Composition of salt marsh vegetation is important to wetland ecosystem health, and monitoring invasive species is critical. The purpose of this study was to examine the utility of airborne hyperspectral imagery in mapping salt marsh vegetation in Humboldt Bay, California, USA. An unmixing algorithm was applied to spatial and spectral image subsets. Overall accuracy among Spartina densiflora, Salicornia virginica, and Distichlis spicata was assessed at 85.1%. Algorithm prediction between observed and predicted percent cover ranged from r2 = 0.32 to r2 = 0.53, an improvement on comparable studies. Percent cover prediction was least accurate for Distichlis spicata, due to initial endmember selection. Use of the Pixel Purity Index in conjunction with field work likely aided in identifying the best candidates for the linear unmixing technique.
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