Progressive band selection (PBS) reduces spectral redundancy without significant loss of information, thereby reducing
hyperspectral image data volume and processing time. Used onboard a spacecraft, it can also reduce image downlink
time. PBS prioritizes an image's spectral bands according to priority scores that measure their significance to a specific
application. Then it uses one of three methods to select an appropriate number of the most useful bands. Key challenges
for PBS include selecting an appropriate criterion to generate band priority scores, and determining how many bands
should be retained in the reduced image. The image's Virtual Dimensionality (VD), once computed, is a reasonable
estimate of the latter. We describe the major design details of PBS and test PBS in a land classification experiment.