Hyperspectral imagers sample the electromagnetic spectrum at greater resolution than more traditional imaging systems, which result in a higher band-to-band correlation and greater amounts of data. With bandwidth limitations on the communications channels and storage space, intelligent system design, band selection, and/or data compression will be very important. The data from a new hyperspectral sensor, SEBASS, which collects data in the thermal IR was characterized for compression. As expected, it was found that the data's spectral characteristics were very dependent on scheme content and the collection time of day. It was found that the band-to-band correlation was greater in this data than either HYDICE or AVIRIS hyperspectral data. Compression ratios of 7:1 lossless and 20:1 with minimal loss were achieved compared to 3:1 lossless and 7:1 lossy for HYDICE and AVIRIS data. This increase in compression is directly attributable to the increase in band-to-band correlation. Unique characteristics of the thermal IR hyperspectral data is also discussed.