Using hyperspectral data to classify vegetation at the plant functional type-level in mountain terrain at three spatial resolutions

Hyperspectral data covering the visible, near infrared, and shortwave infrared portions of the electromagnetic spectrum have been used to map vegetation at the plant functional type and species levels in a variety of ecosystems. Vegetation maps are basic to the study and analysis of natural resources and are an important component in documenting and understanding the impacts of environmental changes in ecosystems due to human-induced changes (e.g., climate change). Multiple methods for mapping vegetation have been developed to take advantage of the large number of bands (> 200) and spectral contiguity that hyperspectral data provide. The purpose of this study is to determine what the limitations and potential areas of success are for using hyperspectral remote sensing data to classify vegetation cover in steep mountainous terrain at the plant functional type level.