| Summary: | Graduate The goal of this research was to construct a time series of accurate chlorophyll-a concentration for the Strait of Georgia (SoG), Canada, using an improved atmospheric correction scheme and workflow for the Moderate Resolution Imaging Spectroradiometer AQUA (MODIS) satellite instrument to describe the chla dynamics and spring bloom phenology in the SoG. In situ radiometric samples were acquired via Aerosol Robotic Network (AERONET), and hyperspectral data collected from a Hyperspectral Surface Acquisition System (HyperSAS) to assess three potential atmospheric correction schemes. Water property samples including total suspended material (TSM), chromophoric dissolved organic matter (CDOM), and chlorophyll concentrations (chla) were collected to further assess atmospheric corrections and the applied ‘Ocean Color 3 Modis’ (OC3M) standard chlorophyll algorithm. Regression, Absolute percentage difference (APD), Relative Percentage difference (RPD), and Root mean squared error (RMSE) analysis revealed the most appropriate method to be the ‘Management Unit of the North Seas Mathematical Models’ (MUMM) using the shortwave infrared spectrum (SWIR) to determine NIR-derived aerosol model. This method was used to construct a time series (July 2002-June 2014) of daily chlorophyll maps for all available imagery. Files were spatially binned into 8-day composites for the North and Central SoG where a modified threshold-based definition was used to determine the start of the spring phytoplankton bloom period, as well as timing of maxima and duration of the largest spring bloom. Results indicate Central SoG start dates range from late February to late April, with an average start date at the last week of March. These results compare favorably to Hindcast predictive modelling of bloom start dates. The Northern SoG bloom phenology starts on average 9 days earlier, and experiences lower chlorophyll-a magnitudes. Hierarchical clustering with correlation similarity of spring seasons indicate 2008 and 2007 were anomalous, ...
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