A Comparison of Forest Classification using Hyperion and AVIRIS Hyperspectral Imagery

We test how well a cluster-based unsupervised classification algorithm separates forest land covers. Our test data, Hyperion and AVIRIS images taken in northern Virginia during autumn, provide two spectrally distinct land covers: pine forests and senescent deciduous forests. We find that the algorithm successfully separates these land covers for AVIRIS data that has been spatially aggregated to simulate 30-m Hyperion GSD. The algorithm does not successfully separate the land covers for the Hyperion data.