist to adequately monitor water quality, and in particular phytoplankton dynamics, over large spatial and temporal scales using traditional in situ methods. Satellite electro-optical remote sensing offers a potential tool to provide better characterization of phytoplankton dynamics for a variety of freshwater systems. This work resulted in an approach to quantify global summer phytoplankton abundance using a newly developed remote sensing derived chlorophyll-a product. This product was also used in conjunction with a newly created carbon fixation model to assess global freshwater phytoplankton production which provided new insights into the role freshwater systems play in the global carbon budget. Spatial and temporal assessments of specific populations of phytoplankton and cyanobacteria were established through the development of a new remote sensing algorithm to isolate high biomass assemblages in the Laurentian Great Lakes (Lake Erie, Lake Huron, Lake Michigan). The algorithm was developed to facilitate the fusion of multiple remote sensing data sources (SeaWiFS and MODIS) in order to generate a new 20-year time-series data product to better understand the factors controlling bloom dynamics. Finally, a spatio-temporal analysis documenting the variability of inherent optical properties (IOPs) in Lake Erie established a seasonal progression of phytoplankton/cyanobacteria community structures for two years over the vegetative season, the findings of which are critical for the development of the next generation of hyperspectral remote sensing algorithms to improve phytoplankton community characterizations from space. These documented results clearly show the utility of electro-optical remote sensing to provide characterization of phytoplankton dynamics and insights at both community and population scales in freshwater systems.
Sayers, Michael, "CHARACTERIZING FRESHWATER PHYTOPLANKTON DYNAMICS WITH ELECTRO-OPTICAL REMOTE SENSING", Open Access Dissertation, Michigan Technological University, 2019.