Purpose
Living Shorelines Provide a Nature-Based Approach to Coastal Protection. Unsustainable harvesting habits and a steady decline in water quality have led to population decline locally and globally. NOAA has identified oyster reef restoration as a conservation.
Mapping wild oyster reefs presents formidable challenges. Using traditional on-site techniques are laborious due to the rugged terrain of oyster habitat. The following research outlines remote sensing techniques used to monitor oyster populations.
Methodology
1. Data collection of aerial imagery (2013, 2018) and preprocessing of data.
2. Digitizing to create a subset of data limited to oyster vs. non-oyster areas to reduce spectral confusion between oysters and vegetation.
3. Classification of oyster polygons into density classes- high, moderate, low, and non-oyster
4. Statistical analysis and cartographic products to evaluate change.
Results
Accuracy assessment results put the classification methodology at 74-76%.
In 2013, Oysters comprised 78.2% of the total digitized polygons within the park and the non-oyster class comprised 21.8% of the total digitized polygons within the park. Low to lowest-density oysters occupy 39.2 acres of the park and compose 73.2% of the non-oyster population. This is the highest population density class in 2013.
In 2018, Oysters comprise 78% of the total digitized polygons within the park and the non-oyster class comprises 22% of the total digitized polygons within the park. Moderate to moderately low-density oysters occupy 26.9 acres of the park and constitute 43.1% of the non-oyster population. This is the highest population density class in 2018.
There is a notable shift from low density populations to moderate and high-density populations over time.
Conclusion
Ground truthing would greatly improve accuracy. The ideal solution to monitoring this population would be data collection of small sample areas, using high-resolution multispectral drone imagery paired with the process outlined in this research.