Dynamic Spectrum Access (DSA) radios typically select their radio channels according to their data networking goals, a defined DSA spectrum operating policy, and the state of the RF spectrum. RF spectrum sensing can be used to collect information about the state of the RF spectrum and prioritize which channels should be assigned for DSA radio waveform transmission and reception. This paper describes a Greedy Channel Ranking Algorithm (GCRA) used to calculate and rank RF interference metrics for observed DSA radio channels. The channel rankings can then be used to select and/or avoid channels in order to attain a desired DSA radio performance level. Experimental measurements are collected using our custom software-defined radio (SDR) system to quantify the performance of using GCRA for a DSA radio application. Analysis of these results show that both pre and post-detection average interference power metrics are the most accurate metrics for selecting groups of radio channels to solve constrained channel assignment problems in occupied gray space spectrum.