The discharge of sediment-laden rivers into the Mississippi Sound increases the turbidity of coastal waters. The concentration of suspended particulates is an important parameter in the analysis of coastal water quality factors. The spatiotemporal resolution associated with satellite sensors makes remote sensing an ideal tool to monitor suspended particulate concentrations. Accordingly, the presented research evaluated the validity of published algorithms that relate remote sensing reflectance (Rrs) with suspended particulate matter for the Mississippi Sound. Additionally, regression analysis was used to correlate in situ SPM concentrations with coincident observations of visible and near-infrared band reflectance collected by the MODIS Aqua sensor in order to develop a predictive model for SPM. The most robust algorithm yielded an RMSE of 15.53% (n = 86) in the determination of SPM concentrations. The application of this algorithm allows for the rapid assessment of water quality issues related to elevated SPM concentrations in the Mississippi Sound.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-2937 |
| Date | 07 May 2016 |
| Creators | Merritt, Danielle |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
Page generated in 0.0017 seconds