This paper describes a study in progress. Its objective is to investigate the effects of spectral and spatial resolution, spectral coverage, signal-to-noise (SNR), and terrestrial background environments on hyperspectral exploitation performance and to determine their tradeoffs. The trade space and the methodologies used to perform nonliteral exploitation functions such as anomaly/target detection, material identification, and abundance estimation are described. Of the three exploitation functions, only summary anomaly/target detection results are presented in this paper. They are presented as a function of 4 spatial resolutions, 4 spectral resolutions, 2 spectral regions, 2 SNR levels, and 2 backgrounds. Anomaly/target detection performance comparison is made in terms of detection success rate when the false alarm rate is held constant for all image cubes. Within the study's trade space,results so far indicate that spatial resolution is the most important parameter for anomaly/target detection, followed by SNR and spectral resolution. Subsequent work on the effects of the same sensor design parameters on material identification is near completion and results will be documented in the very near future.