Changes in Carlson’s Trophic State Index (TSI) through time for TSI calculated with chl-a concentrations through time. Gray squares represent spring data, black circles represent summer data, triangles represent fall data, and crosses represent winter data. Seasons were defined according to Trenberth (1983)

Changes in Carlson’s Trophic State Index (TSI) through time for TSI calculated with chl-a concentrations through time. Gray squares represent spring data, black circles represent summer data, triangles represent fall data, and crosses represent winter data. Seasons were defined according to Trenberth (1983)

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In situ monitoring of freshwater systems is often constrained by cost and accessibility, particularly in developing countries and in remote areas. Satellite remote sensing is therefore increasingly being integrated with existing in situ water quality monitoring programs. In this study, we use the Landsat TM/ETM+ image record collected between 1984...

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Thesis
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Water clarity has been extensively assessed in Landsat-based remote sensing studies of inland waters, regularly relying on locally calibrated empirical algorithms, and close temporal matching between field data and satellite overpass. As more satellite data and faster data processing systems become readily accessible, new opportunities are emerging to revisit traditional assumptions concerning empirical calibration methodologies. Using Landsat 8 images with large water clarity datasets from southern Canada, we assess: (1) whether clear regional differences in water clarity algorithm coefficients exist and (2) whether model fit can be improved by expanding temporal matching windows. We found that a single global algorithm effectively represents the empirical relationship between in situ Secchi disk depth (SDD) and the Landsat 8 Blue/Red band ratio across diverse lake types in Canada. We also found that the model fit improved significantly when applying a median filter on data from ever-wider time windows between the date of in situ SDD sample and the date of satellite overpass. The median filter effectively removed the outliers that were likely caused by atmospheric artifacts in the available imagery. Our findings open new discussions on the ability of large datasets and temporal averaging methods to better elucidate the true relationships between in situ water clarity and satellite reflectance data.