Bergner, J.; Wallin, D.; Yang, S., and Rybczyk, J., 2025. Using drone-captured imagery and a digital elevation model to differentiate eelgrass species: Padilla Bay, Washington. Journal of Coastal Research, 41(1), 105–121. Charlotte (North Carolina), ISSN 0749-0208.

There are two primary species of eelgrass at the Padilla Bay National Estuarine Research Reserve, Zostera marina, a native eelgrass, and Zostera japonica, a nonnative. Recently, unoccupied aerial systems (UAS) have been used for eelgrass monitoring and mapping since imagery can be collected frequently and during different seasons. This project, conducted from April to September 2022, utilized UAS imagery, elevation data, and eelgrass vegetation surveys in the intertidal zone to identify regions with Z. japonica–dominant, mixed, and Z. marina–dominant cover. Multispectral imagery, using random forest (2000 trees) classification and eelgrass vegetation survey data, was used to predict eelgrass cover categories. Z. japonica–dominant, mixed, and Z. marina–dominant cover differed spectrally due to speciation and canopy characteristics, but low Z. japonica–dominant cover and exposed mud significantly decreased the accuracy in predicting that cover class in April and May. The overall accuracy predicting Z. japonica–dominant, mixed, and Z. marina–dominant cover was 75% using multispectral data alone. When multispectral imagery was combined with a 1-m-resolution digital elevation model (DEM) with a vertical error of 4.3 cm, the overall accuracy rose to 89%. Accuracy for each cover category rose as well. Most notably, Z. japonica–dominant cover rose from a user's accuracy of 71% to 92%. Z. japonica–dominant cover increased by 0.3 km² from April to September. Mixed cover slightly increased from April to May, and Z. marina–dominant cover remained relatively consistent through the months. This is the first study to yield highly accurate classification between Z. japonica– and Z. marina–dominant cover, and results can be further improved through additional management of spectral variation.