Increasing emphasis is being placed on detecting damage in civil structures in order to estimate remaining life, forestall catastrophic failure, and make more effective use of limited maintenance resources. Image analysis represents a very promising tool for the rapid inspection of large structures that have significant areas unavailable for direct inspection. We describe a straightforward biologically inspired artificial life implementation methodology whereby cellular automata (CAs) can be used to analyze multispectral images of large civil structures to identify structural damage. The size of the CA population can be correlated with structural lifetime, required time to detailed inspection, and other engineering parameters. A simple application of the methodology is described and the results of its operation are presented.