Improvements to land-cover and invasive species mapping from hyperspectral imagery in the Virginia Coast reserve

There are a number of challenges in developing consistent error-free maps of vegetation at the species level from hyperspectral imagery. One of the primary difficulties stems from bi-directional reflectance distribution function (BRDF) effects. Similarly, in applying classification models from one hyperspectral scene to another, BRDF effects also limit the classification accuracy. Other sources of nonlinearity, especially in coastal environments such as coastal wetlands arise from the variable presence of water in pixels as a function of position in the landscape. In a previous paper, we develop an approach to modeling these nonlinearities by deriving nonlinear coordinates that describe the hyperspectral data manifold. In this paper, we examine whether a nonlinear manifold model can he aligned from one hyperspectral scene to another