​Overview: 
Satellite imaging systems have been widely used to support water quality and quantity management as it allows water quality analysis using empirical and semi-analytical relationship between optically active constituents (e.g., sediments, chlorophyll-a, dissolved organic matter) and spectral water reflectance. (Dekker et al., 1993; Lee et al., 2002; Matthews, 2011; Odermatt et al., 2012). NASA Landsat 8/9 OLI and ESA Sentinel-2 MSI are the most relevant medium spatial resolution data sources for water applications, and the data harmonization from both optical sensors into a single data set, so-called “virtual constellation”, creates an unpreceded opportunity with a repeat frequency of ~ 3 days on average, and higher probability to obtain a cloud-free mapping of water constituents than Landsat or Sentinel-2 alone (Claverie et al., 2018).

This research project will develop and validate a harmonized Landsat-Sentinel-2 framework for water reflectance retrieval in optically complex waters. This sensor-generic framework will solve complex radiative transfer calculations to derive water reflectance products across Mississippi inland and coastal waters. Landsat-Sentinel-2 water reflectance product will be validated with collected in situ radiometric data, and water samples will be used to develop and validate a turbidity algorithm on the Mississippi Gulf coast.

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