Abstract
The Oysters in the Mississippi Sound are depleting because of a range of environmental and anthropogenic stressors. While some of the organic matter in water can be helpful for oyster survival and growth, the detritus in the suspended particulate matter (SPM) can foul these suspension feeding animals. Oysters are also subjected to additional stress because of bioavailability of the contaminants associated with SPM. Runoff from adjacent watersheds and resuspension of bottom sediments increase SPM in the water column. Remote sensing is useful in mapping the spatio-temporal distribution of SPM. The overarching objective of this research is to develop remote sensing algorithms for mapping SPM using Unmanned Aerial Systems (UAS). UAS imagery was collected by 71 flights during seven week-long trips in the months of March, May, June, July, and December 2018, and June and July, 2019 over the Henderson Point and Pass Christian Oyster Reefs, Mississippi, the largest oyster reef in the Mississippi Sound. Water samples and ancillary data were also collected from 71 locations during each flight. An empirical algorithm was developed using field data and data collected using a handheld radiometer. A series of image processing techniques were applied to the UAS imagery and the output were validated using a second method of image processing to ensure the accuracy of the UAS imagery output. The SPM algorithm was then applied to all the UAS imagery to generate SPM images. Subsequently, a time series analysis was performed with discharge to the Wwestern Mississippi Sound. The outcome of this study will not only help monitoring the water quality over the oyster reef in Mississippi but also the procedures developed to process the UAS imagery and algorithm development could act as a blueprint for future research in exploring the potential of using UAS for remote sensing of water quality.
