Information elasticity is a new concept proposed by us to assess the role of information in making effective decisions in sensor processing. Information elasticity is defined as the ratio of the fractional increase in decision effectiveness to the fractional increase in information. One such application is the role of bandwidth when applied to target detection in ground clutter. Continuous, uniformly distributed, land clutter, such as snow, sand, or dirt, has a normalized radar cross section (NRCS) that increases with frequency in the microwave region of the electromagnetic (EM) spectrum. If a target’s radar cross section (RCS) increases slower than the clutter that surrounds it as the signal bandwidth increases, this can limit the amount of useful fractional bandwidth that can be used for achieving high range resolution. Using equations for the RCS of a typical sphere target and the overall NRCS of land clutter, it is possible to determine the signal-to-clutter ratio (SCR) at differing fractional bandwidth percentages. If the size of the frequency bins measured is kept constant, a higher fractional bandwidth will have more frequency bins causing an increase in processing time and therefore a decrease in the elasticity. Several different target shapes and types of distributed clutter were simulated, and it is shown that there can be a decrease in elasticity when the fractional bandwidth exceeds a certain value. Furthermore, factoring in the sensor processing time shows that there exists a tipping point beyond which information overload occurs resulting in negative elasticity.